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1. NEV r l D gt A A o CROMOVET IN UNIVERSITY OF BRISTOL NERC INTERNSHIP REPORT Aerial Photogrammetry for the Earth Sciences Author Supervisor Drew SILCOCK Dr Juliet Biggs NERC SCIENCE OF THE SN WAINO NI Mis aE Monday 29t September 2014 1 Introduction The aim of this project is to investigate the practical use of photogrammetry with a focus of its applications to the Earth Sciences It covers the methods used to gain photogrammetric data and analyses some results taken from fieldwork 1 1 How photogrammetry works The basic principle of photogrammetry is the same mechanism by which the eyes infer distance triangulation By moving around an object or parallel to a faade one can infer the distance to the object by a simple trigonometric calculation as demonstrated in Figure 1 By leveraging this simple trigonometric distance calculation one can infer from the group of photos of the same object taken using the appropriate method as described in Section 2 1 the distance to any point in the photos and thus built up a three dimensional model of the captured objects Importantly this can be achieved without need for explicitly inputting the location that the photographs were taken although it does increase the accuracy of the resulting model as discussed in Section 2 4 1 2 Unmanned Aerial Vehicles To gain the photographs and geopo sitioning data for the photogrammet Object ric reconstruction we emplo2. until k gt 0O if k lt 5 then gosub chiup if k gt 4 and k lt 8 then gosub chimid if k gt 7 and k lt 11 then gosub chidown if k gt 10 and k lt 14 then gosub ch2up if k gt 13 and k lt 17 then gosub ch2mid if k gt 16 and k lt 20 then gosub ch2down if k gt 19 then print error wend end chiup print ChiUp Shoot k set_zoom s shoot sleep 1000 return chimid print ChiMid Stowed k set_zoom i sleep 1000 llhttp plane ardupilot com wiki common chdk camera control tutorial 19 return chidown print Ch1Down Extended k set_zoom o sleep 1000 return The variable k set equal to the current power going into the camera through the USB port corresponds to different pulse widths as given by Table 31 Pulse Width ms lt O gt 4 and lt 8 gt 7 and lt 110 Table 3 The conversion between PWM widths and the value taken from get_usb_power 12nttp plane ardupilot com wiki common chdk camera control tutorial 20 C Models All of the photogrammetric models discussed in this report along with many others are available to view online at https sketchfab com drewsberry models In particular the following discussed models are available for viewing Long Ashton Without GCPs https sketchfab com models ec777be4b73f4e7a8fdd992c2b8d026a Long Ashton With GCPs https sketchfab com models deaac286092b48498ef 24cf6cae55b5f Avon Gorge Pass 1 No GCPs ht
3. Clearly the orthophoto shows that the 63 photos were sufficient to build a model of the topography of the area However the Digital Elevation Model shows that the photogrammetric reconstruction interpreted the topography as on a significant tilt head from the car park up to the building We hypothesise that this tilt is due to the lack of GCPs to correct for such systematic errors This is discussed with reference to the model produced with GCPs in Section 4 1 2 and also with reference to the Avon Gorge reconstruction in Section 4 2 Figure 8c shows that the overlap between the photos is more than adequate in all the central areas of the model only reducing to lt 9 around the very edges of the area 6 80172 m a The generated or c The calculated photo thophoto for the Long b The generated DEM graphic overlap achieved Ashton data set without for the Long Ashton data in the Long Ashton photo GCPs input set without GCPs input dataset Figure 8 The data produced by PhotoScan from the Long Ashton aerial im agery without factoring in GCPs 4 1 2 With GCPs The reconstruction was then rerun with a limited number of Ground Control Points input These GCPs were taken using distinguishable features from the landscape and their geolocation found from Google Earth to test the effect they would have on the resulting model and DEM The first DEM was taken as the centre of a pond the second the corner of a fence and the thir
4. are input into PhotoScan Optimise alignment The camera alignment is then optimised using the GCP data Build Dense Point Cloud PhotoScan subsequently builds a dense point cloud from the sparse point cloud Build Mesh Penultimately the mesh is built by joining the dense point cloud into a smooth model Build Texture Finally the mesh is overlaid with a texture finished the pho togrammetric reconstruction Once this workflow is accomplished the resulting model can be exported as an orthophoto whereby the original photos are stitched together into a single aerial image and as a Digital Elevation Model DEM which contains all the information about the topography of the model It is this DEM that is of application to Earth Science research 1 3 3 Canon Hack Development Kit In order to control the camera remotely we employed the Canon Hack Devel opment Kit CHDK Specifically we used firmware version 1 00B Alpha for the Powershot IXUS132 loaded by a bootable SD card This allows one to run scripts on the camera written in either Lua or UBASIC that interface with the camera mechanism e g taking pictures zooming turning off etc This allowed us control over the camera during the flights Shttp www agisoft ru products photoscan professional http chdk wikia com http chdk wikia com wiki ELPH115 2 Methods 2 1 Photographic Technique As per the PhotoScan user manual the photos were taken at an o
