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1. Eje Edit View Go Tools Window Help AAA AAA USA TEetet d No and atar ani _ Pe Ar nin AS SCE See as PT 88 jel as a Y DENIA TDMA IAEA IAS TAS FEAS AO A o Location fr Connections mat o AE OSITOS SLANE I DIES DOI LIDS L AAA ID DI DIA IDOLS PPP D DNAS PROP TADO RADA Stylesheet ere nr TED DOE as s Contents s rem adaa hacks Add OLE DB Connection 2 Add Spatial Database Connection cee Y 8 D El f Database Connections 3 Add OLE DB Connection Add Spatial Database Conr Q Address Locators Eis GIS Servers a A Search Results Figure 44 Adding an OLE DB Connection in ArcCatalog In the Data Link Properties select Microsoft OLE DB Provider for ODBC Drivers Figure 45 and click Next gt gt Data Link Properties Provider Connection Advanced All Select the data you want to connect to OLE DB Provider s MediaCatalogDB OLE DB Provider MediaCatalogMergedDB OLE DB Provider MediaCatalogebDB OLE DB Provider Microsoft Jet 4 0 OLE DB Provider Microsoft OLE DB Provider For Data Mining Services Microsoft OLE DB Provider for Internet Publishing Microsoft OLE DB Provider for ODBC Drivers Microsoft OLE DB Provider for OLAP Services 8 0 Microsoft OLE DB Provider for Oracle Microsoft OLE DB Provider for Outlook Search Microsoft OLE DB Provider for SQL Server Microsoft OLE DB Simple Provider MSDataShape OLE DB Provider f
2. Wavelength 1 550 E Cancel Wavelength 2 468 Figure 30 Waveband Definition Dialog Feature Space Name PCT_10 Cancel Description Fe 10 principal components Dimension 10 Figure 31 PCT Feature Space dialog To delete an existing feature space make sure the currently selected feature space is the one to be deleted Then select Delete from the Feature Space submenu The current feature space is re moved from the database 4 2 7 5 5 Feature Space Selection A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 26 User Guide of 53 The feature space selection is comprised of two panels a a selection of the feature space type offering DI NTBI and PCT and b a drop down list box that contains all feature spaces of the cur rent type see Figure 32 Feature Space Types BE Feature Spaces DGVI Y Figure 32 Feature space settings 4 2 8 File Export SpectraProc features a powerful file export that facilitates the analysis and visualisation of the data in third party products All output files are written to the directory The output is controlled by a single dialog see Figure 33 The file export dialog is displayed by selecting File gt Export Data can be exported at any processing stage Raw Filtered removal of noisy band regions Smoothed Synthesized Derived Feature Space transformed E 00 La ad The processing for these stages depend
3. Landsat Landsat 7 Thematic Mapper Sensor Band Wavelength nm Ratio 1 435 0016 1 436 00 027 1 437 0 048 1 438 0 094 1 439 0 LG 7 1 440 Q287 1 441 0 459 1 442 0000 1 443 Us 20 1 444 0709 To import a new sensor select Database gt Import Sensor In the Import Sensor dialog select the sensor response type and the input file by clicking on Browse Then click OK and the sensor data will be imported An according message will be displayed in the message window when the sensor is loaded Import Sensor Input file A Browse Sensor Element Response Type f Gaussian Ratio Figure 41 Import Sensor dialog A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 35 User Guide of 53 4 2 14 Linking to a GIS System If a GPS unit is used to record the spatial position of the sampling sites during the sampling pro cess every site in the database contains the latitude longitude and altitude in WGS84 format The database tables can be accessed by a GIS system if ODBC connections are supported The connection is shown here on the example of ArcGIS 4 2 14 1 Setting up the Spectral DB as a Data Source Note that before the Spectral DB can be configured as a data source the MySQL ODBC driver available from the MySQL website must be installed on the system Start Data Sources ODBC from the Windows administrative tools In the New Data Source dia log Figure 42 select the MySQ
4. 6 00E 01 4 00E 01 2 00E 01 0 00E 00 a 0 00E 00 5 00E 02 1 00E 03 1 50E 03 200E 03 250E 03 3 00E 03 Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern Cabbage_tree Cabbage_tree Cabbage_tree Figure 59 Waveband filtered data export with the include filtered bands option To generate stacked plots select the option Offset by in the file export dialog and set the per centage to 100 Then plot the data again The spectra of each species are offset by the same amount see Figure 60 If only the species mean is selected the resulting plot is similar to the ones shown in diverse journal articles see Figure 61 Note that when creating graphs in these cases the Y axis scale should not displayed as it makes physically not much sense reflectances bigger than 1 Reflectance offset for clarity SS NE EN WA TrS pa a 1350 1550 Wavelength nm Figure 60 Stacked plots offset by 100 showing all spectra per species A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 47 User Guide of 53 gt ON E amp O 5 rs de NE ee ar
5. 6 321E D02 2 873 001 5 115E 001 4 098E 000 5 358E 000 6 618E 000 7 878E 000 9 138E 000 Figure 67 Score Plot after disabling an outlier To assess the impact of an outlier on the building of covariances and thus on the classification result build a library using a PCT feature space of low dimensionality e g 2 and run Discriminant Analysis Repeat library building and discriminant analysis after re enabling the outlier in Spec traProc Query You should see a significant change in classification accuracy PCA output written to file C Data MPhil Remote Sensing SpectraProc_output pca_output csv Error matrix written to file C Data MPhil Remote Sensing SpectraProc_output Error Matrix csv PCA output written to file C Data MPhil Remote Sensing SpectraProc_output pca_output csv Error matrix written to file C Data MPhil Remote Sensing SpectraProc_output Error Matrix csv A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 51 User Guide of 53 6 Change History 6 1 SpectraProc 6 1 1 Added Features SpectraProc E v1 1 13 4 2006 ted as the active study 26 4 2006 PCA Score Plot shown when performing PCA 10 5 2006 The contents of the report window can be saved to a file by select 20 10 2006 ing File gt Save Report Window Content The file is written to the default output directory and named report_window_output txt Disabled spectra are not utilized in the calculations disab
6. The name that is used as species name can be one out of five choices O Common common name is defined in database O Maori Maori name as defined in database O Latin Latin name as defined in database A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 27 User Guide of 53 O Folder name of the folder that contains the site directories of the species O Auto number incrementing numbers are assigned to the species according to their order in the database The current version of the software supports only one file level setting study l e all species of the current study are written to one single file Four checkboxes allow for the following operations O Transpose the observations are written as columns instead of rows This option can make the import of data into other programs easier O Include filtered bands this is for visualisation purposes only The regions that were re moved in the waveband filtering stage are written as empty cells i e when plotted the filtered regions will appear as gaps O Offset each species will be set off by a freely choose able percentage of 100 reflec tance This is to be used for visualisation purposes only O Interpolate this option is only available when the Synthesized stage is selected as output step The synthesized data is interpolated to ASD data using straight line seg ments This is useful for the assessment of the smoothing effect of the synthesizing operation
7. EL Search Results E pca_data MySQL Table sensor MySQL Table E sensor_element MySQL Table sensor_response_type MySQL Table E site MySQL Table E smoothing_filter MySQL Table smoothing_Filter_type MySQL Table species MySQL Table El spectrum MySQL Table statistic MySQL Table study MySQL Table El Wwaveband_filter MySQL Table E waveband_filter_range MySQL Table i OLE DE Connection selected Figure 47 SpectralDB and tables in ArcCatalog 4 2 14 3 Adding Table Data to a Map To add table data to a map select Add Data in ArcMap and choose the SpectralDB under Data base Connections Figure 48 Then select the site table as the data source Figure 49 The sampling sites can then be displayed on the map by selecting Display XY Data and using the longitude and latitude fields of the site table as X and Y coordinates Lookin QB Database Connections v a Add OLE DB Connection Add Spatial Database Connection 5 SpectralDB ode Name SpectralD Bode Show of type Datasets and Layers lyr Cancel Figure 48 Selecting the SpectralDB as data source A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc User Guide Look in 8 SpectralDB ode z a ZE band_range ZE derivative E sensor_element ES sensor_response_type EE derivative_calc_method ENE 22 feature_space 22 feature _space_type 22 mixture 22 pca_data B smoothing _filter E smoo
8. ae 10 8 6 4 2 0 2 4 6 8 10 Figure 24 Gaussian curve illustrating the FWHM measure The coefficients used for the convolution operation are given by the Gaussian function 1l wavelength band _i wavelenth_band_j 2 O l c f wavelength band _ i e y2 0 where wavelength band _i wavelength of the i th ASD band wavelength band _ j wavelength of the j th band of the sensor to be synthesized c the i th coefficient for the convolution operation The band convolution is calculated by u range Gr i u range r u E J u range C i u range where the synthesized reflectance value of the j th synthesized band C the coefficient determined by the Gaussian function for the wavelength of the i th ASD band r reflectance value of i th ASD band range defines the range of values to be used for the band convolution symmetrically to the middle ASD waveband The middle ASD waveband is the one closest to the average wavelength of the j th synthesized band The nature of the Gaussian function effectively carries out a smoothing of the data The range of values used for the convolution is set to 3 times the standard deviation range 3 0 i e 99 74 of all contributing values are used Papula 1994 This range is practically not usable for all bands because some wavelengths may have been filtered previously segmenting the spectrum In these situations the range is symmetrically reduced
9. oo A 5 A Blackfern 2 5 Cabbage_tree Q a Lemonwood 2 A E is ae m ii O 3 X 250 450 650 850 1050 1250 1450 1650 1850 2050 2250 2450 Wavelength nm Figure 61 Stacked plot showing the mean per species 5 5 Discriminant Analysis in PCT Feature Space Discriminant Analysis DA is carried out in feature spaces As an example the data will be trans formed by a principal component transformation PCT The number of components used in the transformation has a direct impact on the classification accuracy achieved by DA as will be demon strated hereafter Select PCT as the current feature space type Note that the Feature Spaces dropdown listbox states that there exist no feature spaces of this type see Figure 62 A PCT is only possible if a Principal Components Analysis has been carried out Perform PCA see 4 2 12 3 for details Feature Space Types DI NTBI te PCT Feature Spaces No feature spaces of this type y Figure 62 PCT feature spaces Open the PCA output file in Excel and plot the first 10 eigenvalues against the component number The result should be similar than the one showed in Figure 63 This graph is called screeplot The sharper the drop off in eigenvalues the better are the results that can be expected from the follow ing PCT Note that once the PCA has been performed the Feature Spaces dropdow