5. effective as the exact location of the marker can be precisely set to the centre of the cross As per the PhotoScan website roughly 10 GCPs are required for the com pletion of the georeferencing while 15 or more GCPs are preferable for improved accuracy The laser based surveying equipment used to identify the GCPs is shown in Figure 6 3 Theory 3 1 Calculating Resolution as Function of Height http edwardns com shutterlag html 8 As per http copter ardupilot com wiki common geotagging images with mission planner Geotag_Mode and https store 3drobotics com products 3dr gps ublox with compass nttp www agisoft ru wiki PhotoScan Tips_and_Tricks Ground_Control Camera Camera Ground Distance photographed x Distance photographed y HORIZONTAL VERTICAL a The horizontal view of the angle of b The vertical view of the angle of view view of the camera facing the ground of the camera facing the ground Figure 7 The views of the angle of view as the camera faces directly towards the ground If one knows the resolution of the camera the height from which the photo was taken and the angle of view of the camera then one can calculate the resolution of the resulting pho tographs in terms of how many me ters correspond to a single pixel To do this the geometry of the situation illustrated in Figure 7 is parametrised as follows e Distance photographed along ground x and y Figure
6. few seconds 2 4 Geotagging In order to increase the accuracy and precision of the camera location in Camera Timings Average Time Taken s Set Time s Figure 3 The measured averaged time difference between successive photos plotted against the interval input into the script 11 photos giving 10 time differences were taken Figure 4 The cable used to connect the camera running CHDK to the APM board PWM signals are sent through this cable and interpreted by scripts running on the camera the photogrammetry software and thereby the accuracy and precision of the final model the photos are tagged with their location by using the UAV s on board Global Positioning System GPS The geolocation is written either into a separate comma separated value CSV file or is written directly into the exif metadata of the photos themselves Either can be imported into PhotoScan The technique used to determine the location of the photographs depends on whether the photographs were taken using the time interval script or as con trolled by the APM autopilot 2 4 1 Time Offset Method If the camera is set to automatically take pictures every 5 seconds then one needs to know the difference between the internally logged time on the camera stamped onto the photographs exif metadata by the camera automatically and the GPS time on the UAV As the UAV constantly takes logs of its GPS location and the time knowing t
7. oblique gle angle c The model produced using only the second pass of photos masking out the sky Figure 10 A visual comparison of the relative error induced in the models pro duced in the first and second passes at zenithal and oblique angles respectively 14 g gt 9 a9 a8 a7 m6 a5 a4 a3 a2 a1 _ gt D aii d The calculated positions of the c The calculated cameras along with a The generated b The generated photographic over the errors involved orthophoto for the DEM for the Avon lap achieved in the in these calcula Avon Gorge data Gorge data set no Avon Gorge photo tions representation set no GCPs input GCPs input dataset no GCPs as ellipses Figure 11 The data produced by PhotoScan from the Avon Gorge horizontal imagery no GCPs input 15 24 5654 m a The generated orthophoto for the 2 Avon Gorge data set with 14 GCPs b The generated DEM for the Avon input Gorge data set with 14 GCPs input c The calculated photographic over lap achieved in the Avon Gorge photo dataset with 14 GCPs d The positions of the input GCPs Figure 12 The data produced by PhotoScan from the Avon Gorge horizontal imagery with 14 GCPs input 16 Without GCPs With GCPs Flying Altitude m 16 5655 51 5781 Ground Resolution m pix 0 00339199 0 00260205 Error pix 1 02017 4 76105 DEM Resolution m pix 0 013568 0 0692152 Table 2 The PhotoS