10. 9 38E 02 1 14E 01 1 27E 01 1 32E 01 1 27E 01 1 16E 01 1 10E 01 2 60E 02 2 74E 02 2 90E 02 3 05E 02 3 17E 02 3 26E 02 3 37 E 02 3 65E 02 4 40E 02 5 90E 02 7 66E 02 9 51E 02 1 07E 01 1 11E 01 1 07E 01 9 61E 02 9 24E 02 3 63E 02 3 96E 02 4 22E 02 4 50E 02 4 67E 02 4 60E 02 4 95E 02 5 47E 02 6 07 E 02 9 61E 02 1 31E 01 1 60E 01 1 60E 01 1 65E 01 1 71E 01 1 52E 01 1 39E 01 M 4 gt gt Mikes_example_Hyperion_synth_al lt Draw Ly AutoShapesy X C Ad Al 23 al Ll Oy 4 Ay SS Fe Ready Figure 55 Example of a SpectraProc CSV output Create an X Y plot The result should be similar to the one shown in Figure 56 Maybe surprisingly the plot shows not the expected spectra but some noise that reaches values of up to 140 To see the vegetation spectra rescale the Y axis to a maximum of 1 0 See Figure 57 The noise is caused by atmospheric absorption Thenkabail et al 2004 As first step this water band noise should be removed from the data before any further processing or analysis is carried out To remove the noise affected regions from the spectra open the waveband filter dialog see 4 2 7 1 and click on Add default ranges This adds three wavelength regions that are known to contain waterband noise 4 60E 02 Blackfern ______ Blackfern Blackfern i Blackfern Blackfern 1 20E 02 _____ Blac
11. Overview The tutorial is based on an example dataset comprised of three plant species The folder contain ing the species folders is called Vegetation_example 5 2 Examine the Folder and File Structure Open the folder Vegetation example It contains three species folders Blackfern Cabbage tree and Lemonwood Open each of these species folders and examine the contents of the site director ies contained in them Blackfern has only one sample site while Lemonwood and Cabbage tree have two Also browse inside the site directories to find the ASD binary files 5 3 Creating a new Study and Loading the Spectra Create a new study as detailed in 4 2 2 As study name type your name_example e g Mikes_ example The Species directory path is in this case the path pointing to the folder named Vegetation example Set the number of samples per species for library inclusion to 10 Once the new study is created it will be automatically selected as the current study otherwise se lect it see 4 2 5 and import the spectra see 4 2 6 5 4 Get to Know Your Data Check the settings of the processing chain O Smoothing filter none O Current Sensor Hyperion O Derivative 0 Use the Export function see 4 2 8 to export the Hyperion synthesized spectra to a CSV file Processing Stage Synthesized Data Details All Spectra Species Restriction Include all species Names Folder Transpose Ticked Format csv ER
12. S ace a na eat da ee 14 AAP SSS MC AC cs 14 422 Creating a new SUY insara p dota 15 4 2 3 Deleting an existing Study oocccoccccocncccnccccnoncnconnnonnnnnnnonnnnnnnnnnnnnnnnonnnnnnnnonnnnonnnnnnnnoncnnns 16 A A A E 16 ALO SCISCUNG IES it i 16 426 Loading OPE cast rt a a 17 4 2 7 Processing Chain Settings csi a to 17 AS A are anes os a a neue eunde a Sey aa teleost 17 Alia O MONN da idas 18 42 1 5 Sensor syutnesizin Downsaimpline da ii 20 ADSM AD A 20 AZ CAUSAS CENSORS aii 20 SS E SS hrs eee sistas Seatac lia att a Mine toed ates te 22 AD VA DEL Valtivo CAC UA OM ys ah ice teen Gs iaa 22 AQT Feature Space rans lOrm dln ssc sees Gece ca tea lia act seach cases tesa 23 a NS ene eR A URE oem eeTe 23 AA A ae Ne On eC A 23 A is PE A 24 4 2 7 5 4 Creation Modification and Deletion of Feature Space Definitions ccccccccnnncnnnnnnnnnnnnos 24 A2 Too A 25 A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 4 User Guide of 53 OL MN OOF ae hs rare hse ener O ete ces ec Se ee 26 4 2 9 Saving the Contents of the Report WiNdoOW occcocccoccccocncocnnncnconcncncncnncnnncnnnnnonanonononoos 28 4210 Specta MXUrES a Og Sate wae oe iaa 28 42 TOT Em miemBer Des NA ind 28 AD MOD Abundance UU das de nates aes 29 Az 11 Library Bullas 29 42I A y 29 A A le eee re ca ee eee 29 42122 Disctimmant AMALY S184 56s pecc les ces cette Real is alee a a alee cule 30 A 212 5 Principal Component M
13. Sensor Y Indiv Classify none Y Derivative order gt Current Sensor Hyperion Derivative N Derivative calculation method JN Calculation method Report window E lo Derivative calculation detail settings button Feature Space Types DE Feature space NTBI Feature Spaces Feature space DGVI Y Classifier Classifier APP Mahalanobis v discriminant function Ready Figure 6 Main window elements A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 15 User Guide of 53 4 2 2 Creating a new Study To create a new study select Database gt Create New Study Figure 7 This brings up the new study dialog Figure 8 eine Chain Settings Statistics Create New Study h Delete Current Study Study Report Import Spectra into current Study Import Sensor Figure 7 Create New Study menu entry Enter a study name of 45 character maximum and not containing special characters that can not be part of any Windows file name like 1 9 lt gt The study description is optional and can contain any string up to 200 characters long The species directory path is a Windows pathname pointing to the directory that contains all spe cies folders of this study To set the path either type it in manually or select the Browse button that brings up a directory tree Figure 9 and select the appropriate directory The number of samples per species for library inclusion can be set
14. Soil Research 46 623 635 Landgrebe D 1997 On Information Extraction Principles for Hyperspectral Data Purdue Univer sity West Lafayette IN 34 pp Papula L 1994 Mathematik fuer Ingenieure und Naturwissenschaftler Vol Band 3 Viewegs Richards J A 1993 Remote Sensing Digital Image Analysis 2nd edn Springer Verlag Berlin Savitzky A Golay M J E 1964 Smoothing and Differentiation of Data by Simplified Least Squares Procedures Analytical Chemistry 36 8 1627 1639 Shaw G Manolakis D 2002 Signal Processing for Hyperspectral Image Exploitation IEEE Sig nal Processing Magazine 19 1 12 16 Thenkabail P S Enclona E A Ashton M S 2004 Accuracy assessment of hyperspectral waveband performance for vegetation analysis applications Remote Sensing of Environment 91 354 376 WEKA 2005 Version 3 4 5 University of Waikato Vane G Goetz A F H 1988 Terrestrial Imaging Spectroscopy Remote Sensing of Envi ronment 24 1 29 A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008
15. as defined in the configuration file click on Add default ranges see 2 2 on how to configure the default filter ranges 4 2 7 2 Smoothing Smoothing applies a smoothing function to the spectra The default smoothing filter type is None meaning no smoothing is carried out The smoothing type is selected using the drop down list box in the main window Figure 20 Two different Savitzky Golay implementations are offered in this A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 19 User Guide of 53 list Moving Window MW and Fast Fourier Transformation FFT The output is exactly the same however due to internal overhead the MW method is currently the faster of the two Smoothing Filter none e Savitzky Golay MW aveo olay Gola FFT Figure 20 Smoothing filter type drop down list box The processing details of the smoothing filter are set by clicking on the Edit button below the list box This brings up a dialog where the polynomial order and the filter window size can be changed Figure 21 The filter size is automatically incremented resp decremented in steps of two to keep the filter size and uneven number i e the number of points on the left and right of the point to be smoothed are equal The polynomial order sets the order of the curve that is used in the least squares approximation Note that the Savitzky Golay coefficients for quadratic and cubic functions are the same and t
16. named report_window_ output txt see Figure 34 Library Database Chain Settings S Load ENVI Z Profile Open ctrl 0 Save Report Window Content Ctrl S Export gt Exit Figure 34 Saving the report window content 4 2 10 Spectral Mixtures Spectral mixtures occur when more than one endmember is present in the field of view If the end members are known the mixtures can be unmixed to give estimates of the abundance of each endmember in the mixture For the process of unmixing refer to 4 2 12 4 The unmixing process needs to have a set of endmembers and a set of mixtures to be unmixed using the endmember information For this purpose species can be designated as endmembers If the spectral mixtures are the result of a controlled mixing experiment the abundances of the endmembers are usually know These known endmember fractions can be entered into the data base for each mixture thus allowing the automatic calculation of the error involved in the estimation by the unmixing procedure 4 2 10 1 Endmember Designation To display the endmember designation dialog choose Spectral Mixing gt Endmember Selection Figure 35 a ia Help Test Endmember Selection Abundance Settings Unmix Figure 35 Endmember Selection menu entry Initially all species will be listed in the Classes list while the Endmembers list is empty To desig nate a species as an endmember select the class by clicking on it then c
17. to avoid filtered regions A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 22 User Guide of 53 4 2 7 3 3 Supplied Sensors The sensors currently supplied with the software are Names Type Description Sensor as flown on EO 1 Effects a 1 1 copy of ASD data i e no data reduction Opt_Hyperion Gaussian The Hyperion sensor according to the blueprint i e all sen sor elements are operating Landsat To change the current sensor select a sensor from the sensor drop down list box Figure 25 Current Sensor y TEU Figure 25 Selection of current sensor It may be advisable to apply the downsampling only to smoothed data in order to avoid aliasing The combination of smoothing and downsampling is called decimation Fliege 1994 4 2 7 4 Derivative Calculation The derivative order is set to zero by default i e no derivative is calculated To change the order use the up and down arrows next to the box showing the derivative order Figure 26 If the order is changed to a non zero value the calculation method can be selected Iterative calculation is based on the gradient of the linear curve segment between two wavebands _ P 6 p b Bear 6 1 A b where p b reflectance of band i A 5 wavelength of band i p b b first derivative of linear curve segment between reflectances of band i and band 1 The n th derivative is thus calculated by applying
18. 0 Figure 63 Scree plot of the eigenvalues of the first 10 components Table 6 Error Matrix for DA on PCT_5 feature space Blackfern Cabbage_tree Lemonwood _ Row Total ee Blackfern 12 0 0 12 1 00E 02 Cabbage_tree 6 20 0 26 7 69E 01 Lemonwood 0 0 27 27 1 00E 02 Column Total 18 20 27 65 Producer Accuracy 6 67E 01 1 00E 02 1 00E 02 9 08E 01 5 6 Disabling Outliers By combining SpectraProc and SpectraProc Query outliers can be identified and disabled In the example dataset you might have spotted one cabbage tree spectrum that looks different low reflection in the NIR than all others If PCA is run on this data set the outlier can also be spotted see Figure 64 PCA Score Plot of study example 8 918E 001 4 176E 001 5 870 002 4 784E 000 6 247E 000 7 711E 000 9 175E 000 Figure 64 Score Plot showing an outlier A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 49 User Guide of 53 Now start SpectraProc Query select the example campaign in the Campaign Conditions select Cabbage Tree as Species Condition select Spectrum as report level and click Exec Query see Figure 65 spectra_proc_query SpectraProc Query A TCL TK Interface Campaign Report Level example X Campaign Species Use wildcards for multiple chars and _ for single chars C Site Spectrum oa SQL Query autobuilt Folder name Cabbage_tree y SELECT COU
19. 2008 SpectraProc Page 31 User Guide of 53 Discriminant Analysis Select name type Names Common Maori Latin Folder Figure 39 Discriminant Analysis dialog A message stating the file name of the error matrix and the overall accuracy is reported in the mes sage window similar to the example shown below Discriminant Analysis Error matrix written to file C Data MPhil Remote Sensing SpectraProc outputAError Matrix csv Overall Accuracy 78 46154 The error matrix written to a file contains the errors of omission and commission the total accuracy the producer and user accuracy and the minimum maximum and mean for both producer and user accuracy Table 2 Error matrix of DA using a 3 dimensional NTBI feature space Blackfern Cabbage_tree Lemonwood Row Total ES Blackfern 11 00 0 00 0 00 11 00 100 00 Cabbage_tree 7 00 19 00 6 00 32 00 59 38 Lemonwood 0 00 1 00 21 00 22 00 95 45 Column Total 18 00 20 00 27 00 65 00 Producer Accuracy 61 11 95 00 77 78 78 46 Prod Acc Min 61 11 Prod Acc Max 95 00 Prod Acc Mean 77 96 User Acc Min 59 38 User Acc Max 100 00 User Acc Mean 84 94 To run the DA with an independent data set choose Statistics gt Discr Analysis using indep set A dialog is displayed to select the study that contains the independent set Figure 40 Note that in order to work correctly the folder names of corresponding species in the training and in the independent study mu
20. AA 32 E o Ne a en Cree eer One nee oR a 32 4 2139 Adding NEW SENSOMS il 33 4 2 14 Linking to a GIS System it Maecenas RR 35 4 2 14 1 Setting up the Spectral DB as a Data Source occccccccnoncnnnononononnnnnonnnononnnnnnnnnnnnnnnnnnnn non nnnnnnnnnns 35 4 2 14 2 Establishing a Database Connection in ArcCatalog cccccccnnnnnnncnnnnnnnnnnnnnononononononononanannns 35 42 143 Adding Table Data to a Md Gel estes 37 4 3 SpectraProc Query Interface A ad oi 39 ASA DroduUCION rt dci 39 43 2 Database Connection siii ones eee sed id sleet 39 43 9 sUSEMIMGE MACE sirieni a a a a N a e a ten 39 434 Report WINdJOWS a a a a ieee 40 AOA Campa b m Cee enee a a a eet eee ss 40 ASAD PECES O de ds dd as 41 A A o ae 41 AI SPECK REPO lo aca 42 S o A sieenes 43 O O 43 5 2 Examine the Folder and File Structure cooocccocccccnccocnconncconoconoconnnnnnnnnnnonanonononannonanenaninons 43 5 3 Creating a new Study and Loading the Spectra oococcccoccconcconcconccnccononcnnnnnnononononnnconnnonnnos 43 Ot AGETTOAKMOW CU DAA e Siac aa a dilo 43 5 5 Discriminant Analysis in PCT Feature Space cooccccncccccnccccccccnoconoconononnonnnonononnnnonnnnnnnnonanenaninons 47 50 Disabling Quiles a bode el lean aed ee ee 48 O Change HIStory ic asa pirita iaa 51 OT SSDSCUAIP OC iad TNT 51 OLE O t ha acacia E A iene 51 OLA FREI DUO So es 51 Oko KAOWN BUGS iiie E E a 52 02 Specia roc Dalabase a 52 621 a PP E mete an cee 52 T R
21. AAT a ta a AEA This will create a file in the SpectraProc output directory The output file name is shown in the mes sage window Open this file by double clicking which should load it directly into Excel The columns displayed should be similar to the example shown in Figure 55 Column A contains the average wavelengths of the Hyperion bands The following columns contain the spectral data for each spec trum The column headers are the species folder names A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 Page 44 of 53 SpectraProc User Guide Seles A X a9 EE 44049 100 aj 2 ES Microsoft Excel Mikes_example_Hyperion_synth_all_species csv Fed File Edit View Insert Format Tools Data 5 PLUS Window Help 3 MM Arial 10 B ZJU fe species Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern 3 54E 02 3 70E 02 3 67E 02 4 O3E 02 4 16E 02 4 26E 02 4 39E 02 4 72E 02 5 64E 02 SDE 02 9 94E 02 1 19E 01 1 33E 01 1 38 01 1 32E 01 1 21E 01 1 14E 01 3 10E 02 3 24E 02 3 42E 02 3 61E 02 3 74E 02 3 66E 02 3 96E 02 4 29E 02 5 16E 02 6 66E 02 9 06E 02 1 10E 01 1 23E 01 1 29E 01 1 24E 01 1 14E 01 1 08E 01 2 04E 02 3 00E 02 3 16E 02 3 36E 02 3 50E 02 3 62E 02 3 74E 02 4 11E 02 5 13E 02 7 15E 02 9 74E 02 1 19E 01 1 33E 01 1 39E 01 1 33E 01 1 22E 01 1 14E 01 2 69E 02 2 62E 02 3 00E 02 3 19E 02 3 33E 02 3 45E 02 3 57E 02 3 95E 02 4 96E 02 6 92E 02
22. EFENCOS paid 53 A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 5 User Guide of 53 1 Introduction Field spectroradiometry has become increasingly popular in the last few years The technology has advantages over conventional techniques allowing the non destructive sampling of objects and possibly enabling the user to gain critical information more quickly and cheaply As a result many scientists are now actively researching applications of hyperspectral sensing The operation of the instruments tends to be relatively easy and data are collected quickly However the interpretation of these data is not so simple The main issue when dealing with hyperspectral data is their dimen sionality which is the result of sampling a wide spectral range in very narrow bands This is in itself a problem because the influence of noise on narrow channels is much higher than on traditional broadband channels Hyperspectral data are more complex than previous multispectral data and different approaches for data handling and information extraction are needed Landgrebe 1997 Vane and Goetz 1988 Hyperspectral data are essentially multivariate data consisting of hundreds or even thousands of variables It has been shown that more bands do not automatically imply better results Although the separability of classes does increase with growing dimensionality the classification accuracy does not follow this trend endlessly but will decreas
23. HIO spectral database However SPECCHIO is still lacking the processing features as offered by SpectraProc at this point of time For more information see www specchio ch A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 6 User Guide of 53 2 Installation and Configuration 2 1 Database 2 1 1 Installing MySQL SpectraProc runs on versions 4 and 5 of MySQL database SpectraProc Query only runs on ver sion 5 O Download the installation wizard ZIP file for Windows from www mysal com mysql 5 0 26 win32 zip O Install the above ZIP file by running it O Use standard configuration O Inthe configuration section select o Install as windows service o Root password root or any other password but make sure you can remember it 2 1 2 Installing MySQL Administrator and Query Browser O Download the windows install MSI file from www mysql com mysql gui tools 5 0 r4 win32 msi O Install both applications by running the above MSI file 2 1 3 Setting up the Spectral Database Schema Tables and Users O Run MySQL Administrator O Go to Restore and load the supplied Spectral DB XXXXXXX SQL file This will create all tables and populate them O Goto the User Administration tab and create a new user User name and password are both SpectraProc Edit the spectral_db schema privileges by adding SELECT INSERT UPDATE AND DELETE to the assigned privileges Assign Resources max_questions 0 max_updates 0 max_con
24. L ODBC Driver and click on Finish Create New Data Source Select a driver for which you want to set up a data source Microsoft ODBC for Oracle Microsoft Paradox Driver db Microsoft Paradox Treiber db Microsoft Text Driver txt cs Microsoft Text Treiber txt cs Microsoft Visual FoxPro Driver Microsoft Visual FoxPro T reiber MySQL ODBC 3 51 Driver SOL Server lt Mort fa fe fe EM core Figure 42 New Data Source dialog This brings up the ODBC configuration dialog Figure 43 Type in a name for the Data Source Name Set the Server to the address of the database server Enter the User name and Password SpectraProc Select the database schema containing the spectral data from the Database drop down list N Connector ODBC 3 51 12 Configure Data Source Name Connector ODBC RR Login Connect Options Advanced Connector ODBC aie Configuration Data Source Name Spectral DB This dialog is used to edit a Data Source Name DSN Description Server it022005 massey ac nz User SpectraProc Password Database spectral_db v Figure 43 MySQL ODBC Configuration dialog 4 2 14 2 Establishing a Database Connection in ArcCatalog Start ArcCatalog and select Add OLE DB Connection Figure 44 A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 36 User Guide of 53 Y ArcCatalog Arcinfo Database Connections
25. NT distinct spectrum spectrum_id FROM study pecies spectrum WHERE name example AND folder_name Cabbage_tree AND study study id species study 1d AND st mita AF aaa al AND species species_id spect From TT rum species_id t ja el eoe e a a a a _ o Result Set Information Altitude m lt gt Number of resulting rows by curent query 20 Exec Query Reset Figure 65 Conditions set to select Cabbage Tree spectra from the example campaign Collection Dates In the spectrum report See Figure 66 scroll down till you see the wrong looking cabbage tree spectrum spectrum number 9 of site 1 you can deduce the site number from the pathname Tick the checkbox in order to disable the spectrum Now rerun the PCA calculation in SpectraProc and the outlier will vanish from the Score plot see Figure 67 Spectrum Query Results 1 Spectrum Query Results 20 rows loaded in 1 1439 seconds Cabbage_tree C Documents and Settings 4drni nistrator Desktop Vegetation_ex ample Cabbage_tree sitel cabb age 009 900 0 1450 0 20000 2550 0 Wavelength nm Cabbage_tree C Documents and Settings 4dri nistrator Desktop egetation_ex sranle CO ahhana fresh site Tesh N ds Figure 66 Spectrum Report showing a wrong looking Cabbage Tree spectrum A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 50 User Guide of 53 PCA Score Plot of study example 3 851E 001 1 609E 001
26. They greyed out fields to the right of the date fields automatically show the resulting dates when one of the date fields is filled The years are automatically restricted to the maximal or minimal year of all records in the database Spatial restrictions can be added by specifying a threshold for the altitude in the Minimal Maximal Altitude Fields The report level is chosen by clicking on the option buttons in the Report Level Selection The resulting SQL query is displayed in the Auto Built SQL Query Text Field The number of records rows that will be selected by the current query is displayed in the Result Set Counter field Any change in conditions or report level will automatically update the auto built query and the num ber of resulting rows A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc User Guide Page 40 of 53 Finally there are two buttons at the bottom right side of the GUI Exec Query will run the current query and display a report in a new window Reset will return all conditions to their starting values and reset the level to Campaign Campaign Conditions Campaign Name Campaign Name Species Name Report Level Auto built SQL Selection Wildcard String Wildcard String Selection Query Text Field Species Name x Selection f spuctra_proc_query DER NS SpectxaProc Que CL TKNoterfa