8. tilted as it is attached to the UAVs 4 2 3 With GCPs Once the GCPs are input there are several important effects The photographic overlap of the gorge increases with only the very corners having less than 9 overlapped photos covering it With more accurate georefer encing the software recognises the photos as taken more spread apart and thus with better coverage of the corners of the model The tilt present in Figure 11b disappears as shown in Figure 12b The produced model now correctly identifies the bottom of the gorge as level This indicates that the slopes present in the Avon Gorge and Long Ashton models are merely artefacts of the lack of GCPs which when the sufficient number of GCPs are introduced disappears The data produced by PhotoScan is shown in Table 2 As in Table 1 the flying altitude is increased significantly for the GCP georeferenced model al though in this context the flying altitude has less meaning owing to the fact that the photographs of the gorge were taken horizontally As before the ground res olution is better again due to the different value of the flying altitude inferred from the software The difference in reprojection error is more pronounced here which could be explained by the higher number of GCPs with the model fully accurately 13 a The model produced using only the b The model produced using only the first pass of photos at the zenithal an second pass of photos at the
9. 0 user Manual Capturing Scenarios Page 5 http downloads agisoft ru pdf photoscan pro_1_0_0_en pdf are taken from a height h For the Ixus 132 we used with a 48 9 requiring an overlap of w 0 8 gives ding 0 182h meters second 11 If the photos are taken once every five seconds tint 5 seconds as we did then this gives a maximum UAV velocity of din vuAV gt t 0 0364h meters second 12 ant Taking a reasonable height of h 50 meters thus gives vu AV 1 82 meters second 13 This is a very reasonable and achievable speed 4 Results Two sets of data were taken and are examined here in terms of the accuracy of their produced models and the possible causes of error in the reconstruction process The first set of photographs were taken at Long Ashton Farm outside Bristol and the second set were taken at the Avon Gorge in Bristol 4 1 Long Ashton For this data set a hexacopter was used to gather a total of 63 aerial images The time interval technique was used to take the photos and the time offset method used to geotag the resulting photos 4 1 1 Without GCPs Firstly the reconstruction was run without the Ground Control Points in put and without any photographic alignment optimisation The resulting or thophoto is shown in Figure 8a while the DEM is shown in Figure 8b and the photographic overlap is shown in Figure 8c The produced model is available to view interactively online
10. 6 The equipment used to survey e Resolution of camera n pix in Ground Control Points els r and ry e Height from which photo was taken h e Angle of view of camera a and ay e Number of meters correspond ing to a single pixel us and py Then according to this parametrisation as a matter of elementary trigonom etry tan and 1 m 3 2 Rearranging this for x and y gives x 2htan and 4 y 2htan 5 Then the resolution in meters per pixel is simply this distance x divided by the total number of pixels in the photograph 2ht Zz py ZE ana G rr rr OY 2h tan Hy ry ry oO This agrees approximately with the values generated by PhotoScan in doing the photogrammetric reconstruction discussed in Sections 4 1 2 and 4 2 3 3 2 Ensuring sufficient photo overlap Agisoft states in the PhotoScan User Manual that 80 overlap is needed for standard front overlap between successive photos Thus one can calculate the speed one needs to travel at to ensure that if one takes photos every five seconds the overlap is at least 80 The distance between the photo locations illustrated in Figure is then given by ding 2htan 2 overlap 8 2h tan 2hw tan 9 2htan 2 Mw 10 Where dint is the required maximum distance between the photos needed to ensure an overlap of w where the vertical angle of view is a and the photographs 10PhotoScan 1 0
11. CPs d The locations of the placed GCPs Figure 9 The data produced by PhotoScan from the Long Ashton aerial im agery with 3 GCPs input 11 Without GCPs With GCPs Flying Altitude m 4 88261 37 1183 Ground Resolution m pix 0 000940159 0 00622731 Error pix 0 971366 1 37699 DEM Resolution m pix 0 00376064 0 0249093 Table 1 The data generated by PhotoScan for the Long Ashton models with and without GCPs the final model appear slanted but the flying altitude is incorrectly taken to be 4 9m Even with only 3 GCPs this altitude error is corrected when the GCPs are used to georeference the model as well as the geotagged photos This difference in calculated flying altitude also explains the better ground and DEM resolution for the model reconstructed without GCPs as opposed to the model reconstructed with the GCPs the factor by which the GCP ground and DEM resolution is better is approximately equal to the factor by which the GCP model flying altitude is higher taking the slight difference in error into account Having a higher flying altitude means each pixel corresponds to a larger distance The errors for both models are approximately equal at 1 pix with a slightly higher error for the model with GCPs This number represents the root means square reprojection error calculated over all features points detected on the photo Thus a possible source of the error is that without the GCPs the software in unaware of t