27. User Guide Version 1 2b Date 13 10 2008 Status Valid Author A Hueni File UserGuide_V1 2b doc Pages 53 Classification Distribution SpectraProc SpectraProc Page 2 User Guide of 53 History Version Date Author Remak 03 04 2006 First draft 06 04 2006 Modified MySQL installation 16 06 2006 Modified Tutorial for new example set 1 1 20 10 2006 A Hueni Added description of new SpectraProc Fea tures Added description of new SpectraProc Query interface Added new section in the Tutorial about disabl ing of outliers Added change history of added features fixed bugs and known bugs 16 11 2006 A Hueni Added another table change statement for the spectrum table see Upgrading to SpectralDB V1 1 17 12 2006 A Hueni Added description how to change the database connection string for SpectraProc Query 2a 15 02 2008 A Hueni Upgraded the supplied spectral_ db schema to V1 1 and therefore adapted the installation in structions in this user guide Removed the upgrade database section 13 10 2008 Updated the application bundle TCL relevant A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 3 User Guide of 53 Table of Contents INtToOdUciION niente 5 2 Installation and Configuration ooccoccconncocccinnncoccnccnnenancnnnnnannnnnnonarennnrnnnnnnanenas 6 2i WANDA ri ees 6 2 Instala VIV SOE eos daa 6 2 1 2 Installing MySQL Administrator and Query Browser
28. User Guide of 53 4 Operation 4 1 Overview 4 1 1 Dataflow A typical dataflow is illustrated in Figure 3 An ASD FieldspecPro spectroradiometer is used to cap ture the radiance of field objects A GPS connected to the field laptop records the spatial position of the field object Reflectance and metadata are automatically saved on the field laptop in a binary file for every reading taken These binary files are transferred to a laboratory computer where they are read by SpectraProc and stored in the relevant tables in the spectral database GPS pe Spatial data E Reflectance A Binary file gt gt gt gt az JIAN Reflectance amp metadata gt Spectral database 3k Field ASD Field laptop Lab computer object Spectroradiometer Figure 3 Dataflow and involved hardware 4 1 2 File System Interfaces SpectraProc provides input and output interfaces to the file system see Figure 4 Input file formats are ASD binary file as produced by the ASD FieldSpecPro Spectroradiometer ENVI Z Profiles that are signatures extracted from hyperspectral imagery in ENVI and sensor specifications in a propri etary tabulator separated format ASD files can be imported into the database as part of a study or loaded into memory for classification against a study dataset ENVI Z Profiles can be loaded for classification only Sensor specification files are a way of defining new sensors in the database Output can be wr
29. alue Proportion Cumulative 1 2 211 0 944 0 944 2 0 097 0 042 0 986 3 0 019 0 008 0 994 4 0 007 0 003 0 997 5 0 005 0 002 0 999 6 0 001 0 001 0 999 7 0 000 0 000 0 999 8 0 000 0 000 1 000 9 0 000 0 000 1 000 10 0 000 0 000 1 000 4 2 12 4 Unmixing The unmixing procedure implemented is experimental at this stage and works on Landsat data only Before starting the unmixing make sure that the current sensor is Landsat7 the study has the mixtures and endmembers defined and the abundances are entered for each mixture The model used is unconstrained Keshava and Mustard 2002 A 1 i STS S x A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 33 User Guide of 53 where x spectrum vector to be unmixed L x 1 S endmember matrix L x M consisting of M endmembers with the columns being the endmem ber spectra vectors y the unconstrained least squares solution for the abundances of the endmembers in the spec trum vector x To start the unmixing select Spectral Mixing gt Unmix For each mixture the unmixing results are displayed in the message window first stating the calculated abundances for each endmember then the abundances stored in the database and finally the absolute errors for each endmember abundance see example of such an output below Spectral Unmixing 0 69 OV 360P 0 35 360V_0P simulated mixture abundances from database 0 67 OV_360P Dia SO0V OP absolute erro
30. and post filtering of water noise bands The waveband filter regions are freely configurable for each study To modify the current filter set tings select Chain Settings gt Waveband Filter Setup Figure 16 A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 18 User Guide of 53 gi Statistics Spi Waveband Filter Setup Feature Space Figure 16 Waveband Filter Setup menu entry Waveband Filter Setup Waveband filter nm Modify Delete Add default ranges Figure 17 Waveband Filter Setup dialog no regions defined The Waveband Filter Setup dialog lists the waveband filter ranges in the listbox on the left side Figure 17 To add a new filter region click New In the pop up window enter the lower and upper wavelengths in nanometres of the region Figure 18 After clicking on OK in this dialog the newly created filter range is shown in the Waveband Filter Setup dialog Figure 19 Filter band definition Lower wavelength 350 Cancel Upper wavelength ES Figure 18 Filter band definition dialog Waveband Filter Setup Waveband filter nm 350 470 nm Modify i Delete Add default ranges Figure 19 A new waveband filter range added to the list of filter ranges To modify an existing range select the range to be modified in the listbox and click Modify To delete an existing range select the range and click Delete To add the default ranges
31. anged by editing the file spectra_proc_query tcl The localhost string must be replaced with the net work name of the database server this is similar to running SpectraProc over a network set db_handle mysqlconnect host localhost db spectral_db user Spec traProc password SpectraProc 4 3 3 User Interface This section describes the user interface of SpectraProc Query Please refer to Figure 50 for an example of the GUI As indicated above the resulting rows in reports can be restricted by setting conditions These conditions are situated at the left side of the GUI The campaign conditions refer to conditions that restrict the campaigns studies The campaigns can be restricted by either choosing a specific campaign name in the Campaign Name Selection box or by entering a string in the Campaign Name Wildcard String box The latter also accepts wildcards stands for any string and _ stands for a single character The species conditions restrict the species by their folder names A name can be selected in the Species Name Selection box or be entered as a string with wildcards in the Species Name Wild card String box A restriction of the campaigns has a direct impact on the names available in the list of species names only species contained in the resulting campaigns are available in the list The result set can be temporally restricted by entering dates in the Collection Date From and To Fields The dates have the format DD MM YYYY
32. ative_order 1 will result in the removal of n derivative_order number of points Derivative Filter Details Filter size Polynomial order Figure 27 Savitzky Golay settings for derivative calculation Note that too big filter sizes remove relatively lot of data because the derivative calculation takes place after the data reduction step sensor synthesizing downsampling E g a filter size of 5 ap plied to data downsampled by factor ten will remove 4 data points i e 40nm per segment 4 2 7 5 Feature Space Transformation Three types of feature spaces are implemented O Derivative Indices Dl O Normalized Two Band Indices NTBI O Principal Component Transformation PCT 4 2 7 5 1 DI DGVI DGVIs Derivative Greenness Vegetation Indices are an example of a DI These indices are trying to describe the shape of the reflectance curve The DGVI calculation is based on the equations used by Thenkabail et al Thenkabail et al 2004 and Elvidge and Chen Elvidge and Chen 1995 kd AD where 0 b b first derivative of reflectance curve between b and b m n start and end band number of DGVI area b centre wavelength of band i band number Ab step width Dis Di 4 2 7 5 2 NTBI Normalized two band indices are calculated by A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 24 User Guide of 53 _ p b p p b p b 4 2 7 5 3 PCT Principal components transformati
33. ce scipaign Report level DS le Zampaign Species A MS BeA a and _ for singlt chars Y Site C Spectrum rSpecies Species Conditions Collection Dates Conditions Spatial Attributes Conditions Collection Date From and To Fields gt Folder name All Collection Dates From so FAN Spatial AYibutes ae Altitude rn y lt gt mn oo SOLQ uey autobuilt SELECP COUNT distinct study study_ id FROM study Result Set Information Number of resulting rows by current query Ze ec Query get 7 Minimal Altitude Field Maximal Altitude Field Exec Query Button Reset Button Result Set Counter Figure 50 SpectraProc Query GUI 4 3 4 Report Windows The number of report windows is not restricted by the software although a limit might exist due to memory or operating system restrictions All reports start with a title that contains the level of the report plus a subtitle indicating the time taken for the report building This is followed by the main table containing the data 4 3 4 1 Campaign Report An example of a campaign report is shown in Figure 51 The reported attributes are campaign name description and file system path A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 41 User Guide of 53 Campaign Query Results 1 Campaign Query Resul
34. data collections The time and effort that is spent in collecting spectral data combined with the characteristically large number of files makes it clear that spectral data should be well organised Otherwise valu able data can be lost or loses its value because of missing metadata Considering the above it seems logical to employ a database to store spectral data in a suitable form A further character istic of hyperspectral data is the data redundancy It has been shown that neighbouring wavebands have a high degree of correlation Thenkabail et al 2004 This redundancy is created by over sampling i e the spectral signal is sampled at small enough steps to describe very narrow features that could be discriminating Shaw and Manolakis 2002 The redundancy and general noisiness of the data usually mean that certain pre processing must be carried out before any useful analysis can be performed SpectraProc and SpectraProc Query bundled with the associated spectral database is a solution for the efficient storage and pre processing of field spectroradiometer data The system has been successfully used in studies concerned with New Zealand native vegetation soil properties and pastures Kusumo et al 2008 SpectraProc has also lately been used in a study of rapid avalanche mapping at the Remote Sens ing Laboratories Zurich Switzerland For the storage of spectral data and associated metadata you may wish to consider using the SPECC
35. e New Study Delete Current Study Study Report Import Sensor Import Spectra into a Study PPP Figure 14 Import Spectra menu entry 4 2 7 Processing Chain Settings 4 2 7 1 Waveband Filtering Waveband filtering is the process of removing unwanted regions of the spectrum All subsequent processing operations will then ignore these regions A typical example is the removal of water bands These water band regions are usually found around 1350 1440 nm 1790 1980 nm and 2360 2500 nm Figure 15 If contact probes are used the noise can be minimal because the atmosphere is effectively non existent 1 00E 00 9 00E 01 Raw Reflectance Curve of Pittosporum eugenioides 8 00E 01 an N 7 00E 01 x 6 00E 01 5 00E 01 Reflectance 4 00E 01 Reflectance 3 00E 01 LY ce 2 00E 01 1 00E 01 A Z AS 0 00E 00 300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500 Wavelength nm Filtered Reflectance Curve of Pittosporum eugenioides 1 00E 00 9 00E 01 8 00E 01 7 00E 01 6 00E 01 5 00E 01 4 00E 01 3 00E 01 ri a 2 00E 01 po rs om 1 00E 01 AS 0 00E 00 300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500 Wavelength nm Figure 15 An example of pre
36. e at a certain point This is called the Hughes Phenomenon and is caused by the ever increasing number of samples needed to build sound stat istics if the dimensionality grows Landgrebe 1997 In practice this means that more samples must be collected to ensure successful statistical analyses It is necessary therefore to collect a large number of spectral data files each containing a hyperspectral spectrum The sheer number of files and variables can become overwhelming Interestingly very few studies concerned with hyperspectral data have ever mentioned how the data had been organised and stored A further issue that is rarely addressed is the reusability of the data Reference data is usually compiled in so called spectral libraries The majority of the publicly available spectral libraries are distributed as physical files This has drawbacks such as low flexibility and low query performance Bojinski et al 2003 Another drawback of most libraries is their restriction in the number of spec tra per class In many cases only one reference spectrum is supplied This reduces any statistical analysis to first order statistics The use of average values may be useful in some circumstances however Landgrebe 1997 noted that the reduction of data to mean values results in a loss of information Second order statistics contain vital information about the distribution of data in spec tral or feature space and should therefore be included in spectral
37. e g by plotting a noise spectrum smoothed minus interpolated synthesized data O Sort species numerically Sorts the species by interpreting the species names as numbers Species restriction Name type selection selection File Export Processing Stage Species Restrictiok Names C Raw Include all species Common J File level C Filtered C Include only library relevant species Maori selection Processing stage Smoothed C Only endmembers f Latin for file export Synthesized aa Folder Denved C Auto number Transpose Observations as columns ES Feature Space _ i S Include filtered bands Data Details r aN Offset by N interpolate Synth stage onl Data averaging Sg ere y dk Transpose options Sort species GN gt observations Mean per species W i Include the filtered Format b and regions A pibe Offset each species by agiven percentage Interpolate output by File format linear segments selection Sort the species names numerically Figure 33 File Export dialog A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 28 User Guide of 53 4 2 9 Saving the Contents of the Report Window The contents of the report window can be saved to a file by selecting File gt Save Report Window Content The file is written to the default output directory and
38. ect comparison of airborne spaceborne sensor and ground data 3 Implicit smoothing of the data 4 Prediction and assessment of the usefulness of a certain sensor Two classes of sensors are supported Ratio and Gaussian 4 2 7 3 1 4 5 3 1 Ratio Sensors The sensor element function of these sensors is modelled by a number of known coefficients thus the synthesizing operation is simply a convolution of a defined wavelength region using these co efficients An example of such ratios is shown for Landsat7 TM band 1 Figure 23 Ratios for Landsat Band 1 Figure 23 Ratios for Landsat7 TM band 1 The convolution is calculated by uw_Jj CF E ri a C i iw_j where r the synthesized reflectance value of the j th synthesized band C the coefficient for wavelength i r reflectance value of i th ASD band Iw __j lower wavelength of the j th band uw _ J upper wavelength of the j th band 4 2 7 3 2 Gaussian Sensors A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 21 User Guide of 53 The sensor element response function of these sensors is best approximated by a Gaussian func tion The sensor elements are technically defined by the middle wavelength and the full width at half the maximum FWHM see Figure 24 Gaussian function for mu 0 and sigma 2 0 18 4 0 16 J 0 14 a FWHM 0 12 J 0 1 J 0 08 J 0 06 J 0 04 4 0 02 J
39. ed for free on the web on http www activestate com Products ActiveTcl Choose C TCL as installation directory 2 3 2 Installing Mysqltcl Package Mysaltcl is a package that handles the communication between a TCL client and a MySQL data base The package can be downloaded on http www xdobry de mysaltcl downloads select the Windows binary version ZIP The ZIP file contains a folder called mysqltcl 3 02 which has been included This folder needs to be copied into the TCL library If TCL was installed on the C drive C TCL then the library folder is C Tcl lib 2 3 3 Plotchart Package The Plotchart package is usually part of the general TCL TK distribution the package is contained in tcl lib tcl8 5 tklib0 4 or similar In some distributions it might be missing In the later case copy the plotchart directory contained in the SpectraProc distribution into tcl lib 2 3 4 Installing SpectraProc Query Interface The source files of SpectraProc Query are supplied in a folder The folder can be copied wherever seems convenient e g in C Program Files 2 3 5 Changing the Database Connection By default the SpectraProc Query connects to the local host If the SpectraProc database is in stalled on a different machine the connection string must be edited manually Open the file spectra_proc_query tcl in some editor Then replace the string localhost with the name or IP address of the database server set db handle mysql
40. ent name during the restore operation change the name of the database O Default filter settings these are the waveband filter ranges that are used as default val ues in the waveband filter setup see 4 2 7 1 More filter ranges can be added to the configuration file by adding a new line starting with filter_br for each range O Output drive and directory specify the output drive and the output directory All file out put is written to this directory This must be a valid i e existing pathname Configuration settings for spectraProc database settings server localhost user SpectraProc password SpectraProc database spectral db default filter settings filter br 1350 1440 Leber br 90 1960 fi TLer DE 2360525 00 specification of file output drive and directory OUTPUT drive C output dir Data MPhil Remote SensinglSpectraProc output Hint access to SpectraProc is made easier by placing a shortcut to the executable on the desktop A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 8 User Guide of 53 2 3 SpectraProc Query Interface The SpectraProc Query Interface is written in TCL TK Access to the database is provided by a package called mysaltcl TCL TK and the package must be installed on the same machine as the SpectraProc Query Interface SpectraProc Query only runs on MySQL version 5 and SpectraProc DB V1 1 2 3 1 Installing TCL TK TCL TK is open source software and can be download
41. f the specimens is described by several measurements per specimen The spatial extent where a specimen is sampled is termed a sample site thus a species contains a number of sample sites The sites are numbered in the order of sampling At each site several readings are taken to capture the variation exhibited by the specimen in question A site therefore contains a number of spectra This leads to a hierarchical directory structure Figure 1 Spectrum 1 Spectrum 1 Spectrum 1 Spectrum 2 Spectrum 2 Spectrum 2 Spectrum n Spectrum n Spectrum n Figure 1 Hierarchical directory structure Although the term species is used it essentially represents the different classes found in a study These classes can either be assigned due to already existing classification systems for e g plants or minerals In other cases a hypothesis might exist that a group of objects can be separated into classes If so the setup of the experiment should mirror this hypothesis If no such assumption ex ists all objects can be put into the same class i e species and the identification of classes could then be carried out by e g cluster analysis 3 3 Directory Structure and Spectral Files The hierarchical structure is used for the directory structure that holds the spectral files Ideally this directory structure is setup when designing the experiment Figure 2 shows an example of a directory structure The main directory Vegetation example holds all specie
42. fern ______ Blackfern Blackfern Blackfern Blackfern Blackfern Blackfern 8 00E 01 6 00E 01 Blackfern Blackfern Blackfern 4 00E 01 2 00E 01 Blackfern Blackfern Blackfern 0 00E 00 Blackfern Blackfern Blackfern Blackfern Blackfern Cabbage_tree 0 00E 00 Cabbage tree 2 50E 03 Cabbage _tree Figure 58 Spectra after setting up the waveband filter regions To plot the filtered regions as gaps select the option Include filtered bands in the file export dia log If the data is plotted again the result will be similar to the one shown in Figure 59 Two other points are noteworthy a some reflectance values are higher than one and b one Cab bage tree spectrum seems to be an outlier The reflectances higher than one could be the effect of changing illumination conditions during the sampling or a result of the BRDF The outlier problem can currently not be solved automatically Two options exist a remove the concerned spectrum from the file system and then delete recreate and reload the study or b re A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc User Guide Page 46 of 53 move the concerned spectrum from the database using SQL commands Future versions of the software may feature automatic outlier detection and elimination 1 20E 00 1 00E 00 8 00E 01
43. he graphics output is relatively computing intensive One should be careful not to start a report with too many several hundred resulting rows as the report can run for a while e g 45 seconds for 1100 spectra Note that the spectral resolution of the graphic is reduced decimated by factor 10 in order to speed up plotting time l e the data points are spaced at 10 nm intervals This may result in some noise being less accentuated than in the raw data The disabled checkbox offers some interaction with the database If checked it will set the field disabled in the spectrum table to TRUE Likewise unchecking sets the field to FALSE Setting this field has a direct impact on the processing by SpectraProc Disabled i e disable TRUE spectra will not be included in any processing It is therefore a chance to remove outliers from the data while still retaining all data in the database An example illustrating this functionality is included in the tutorial see 5 6 Spectrum Query Results 6 Spectrum Query Results 18 rows loaded in 1 1434 seconds Refl Tangle_Fern C Data MPhil Remote Sensing Species_sites T angle_Fern site1 fern 000 O 900 0 14500 2000 0 2550 0 Wavelength nm Refl Tangle_Fern a C Data MPhil Remote Sensing Canran aikan Tanala Cantata e lt Figure 54 Spectrum Report A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 43 User Guide of 53 5 Tutorial 5 1