12. blique angle to the object being modelled namely the ground This amount to ensuring that the camera is facing down towards the ground This is illustrated in Figure 2 Facade Incorrect Facade Correct LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL Figure 2 The incorrect and correct method of taking photos useful for pho togrammetric modelling reproduced from the Agisoft PhotoScan User Manual Version 1 0 2 2 Masking Occasionally background or foreground items obstruct the view of the object that one wishes to model causing error In these cases the offending back or fore ground objects must be masked out This means that the photos are individually edited to indicate that part of the photo is not part of the object to be modelled and should be ignored by PhotoScan when reconstructing the model A commonly masked element of photographs in photogrammetry is the sky as is visually shown in Section 4 2 1 and Figure 10 Without masking the software attempts to integrate the sky into the object being modelled causing significant error 2 3 CHDK Scripts 2 3 1 Time Interval The method used predominantly for remote photography is to run a script which automatically takes photos after a regular interval specified by the user The Lua script for this can be found in Appendix A To ensure that the photos take at regular intervals we tested the actual time between photographs at different Shttp downloads agisoft ru pdf
13. can generated data for the Avon Gorge models with and without GCPs georeferenced the errors in the reprojection are fully realised and reported by PhotoScan meaning that the reported error is higher It s important to note that as before even the higher value of the error for the GCP georeferenced model which corresponds to a value in meters of 1 24cm is well within an acceptable range The fact that this value is also realistic indicates that the previously unrealistically small error in Section 4 1 2 was indeed a result of not having enough GCPs to properly georeference the model thereby resulting in PhotoScan not fully recognising the error present in the model 5 Conclusion In conclusion aerial photography can provide an accurate 3 dimensional pho togrammetric reconstruction of the topology of the ground and a useful cor responding DEM with an error on the scale of a few centimetres This is sufficiently accurate to be able to produce useful DEM for geological purposes Importantly this accuracy can only be achieved using both geotagged photos and Ground Control Points for the georeferencing Without the GCPs the models exhibit systematic error such as the tilts discussed in Sections 4 1 and AD 6 Future Projects The following are proposals for future research into this field e Assess the relative accuracy achieved by using the CAM geotagging method as opposed to the time interval CHDK script e Fur
14. d was a cross marked in with white tape whose location was approximated by referencing nearby features on Google Maps While this is not sufficiently accurate for a true georeference it suffices to demonstrate that the tilt is removed from the final model once the GCPs are introduced Figure 9b shows the DEM with these 3 GCPs introduced into the pho togrammetric alignment process Clearly the model is no longer considering on a slope as it was in Figure 8b However the previously vertical faces are now tilted themselves meaning that the wall of the warehouse is not vertically up but a tilted slope up to the roof We argue that this is an artefact of the small number of GCPs used trying to georeference the model If the minimum number of 10 GCPs or more were used then the software would correctly geo reference the model and the sloped walls would be corrected Section 4 2 2 and 4 2 3 discusses this further with reference to the Avon Gorge photo set which contained more than the required number of GCPs The data generated by PhotoScan displayed in Table 1 further illustrates the inefficacy of georeferencing with geotagged photos alone Not only does 10 12 8661 m a The generated orthophoto for the 257 Long Ashton data set with 3 GCPs b The generated DEM for the Long input Ashton data set with 3 GCPs input c The calculated photographic over lap achieved in the Long Ashton photo dataset with 3 G
15. eotag ging and must be measured so that it can be taken into account To quantify this we analysed the shutter lag of the Powershot IXUS132 we are using This involved taking a photo of a timer exactly on the second and noting the time shown in the photograph We calcu lated the shutter lag to be 90 3 32 0 ms excluding the autofocus lag and 341 140 3 ms including the autofocus lag As the camera is not set to autofocus using this method of remote photography the former value is taken as the value of interest As the GPS logs are made only at a frequency of 5 Hz or one every 200 ms the shutter lag is rounded to the nearest 200 ms and taken as zero 2 5 Ground Control Points To enhance the accuracy and precision of the reconstructions we employed Ground Control Points GCPs These are strategically placed markers the exact location of which are surveyed and subsequently input into PhotoScan Then in PhotoScan after the cameras are aligned inputting the GCPs as markers and giving their geolocation either preferably as WGS or possibly also as local coordinates allows one to optimise the alignment of the cameras producing a more accurate dense point cloud and therefore textured model Distinguishable points such as dark crosses are preferable as they are eas ier to pick out on photos when creating markers in PhotoScan and easier for PhotoScan to analyse and pick out the location of in each picture I particular crosses are
16. first pass a zenithal angle to the cliff face This is shown visually in Figures 10a and 10b In particular where the oblique angle causes the camera to be unable to see the top of the cliff and where the cliff meets the sky the model is erroneous For the former the model produces clear spikes in the model jutting from the face of the cliff For the latter the software includes the sky as an extension of the cliff Masking the sky out as described in Section 2 2 removes the latter problem to a limited extent but the former remains as shown in Figure 10c 4 2 2 Without GCPs When the first pass is taken with no GCPs input there are several important emergent features to note Firstly as Figure 11d shows the calculated locations of the cameras was very inaccurate with some errors extending beyond the model This is because the geolocation of the photos from the on board UAV GPS is simply not accurate enough to be the only method of georeferencing the GCPs are also needed in addition to the geotagged photo locations Secondly as Figure 11b shows the reconstruction has also incorrectly in terpreted the landscape as being on a tilt with the north of the gorge top of the image appearing higher than the south of the gorge bottom of the image The systematic sloping that these reconstructions seem to exhibit is a strange if irrelevant phenomenon so long as a sufficient number of GCPs are provided possibly caused by the camera being
17. he systematic error demonstrated by the sloped DEM When the GCPs are introduced the software realises that the systematic error is there and the value of the reprojection error is increased accordingly Even though the GCP georeferenced model has a slightly larger error it still cor responds to a very small distance of 0 155mm This value is too small to be a realistic value indicating that the GCPs have not sufficiently corrected the model to its true value for the error present in the model to be recognised and reported by PhotoScan This is supported by the comparison in Section 4 2 3 4 2 Avon Gorge This model was reconstructed from two passes of 87 and 61 photos As before the time interval with time offset techniques were used for taking photos and geotagging the photos respectively The photos were taken by attaching the camera to the quadcopter and tilting it by hand to attain horizontally oriented photographs of the cliff face that is the Avon Gorge The purpose of this was to give useful photos equivalent to aerial photogrammetry before the quadcopter was ready to fly 4 2 1 First Pass Versus Second Pass The first pass was taken facing the gorge horizontally on thereby fully repre senting an equivalent to aerial photogrammetry The second pass was at an 12 oblique angle facing upwards to capture the top of the gorge As expected the second pass at an oblique angle produced less accurate results than the
18. he time difference between camera and GPS is sufficient to determine the location of each of the photos Inputting the log photographs and time difference into MP MP automatically geotags the photos to be imported into PhotoScan In order to find this time difference a photograph of MP while connected directly by USB to the APM as illustrated in Figure 5 is taken As the UAV GPS time is displayed on the MP screen and the camera logs the time it takes the photograph comparing the exif time stamp to the GPS time recorded in the photo itself gives the time difference 2 4 2 CAM Dataflash Log Messages If using the UBASIC CHDK script given in Appendix B to allow APM to remotely trigger camera shooting then the GPS time location alti tude roll pitch and yaw are all logged by APM A line will appear in the dataflash log of the form CAM GPSTime GPSWeek Lat Lng Al Geotagging the photos using the CAM messages embedded in the dataflash logs is the more accurate method as there are no uncertainties introduced by the time logged by the Figure 5 A photograph taken of MP camera while connected directly to the APM giving the offset between the camera time and the UAV GPS time 2 4 3 Shutter Lag If using the CAM message method the lag between the instruction to shoot and the photograph being actu ally taken induced by shutter lag can cause systematic errors in the g