44. he same applies to orders 4 and 5 Savitzky and Golay 1964 Smoothing Filter Details Figure 21 Smoothing Filter Details dialog The result is automatically filtered to remove artefacts that appear at the start and end of every valid waveband segment Figure 22 The new valid segment sizes are calculated by MU comes Au pos _ filter _ size Al aome neg _ filter _ size where Al Au lower and upper segment wavelengths Thus every segment looses information of filter_size 1 Smoothed Reflectance Curve of Pittosporum eugenioides showing smoothing artefacts Smoothed Reflectance Curve of Pittosporum eugenioides after the removal of smoothing artefacts Figure 22 A smoothed signature of Pittosporum eugenoides before and after the removal of smoothing artefacts A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 20 User Guide of 53 Generally bigger filter sizes remove more noise while higher polynomial orders fit the original data values better 4 2 7 3 Sensor Synthesizing Downsampling The sensor synthesizing downsampling is effectively a data reduction operation The response of the sensor selected as the current sensor is calculated from ASD data The synthesizing of other sensor responses using ASD data is useful due to several reasons 1 Reduction of dimensionality 2 Dir
45. iconnect host localhost db spectral ab user opec traProc password SpectraProc 2 3 6 Running SpectraProc Query Interface The main source file is called spectra_proc_query tcl Double clicking this file will invoke the TCL interpreter and start the application Tip create a shortcut to spectra_proc_query tcl on your desktop for easy access A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 9 User Guide of 53 A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 10 User Guide of 53 3 Design of Sampling Experiments 3 1 Overview The data collected during sampling campaigns must be organised in a structured way in order to allow the automated import into the spectral database Section 3 2 explains the background of the structure used and section 3 3 gives a practical example of a directory and file structure that should be adopted for data collection Preferably sampling experiments should be designed to reflect the structure used by SpectraProc Alternatively existing data can be arranged to meet the requirements 3 2 Hierarchical Structure A hierarchical data structure that reflects the real world and the setup of sampling campaigns for vegetation is used This structure is derived from the following conditions 1 Reflectances of several different species are captured 2 In order to describe the in species variation several specimens of a species are sampled 3 The variability o
46. itten in three data formats 1 CSV Comma Separated Values for import into various 3 party applications like spreadsheets or statistic packages 2 ENVI Spectral Library for import into ENVI and subsequent use for e g signature matching and 3 ARFF which is a special format used by WEKA WEKA is a collection of machine learning algorithms for data mining tasks University of Waikato 2005 ASD CSV Binary File File q NI Q a SpectraProc ENVI E T ENVI Z Spectral Profile 5 Library File a File E N Sensor Speci fica tons ARFF File Spectral DB Figure 4 File System Interfaces A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 13 User Guide of 53 4 1 3 SpectraProc Operation SpectraProc is study based e spectral data is grouped into studies Advisably a new study is created to hold data for every new sampling experiment The spectral data files of studies must be structured according to the hierarchical structure introduced in 3 This structuring allows the auto mated loading of spectra into the database Typically the operations carried out on a study are 1 Creation of a new study 2 Loading of spectra 3 Repeated pre processing and analysis In ongoing studies new data can be added to the database by simply selecting the loading oper ation again Only new spectra will be added to the database in this case 4 1 4 Spectral Proce
47. kfern Blackfern 1 00E 02 Blackfern Blackfern 8 00E 01 Blackfern Blackfern Blackfern 6 00E 01 Blackfern Blackfern ae Blackfern Blackfern 2 00E 01 Blackfern ______ Blackfern 0 00E 00 a a O Cabbage_tree 0 00E 00 5 00E 02 1 00E 03 1 50E 03 2 00E 03 2 50E 03 3 00E 03 Cabbage_tree Cabbaae_tree Figure 56 A plot showing mainly noise A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc User Guide 4 00E 00 Blackfern _______ Blackfern 9 00E 01 Blackfern Blackfern 8 00E 01 Blackfern _____ Blackfern 7 00E 01 Blackfern _______ Blackfern 6 00E 01 Blackfern 5 00E 01 Blackfern Blackfern 4 00E 01 Blackfern Blackfern 3 00E 01 Blackfern Blackfern 2 00E 01 i Blackfern A Blackfern 7 a i ______ Blackfern ES 0 00E 00 Cabbage tree 0 00E 00 3 00E 03 Cabbage_ tree Cabbagae tree Figure 57 The same plot as above but rescaled to a reflectance of 1 0 Page 45 of 53 Once the waveband filter is setup repeat the export function close the previously written file first in Excel and load it again into Excel and plot it The plot will look similar to the one shown in Figure 59 Note that now the noise regions are plotted as straight line segments For visualization pur poses this should be avoided as it suggests that data exists in the filtered regions 1 20E 00 1 00E 00 Black
48. lick on the arrow pointing towards the right to shift this class into the Endmember list Similarly to move an endmember back to the Classes list select the endmember and click the arrow pointing towards the left Endmember Selection Classes Endmembers OV 360P 360 _0P A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 29 User Guide of 53 Figure 36 Endmember Selection dialog 4 2 10 2 Abundance Settings Before invoking the abundance settings the endmembers should be selected as described in 4 2 10 1 To display the abundance settings dialog select Spectral Mixing gt Abundance Settings All mixtures are listed in the Classes excl endmembers list box The abundances of the end members are set for each of these mixtures by 1 Selecting the mixture 2 Select the endmembers that are contained in the mixture one after another from the Available endmembers list box and shift them down into the Selected endmembers list box 3 For every selected endmember do select the endmember by clicking on it then enter the abundance in the provided box Click Save The total abundance is updated When defining the abundance of the last endmember click on Complement This automatically assigns the abundance to the last endmember by summing the total abundance to 1 Abundance Settings Classes excl endmembers Available endmembers Selected 0 667 Abundance of endmembers selec
49. ling 20 10 2006 spectra with the SpectraProc Query tool Depending on the sensor dimensionality only feature spaces with 20 10 2006 less or equal number of dimensions are selectable in the GUI E g DGVI s dimension 10 cannot be built if Landsat data is syn thesized PCA can now be carried out on multispectral sensors like Landsat 20 10 2006 and Cropcircle ACS210 6 1 2 Fixed Bugs gt fe OO O bo Version deleting studies function PCA output and file is open PCA output file Feature space list not updated Update feature space list when 18 4 2006 when derivative settings changing derivative calculation change corrupt files Check if data exists before starting available the eigenanalysis PCA on Landsat 7 crashes Limit the dimensionality of the fea 20 10 2006 because 1 feature space is ture spaces to smaller or equal the PCT_10 cant build matrix number of bands of the sensor A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 52 User Guide of 53 6 1 3 Known Bugs SpectraProc Problem Work around Version V1 1 The application will crash when Just avoid doing this There is a logic ex building a library using a feature planation why this cannot be done space that requires certain wave Implementing a check to disable such user lengths on sensors with not enough actions is too time consuming at this point band information Can occur when e g redefining the DGVI s to ha
50. n listbox contains a selection of feature spaces The numbers at the end of the names are equal to the number of com ponents used in the feature space E g PCT_ 10 will effect a PCT using the first 10 components of the transformation matrix i e the data will be reduced to 10 variables dimensions Select PCT_5 as feature space The discriminating power of feature spaces can be assessed by carrying out a discriminant analy sis Before the DA can be executed the library for the current processing chain settings must be built see 4 2 11 how to build libraries Then subject the data to DA see 4 2 12 2 for details The resulting overall accuracy should be around 90 7 The DA results are detailed in the DA output file Error_Matrix csv see Table 6 The columns are the species that were classified The number of correctly classified spectra is contained in the diagonal elements The errors of omission are written in the off diagonal elements E g 6 Blackfern spectra were wrongly classified as Cabbage tree Close the DA output file select PCT 10 as feature space and repeat the process of library building and DA and inspect the DA output file once more The classification accuracy should have risen to 100 A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 48 User Guide of 53 Scree Plot 2 5 5 1 5 Eigenvalue 0 5 0 i 0 2 4 6 8 1
51. nections 0 This allows unlimited access If you want to limit the access select positive values O The new user should have access rights for localhost by default If not so add local host to the list of hosts from which the user SpectraProc can connect click on the icon under User Accounts to do this 2 1 4 Network Access The SpectraProc application can access the database over the network if the following configura tions are performed O The IP addresses of all machines from which the user SpectraProc can connect are added to the SpectraProc privileges Alternatively a range of IP addresses can be configured using a netmask see MySQL online documentation for details or a value of will allow access from any possible machine O The port of the MySQL server 3306 by default is not blocked by Microsoft Windows A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 7 User Guide of 53 2 2 SpectraProc Application Copy the SpectraProc directory supplied on the installation CD to C Program Files Open the di rectory after copying it and open spectra_config txt Edit the configuration file as described below O Server if the database is running on a machine different to the machine this copy of SpectraProc is installed on change localhost to the IP address of the database server If the database is access over the network also see 2 1 4 O Database if the database has been given a differ
52. on JM Cancel Maori ICB C Latin JM andB Folder Figure 38 JM B Distance dialog The JM distance is listed in the upper triangular matrix the B distance in the lower triangular matrix see Table 1 The JM distance is asymptotic to 2 0 A JM distance of 2 0 indicates a complete separability and a distance of 1 9 a good separability Richards 1993 The B distance is not asymptotic and can get infinite Inf due to limits in numerical precision Table 1 Example of a JM and B output using a 10 dimensional DI feature space Blackfern Cabbage_tree Lemonwood Blackfern 1 93 1 90 Cabbage_tree 3 41 1 76 Lemonwood 2 99 2 11 4 2 12 2 Discriminant Analysis Discriminant analysis DA uses a discriminant function to assign a class to samples In the case of the calibration set being subjected to DA the result is an assessment of the separability of the classes The DA is carried out in the currently selected feature space The DA result is thus also an assessment of the discriminating power of the feature space Note that the discriminant function used is the one currently selected in the main window Before running DA the library for the current pre processing settings must exist See 4 2 11 on how to build libraries To run the DA select Statistics gt Discriminant Analysis A dialog will be displayed to select the names to be used in the output Figure 39 A Hueni UserGuide_V1 2b doc Version 1 2b 13 10