19. photoscan pro_1_0_0_en pdf input interval values The results illustrated in Figure 3 show that below 5 seconds the interval is unreliable We therefore used 5 seconds as the standard time interval between photos 2 3 2 Pulse Width Modulation Signal Although it is not used for this re search CHDK scripts can take advan tage of the get_usb_power function to take input from APM This utilises Pulse Width Modulation PWM whereby repeated short digital sig nals are interpreted as different volt ages due to their high frequency The APM autipilot send these PWM sig nals to the camera via a cable pic tured in Figure 4 where the cam era interprets them as different volt ages The CHDK script that inter prets these voltages written in UBA SIC is given in Appendix B Note that the Enable Remote parameter must be enabled un der Settings CHDK Settings Remote Parameters Using the time interval script is in general more practical than taking photos through the CHDK cable us ing PWM This is because the time interval method is as Isimple as strap ping the camera to the copter and set ting to photographing whereas when using the CHDK cable one needs to either set APM to take photos at every waypoint using MP which one cannot do when controlling the UAV manually or assign the cam era shoot functionality to a button on the radio control system in which case one needs to press this button every
20. ther investigate the possible applications of photogrammetry to differ ent areas of Earth Science 17 7 Appendices A Time Interval CHDK Script The script used to take pictures every 5 seconds is as follows mae title Intervalometer param a interval sec default a 5 param b number of photos default 1 repeat start get_tick_count shoot sleep a 1000 get_tick_count start b b 1 until b 0 This is adapted from the default interval lua script packaged with all versions of CHDK under the SCRIPTS directory Note that there are two pa rameters a is the time interval between successive photos in seconds which we set to 5 and b is the number of photos to take in total By default this is set to 1 meaning it will continue taking photos indefinitely however it can be useful to limit the number of photos 18 B Pulse Width Modulation CHDK Script The script used to control the camera functions remotely through the CHDK cable using PWM is shown below It is taken directly from the APM wiki page on CHDK camera control title 3DR Shooter rem author Brandon Basso 3D Robotics rem author Dave Mitchell dave zenoshrdlu com rem This script is based on the basic Gentled CHDK2 script rem It takes pictures and sets zooms to a few different levels param o Zoom extended default o 100 param i Zoom stowed default i 30 param s Zoom shoot default s 10 while 1 do k get_usb_power
21. tps sketchfab com models ad8a1d9f8c324eb592a9e4beabc5ab1le Avon Gorge Pass 2 Unmasked No GCPs https sketchfab com models 2a51ae61e6bd4157bca421ab9c0c6b9Ff Avon Gorge Pass 2 Masked No GCPs https sketchfab com models 6b531108db5040e297ada8d9912391b3 Avon Gorge Passes 1 and 2 Unmasked No GCPs https sketchfab com models a9bdb7de52f24a7c8b5138259620ec93 Avon Gorge Passes 1 and 2 Masked No GCPs https sketchfab com models 0240057c321a44cf9a8c468372675b39 Avon Gorge Pass 1 With GCPs https sketchfab com models f277a6c6f6984ed1ad804d1tafdaf35e3 21
22. y the use of Unmanned Aerial Vehicles UAV To this end the ArduPilot Mega APM autopilot on flight hardware and firmware is used Although a quadcopter is the focus of the re search data was also taken with a hexacopter dista nce to object 1 3 Software Used Camera ee ae 1 3 1 Mission Planner Position 1 Position 2 Position 3 Mission Planner was used to interact Figure 1 By taking photographs of an with and give commands to the APM object from different angles one can use autopilot In particular the survey trigonometry to calculate the distance grid option used to guide the UAV to that object in a regular grid pattern is useful for achieving successful photos for mod elling In addition Mission Planner is used to geotag the photos This is discussed in more detail in 2 4 http www ardupilot co uk 2nttp planner ardupilot com 1 3 2 Agisoft PhotoScan The Agisoft PhotoScan Professional Edition software software is used to per form the photogrammetric reconstruction The workflow is as follows Load Photos Firstly the photos are loaded in PhotoScan Load Camera Positions Then the camera geotagging data are loaded either through importing the photo exif metadata or through a separate comma separated value file Align Photos The camera positions are then used to refine the camera posi tion and build a sparse point cloud Place Ground Control Points Next a mesh is generated and the GCPs
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