53. on requires as input the eigenvectors of a given dataset A prin cipal component analysis PCA must be carried out before PCT can be applied to the data PCA results in eigenvalues and eigenvectors The eigenvectors are used in the transformation matrix G If only the first n components are to be used the transformation matrix is a sub matrix of G con sisting of the first n column vectors The dimension of the resulting feature space is therefore n y G x nxm mxl NTBI nxl where m original size of data space n new size of data space equal to the number of selected components 4 2 7 5 4 Creation Modification and Deletion of Feature Space Definitions Based on the three basic feature space types new feature spaces can be created Existing feature spaces can be edited or deleted For any of these functions navigate to the Chain Settings gt Feature Space submenu Figure 28 as Statistics Spectral Mixing Help Waveband Filter Setup i Feature Space Edit CoadedSpect Copy and Edit yl i be Delete Figure 28 Feature Space Submenu To create a new feature space select Copy and Edit or New in the Feature Space submenu New opens up an empty dialog for the definition of a new feature space Copy and Edit copies the settings of the currently selected feature space into the dialog The settings can subsequently be changed before creating the new feature space in the database To modif
54. ooocccooccccoccnccncnconccnoncncnnnncnnnnnnnnnnnnnanos 6 2 1 3 Setting up the Spectral Database Schema Tables and US8FS ooccocccocccnniconconnconionnnos 6 21A INGIWONC ACCC os 6 2 2 SPeCilaPloc ADpiICaOn ieee ee a ee 7 23 opectraProc Query Itaca ade 8 Za Instala TELA a tds 8 2 9 2 Installing Mysgltel Package ii aci n 8 LO wa 1K 04 07210 Gh mat 161 2 0 O sad 8 2 3 4 Installing SpectraProc Query Interface ooccconcconncconococncocononcnoncnonnnnonnnononnonnnonnnoncnnnanonoss 8 2 3 5 Changing the Database Connection coocccocnccocncccnccocnconnnonnononnnnnnonnnonnnnonnnnnnnnnnnnoncnenaninoss 8 2 3 6 Running SpectraProc Query Interface cocoocccocncconccocncoonoconncnnnononononnnnnnnnnnnonnnnnnnonanenons 8 3 Design of Sampling Experiments ccccccssceseeeseeeeeeeeeneeeeeeeeeseeeeeeneseeeees 10 Del OVER 10 g2 a liege OtUliCuune Si seeh A een A Late echt ae ctr oe Co aol eke 10 3 3 Directory Structure and Spectral Files ccooocccconcconnconncccnoconcconnnonnncnnnonnnonnnonannonanonaninons 10 4 OperatloO Maia 12 Ai OVENI SW anaa e A ge ha tea a ee eet PL a ee ae ee 12 A gt 42 A e ad 12 412 File System VC ACCS acest ts cctlne se each att acess a eat adnate A a a dee dad AAA 12 AT lt SPSCUAr TOC OMSlaAUON a Aa 13 4 1 4 Spectral Processing CONCEPt ccoccocncconoocnononconccnnconocanccononononaconnccnnnnanonncnanonanennrennnennenanos 13 DZ ROC 811 OC we tsa O on ot Serica
55. or Microsoft Directory Services OK Cancel Help Figure 45 Data Link Properties Provider tab In the Connection tab select the data source from the dropdown list and enter again the username and password SpectraProc Figure 46 Click OK Data Link Properties Provider Connection Advanced an Specify the following to connect to ODBC data 1 Specify the source of data Use data source name Spectral DB y Refresh C Use connection string 2 Enter information to log on to the server User name SpectraProc Password Blank password Allow saving password 3 Enter the initial catalog to use Figure 46 Data Link Properties Connection tab A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 37 User Guide of 53 The database is now listed in ArcCatalog and the tables are displayed when selecting the database Figure 47 A ArcCatalog Arcinfo Database Connections SpectralDB odc File Edit View Go Tools Window Help ga m SE 88 GA E mL Location Database Connections SpectralDB ode Stylesheet X Contents Preview Metadata Name Type i band_range MySQL Table gt 16 Database Connections derivative MySQL Table Add OLE DB Connection derivative_calc_method MySQL Table Add Spatial Database Conr Feature_space MySQL Table 4 9 feature_space_type MySQL Table Y Address Locators library MySQL Table is GIS Servers mixture MySQL Table
56. rs O03 OV S60P 0202 30601 0B 4 2 13 Adding new Sensors New sensors can be added to the database if their properties are known The sensors details must be entered in a tabulator formatted file as described below Two classes of sensors are supported Gaussian and Ratio see also 4 2 7 3 The header structure is identical for both sensor classes lt Sensor name gt lt Sensor description gt lt Column headers gt The sensor name should not include any of the following characters lt gt The column header line is not interpreted by the program and exists only for the convenience of the user preparing the sensor description file For Gaussian sensors the file body contains one line per sensor band lt Band gt TAB lt Average Wavelength nm gt TAB lt FWHM nm gt TAB lt Calibrated Y X gt For Ratio sensors the file body contains 1 to many lines per band to model the response see also Figure 23 lt Band gt TAB lt Wavelength nm gt TAB lt Ratio gt Examples of Gaussian and Ratio sensor description files are given in tables 4 and 5 A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 34 User Guide of 53 Table 4 Example of a Gaussian sensor Hyperion Hyperion Hyperion Sensor as flown on BOL A ye IS E AT a A 3 q q63 gt ymme sl asemfx IES E RES a A 896 29 as3empx po ws amssampx o IS E EAN D ES O A RN a Table 5 Example of a Ratio sensor Landsat7
57. ry SpectraProc Warning The study Random Materials including all spectral data will be deleted Click OK if you want to delete this study cancel Figure 11 Deletion warning box 4 2 4 Study Report To display name description datapath number of minimum spectra per endmember number of species number of spectra and the capturing timeframe of a study select Database gt Study Re port Figure 13 Chain Settings Statistics Create New Study Delete Current Study Study Report Import Spectr ks to current Study Import Sensor Figure 12 Starting a study report 4 2 5 Selecting Studies To select a study to work with select the appropriate study from the drop down list in main window Figure 13 A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc User Guide Current Study NZ Native Plants Ramiha soil slicel SP Ramiha_grass Pos_dep_outdoors Probe Rotation p Ot A AAA a Figure 13 Selection of current study 4 2 6 Loading Spectra Page 17 of 53 To load the spectra of a study into the database make sure the correct study is selected Please refer to 4 2 3 on the process of selecting the current study Then select Database gt Import Spec tra into current Study Figure 14 A popup window will appear indicating the loading progress Additionally the loaded species are listed in the message window Er EA Chain Settings Statistics Creat
58. s directories of the study This main directory is the folder that needs to be specified when creating a study in the database see 4 2 2 The names given to the species directories are stored in the database and are included in file output if Folder name is specified as desired name type see 4 2 8 for more information on file export A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc User Guide Page 11 of 53 The species directories contain the site directories These can be named freely and the sites will be automatically numbered when read into the database Thus naming a site 1 or s1 is perfectly acceptable The site directories contain all spectral files collected at this site They are auto numbered by the ASD capturing software Folders X Name Pee TIITTTTTITTTTTTT Aeeeeeceeeeeescseseeseeeeseseeeeed 5 Blackfern E cabbage 001 5 site1 E cabbage 002 E Cabbage_tree Ef cabbage 003 O sitel E cabbage 004 5 site2 E cabbage 005 5 Lemonwood E cabbage 006 5 site1 E cabbage 007 5 site2 Ef cabbage 008 4 sites ES cabbage 009 Size 9 KB 9 KB 9 KB 9 KB 9 KB 9 KB 9 KB 9 KB 9 KB 9 KB Type 000 File 001 File 002 File 003 File 004 File 005 File 006 File 007 File 008 File 009 File Figure 2 Example of a directory structures holding spectral files A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 12
59. s upon the parameters that are defined at that point in time for the processing cascade If e g Synthesized is selected every spectrum is put through the cascade of filtering smoothing and synthesizing and is then written to the file l e if a certain stage is selected all the preceding stages are automatically performed The data can be averaged either on site level or on species level If the site mean is chosen a col umn containing the site number will be added to the output file Selecting the All spectra option performs no averaging but writes every spectrum to the file The averaging is the last step of the processing e g if the Synthesized and Mean per species is selected then all spectra of each species are processed till the synthesizing stage and then averaged and written to the file Three file formats are currently supported O CSV Comma Separated Values O ENVI spectral library file O ARFF WEKA file format The species that are written to the file can be controlled by selecting on of four options O Include all species all species are written O Include only library relevant species only species that have equal or more than the minimum number of spectra are written The minimum number of spectra is set when defining a new study see 4 2 2 O Only endmembers only species that have been designated as endmembers are writ ten O Only mixtures only species that are not designated endmembers are written
60. ssing Concept The spectral database only stores the raw spectral data Further processing of the spec tra is performed at runtime and the results are held in memory Once a spectrum is loaded from the database it is put through a cascade of operations as shown in Figure 5 The result of every stage is saved in a sepa rate data structure in memory This allows easy file export of spectral data at any pro cessing step Consequently the structure of this process ing chain implicates that a change of pro cessing parameters of any stage will influ ence the results of the subsequent stages A complete set of pre processing parameters thus describes the processing from raw to feature space transformed data All processing settings are stored in the data base when a library is built Repeated proc essing of the data with the same settings will always result in the same final data set Spectral DB Load spectrum Wave band filtering A Raw data Xx Y Waveband filtered data NE Smoothed data XL Synthesized data Derivative calculation A Derived data Feature Space Trans formation Ni Data in Feature Space Figure 5 Spectral data processing cascade A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 14 User Guide of 53 4 2 SpectraProc 4 2 1 User Interface The graphical user interface GUI is based on the structure of the proce
61. ssing cascade see Figure 6 The left side of the main window consists of controls for the selection of the study and the main settings for smoothing filter synthesizing derivative calculation feature space transformation and classifier discriminant function Processing details are entered in pop up windows which are ex plained in the relevant sections The text output panel report window in the middle of the main window is used to display processing and error information The listbox on top of the text output panel is used to display spectra files that are loaded directly into memory The Indiv Classify button under it classifies the selected individually loaded spectra against the current library The library status box on the top right of the screen indicates whether statistical information has been compiled for the current pre processing settings j List of directl Classification button for direct Study selection y y Library status field loaded spectra loaded spectra Smoothing filter ES Connected to spectrol_db on localhost SpectraProc TER Fie Library Database Chainettings Statistics Spectral Mixing Help Test Smoothing filter W detail settings button Current Study gaded Spectra gt NZ Native Plants M Library Status Not Refy Smoothing Filter
62. st be identical A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 32 User Guide of 53 Discriminant Analysis using independent Dataset Select study to be used as independent dataset lans Pasture Mikes Grapes AgResPlots Cancel AgRes Ramiha AgRes Manawatu Soillab 3M aterials_LS1 PosDep_2Mat hManamahi arase Figure 40 Selection dialog for independent data sets 4 2 12 3 Principal Component Analysis Principal components analysis PCA is applied after the derivative calculation step l e the PCA is carried out for the current settings of waveband filtering sensor synthesizing and derivative calcu lation To run PCA select Statistics gt PCA A message stating the output file similar to the one below is displayed in the message window Principal Component Analysis PCA output written to file Cr Data MPhil Remote Sensing SpectrarProc outputApes ocutpUL CSYv The two first components will be plotted as a scatterplot in a graphics window this plot is also known as scoreplot The pca_output file contains the eigenvalues proportions cumulative proportions see Table 3 for an example and the eigenvectors also know as factor loadings The eigenvectors can possibly be used to assess the significance of the wavelengths in respect to the each component The eigenvalues and eigenvectors are stored in the database Table 3 First ten eigenvalues and proportions of a PCA PC Eigenv
63. ted endmember Save Complement 11 Total abundance Figure 37 Abundance Settings dialog 4 2 11 Library Building A library is a collection of statistics data built for a certain configuration of the processing chain The Library status field in the main window indicates if a library has been built for the current process ing settings To build a library select Library gt Build 4 2 12 Analysis 4 2 12 1 Separability Before running the separability analysis the library for the current pre processing settings must be built See 4 2 11 on how to build libraries The JM and B distance analyses are carried out in the A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 30 User Guide of 53 currently selected feature space l e the discriminating power of feature spaces can be assessed by the separability analysis To run the separability analysis select Statistics gt Separability Report In the displayed JM B Dis tance dialog select the name and distance type and press OK Figure 38 A short message will be displayed in the message window looking similar to Separability Analysis Using JM and B distance JM and B output written to file Ci Data MPHIL Remove Sensing Spectrearroc Outpuc UM and B OUEPut esv The output filename is shown in this message Note that only library relevant species are included in this report JM B Distance Names Y Distance Type Comm
64. the above formula n times The SavGol method uses Savitzky Golay coefficients to calculate the derivatives In this case the derivative is actually the derivative of the approximating function at the wavelength of interest Thus the SavGol method automatically performs a smoothing of the data This can be useful when deal ing with noisy data where a single smoothing operation is not removing enough noise Both methods loose N data points per valid segment where N is the derivative order OO OI coa Derivative A Calculation method Derivative Calculation method Calculation method p 1 a Iterative 1 or Iterative Poa Pers s C SavGol EN SavGol A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 23 User Guide of 53 Figure 26 Derivative calculation settings zero derivative left first derivative iterative middle and first derivative SavGol method right For the SavGol method the filter size and polynomial order can be modified by clicking on the Edit button This brings up the Derivative Filter Details dialog Figure 27 The filter size and order are automatically restricted to meet the following minimal conditions for the calculation of the derivative polynomial order derivative _ order filter size max polynomial order 1 derivative order 1 Thus the minimal filter size depends on both the polynomial and the derivative order A minimal filter size of deriv
65. thing_filter_type E Species E spectrum E statistic E study waveband_filter waveband_filter_range Name site Show of type Datasets and Layers lpr v Cancel Figure 49 Selecting the site table as data source A Hueni UserGuide_V1 2b doc Page 38 of 53 Version 1 2b 13 10 2008 SpectraProc Page 39 User Guide of 53 4 3 SpectraProc Query Interface 4 3 1 Introduction SpectraProc Query was written as an example of an intuitive interactive query building interface It was written in TCL TK with the goal to get to know the characteristics of that language It has proven to be extremely powerful for rapid development of graphical user interfaces A further ad vantage are the string handling capabilities that are useful for the building of SQL queries One of the shortcomings of SpectraProc is the limitation in graphic output Certainly most users would like to see their spectral data visualized Furthermore an overview over the different studies Campaigns species and sites was not available via the SpectraProc application SpectraProc Query can build reports on four different levels campaign study species site and spectrum The report output can be restricted by specifying conditions 4 3 2 Database Connection The database connection is currently hard coded and SpectraProc Query will consequently only run on the localhost i e the same machine as the database is installed on This can be ch
66. to any positive number If a species has less than the specified number of samples it will not be included in the statistics calcu lations when building libraries Once a new study is created it will automatically be selected as the current study Create a new study Study name iM y new study Study description 2 example Species directory path fistratorDesktop egetation_example Browse Number of samples per 11 5 species for library Figure 8 New study dialog Browse for Folder Current Selection C Documents and Settings Administr Desktop a My Documents 4 My Computer HA 3 Floppy 4 ge Local Disk C 2 Recycle Bin 3 My Psion MO egetation_example A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 16 User Guide of 53 Figure 9 Directory tree dialog 4 2 3 Deleting an existing Study To remove a study and all associated data from the database select this study as the current study then select Database gt Delete Current Study Figure 10 Before any data is deleted a warning will be displayed Figure 11 To delete all data of the current study click OK to abort the operation click Cancel The message window will list the involved operations of the deletion Chain Settings Statistics Create New Study Delete Current Study ho Study Report Import Spectra into current Study Import Sensor Figure 10 Delete Current Study menu ent
67. ts 2 rows loaded in 0 307 seconds NZ Native Plants New Zealand Native Plants C Data MPhil Remote Sensing NZ_Sp ecies NZ Natives Indep New Zealand Native Plants indep C Data MPhil Remote Sensing indepe endent dataset ndent_samples 4SD Figure 51 Campaign Report 4 3 4 2 Species Report An example of a species report is shown in Figure 52 The reported attributes are folder name common_name latin_name Species Query Results 3 Species Query Results 39 rows loaded in 0 149 seconds folder_name Blackfern Black tree fern Cyathea medullaris Broadleaf Broadleaf Griselinia littoralis Cabbage_tree Cabbage tree Cordyline australis v lt Figure 52 Species Report 4 3 4 3 Site Report An example of a site report is shown in Figure 53 The reported attributes are capture_date longitude latitude and altitude A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 42 User Guide of 53 Site Query Results 5 Site Query Results 2 rows loaded in 0 136 seconds 2005 07 01 11 44 48 175 499454 39 323483 1269 611111 2005 07 01 11 47 26 175 4994 39 323531 1268 355556 Figure 53 Site Report 4 3 4 4 Spectrum Report An example of a spectrum report is shown in Figure 54 The reported attributes are reflectances as a spectral plot disabled flag as checkbox spectrum number auto number by ASD pathname ASD comments as entered in the capturing software on the field laptop T
68. ve only 5 dimensions and then try to calculate DGV s from Landsat data The application can sometimes just A reboot of the system helps here refuse to load This is some effect of the Symantec Internet security SpectraProc not being in the list of programs that are allowed to access the database port probably cou pled with hibernating the machine 6 2 SpectraProc Database 6 2 1 Added Features SpectraProc Database Version V1 1 Added disabled field to spectrum table 20 10 2006 Removed the not null constraint and added a default value of null for the BLOBS in pca_data spectrum and statistic A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 53 User Guide of 53 7 References Bojinski S Schaepman M Schlaepfer D Itten K 2003 SPECCHIO a spectrum database for remote sensing applications Computers amp Geosciences 29 27 38 Elvidge C D Chen Z 1995 Comparison of broadband and narrowband red and near infrared vegetation indices Remote Sensing of Environment 54 38 48 Fliege N J 1994 Multirate Digital Signal Processing John Wiley amp Sons Chichester Keshava N Mustard J F 2002 Spectral Unmixing IEEE Signal Processing Magazine 19 1 44 57 Kusumo B Hedley C B Hedley M J Hueni A Tuohy M Arnold G C 2008 The use of diffuse reflectance spectroscopy for in situ carbon and nitrogen analysis of pastoral soils Australian Journal of
69. y an existing feature space select Edit All the above three commands invoke the same dialog shown here on the example of a NTBI fea ture space consisting of three individual NTBlIs Figure 29 The name of the feature space can be any alphanumeric string of maximal 45 characters the description can be any alphanumeric string of maximal 250 characters The bands listbox lists the band combinations used to calculate the indices E g index 1 uses bands 550nm and 468nm New band combinations are entered by click ing on New existing band combinations are modified by clicking modify Both commands bring up a dialog box to define the two bands Figure 30 To delete an existing band combination select the combination in the list and click Delete The dimension field in the Feature Space dialog is non editable for Dls and NTBIs where it reflects the number of band combinations For PCT feature spaces the dimension field specifies how many components are to be used for the transformation In the given example the first 10 components will be used Figure 31 A Hueni UserGuide_V1 2b doc Version 1 2b 13 10 2008 SpectraProc Page 25 User Guide of 53 Feature Space Name NDVI 3 Description i Thenkabail et al 2000 l Dimension E E Bands nrn 550 468 nm 11550 682 nm 11920 696 nm New Modify Delete Figure 29 Feature Space edit dialog on the example of a NTBI feature space Waveband Definition

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