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Photogrammetry 1.


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Photogrammetry 1.

  1. 1. What is photogrammetry? <ul><li>Photos – light Gramma – to draw Metron – to measure </li></ul><ul><ul><li>“ Photogrammetry is the technique of measuring objects from photographs” </li></ul></ul><ul><li>“ The art, science and technology of obtaining reliable spatial information about physical objects and the environment through the processes of recording, measuring and interpreting image data.” </li></ul><ul><li>Two distinct types of photogrammetry : </li></ul><ul><ul><li>Aerial / spaceborne photogrammetry </li></ul></ul><ul><ul><li>Close range photogrammetry </li></ul></ul><ul><li>Remember this : Photogrammetry is the metric interpretation of image data </li></ul>
  2. 2. Photogrammetry portrayed as systems approach. The input is usually referred to as data acquisition, the “black box&quot; involves photogrammetric procedures and instruments; the output comprises photogrammetric products.
  3. 4. What is photogrammetry? <ul><li>Topographic photogrammetry </li></ul><ul><li>Used for mapping Earth or planets </li></ul><ul><li>Imaging system is based on an aircraft or spacecraft </li></ul><ul><li>Target is the ground surface </li></ul><ul><li>Image data is processed to create new spatial information products </li></ul><ul><li>Close range photogrammetry </li></ul><ul><li>Used for industrial measurement </li></ul><ul><li>Imaging system is handheld </li></ul><ul><li>Target is the object being measured </li></ul><ul><li>Image data is processed to make precise measurements </li></ul>
  4. 5. What can photogrammetry do? <ul><li>The simple answer: make accurate 2D and 3D measurements </li></ul><ul><li>Information required: images and sensor (camera) parameters </li></ul><ul><li>Close range photogrammetry: 3D only </li></ul><ul><li>Topographic photogrammetry: 2D and 3D, depending on specific application </li></ul>Single photograph + Sensor parameters = 2D measurement Multiple photographs + Sensor parameters = 3D measurement
  5. 6. WHY PHOTOGRAMMETRY <ul><li>VERY PRECISE </li></ul><ul><li>TIME EFFECTIVE </li></ul><ul><li>COST EFFECTIVE </li></ul><ul><li>BASED ON WELL ESTABLISHED AND TESTED ALGORITHMS. </li></ul><ul><li>LESS MANUAL EFFORT </li></ul><ul><li>MORE GEOGRAPHIC FIDELITY </li></ul>
  6. 7. Cont…… <ul><li>Corrects all sorts of distortions. </li></ul><ul><li>provide a reasonable geometric modeling alternative when little is known about the geometric nature of the image data. </li></ul><ul><li>  provide an integrated solution for multiple images or photographs simultaneously </li></ul><ul><li>achieve a reasonable accuracy without a great number of GCPs </li></ul><ul><li>create a three-dimensional stereo model or to extract the elevation information </li></ul>
  7. 14. PHOTOGRAMMETRY – Functional Details
  8. 15. Types of photographs
  9. 16. Image Requirements <ul><li>A block should have at least one pair of images (Satellite or Photo) which overlap: </li></ul>Stereo Pair Overlap Region 60% Overlap
  10. 17. Overlap Between Runs Not essential but can help 30% overlap between runs or swaths Run #1 Run #2
  11. 18. Stereo Vision Left Right Matching correlation windows across scan lines Z ( x , y ) is depth at pixel ( x , y ) d ( x , y ) is disparity baseline depth
  12. 19. Cameras and Sensors <ul><ul><li>Pushbroom Sensors - data is collected along a scan line, each scan line has it's own perspective center. </li></ul></ul>Perspective Centers
  13. 20. Camera and Sensor Types <ul><li>Cameras </li></ul><ul><ul><li>Frame Camera </li></ul></ul><ul><ul><li>Digital Camera </li></ul></ul><ul><ul><li>Video Camera (Videography) </li></ul></ul><ul><ul><li>Non-Metric Camera (35m, Medium and Large Format Cameras) </li></ul></ul><ul><li>Pushbroom Sensors </li></ul><ul><ul><li>Generic </li></ul></ul><ul><ul><li>Spot </li></ul></ul><ul><ul><li>IRS-1C </li></ul></ul>
  14. 21. Stereo aerial photography
  15. 22. Photogrammetry and remote sensing <ul><li>Photogrammetry -> metric exploitation of imagery </li></ul><ul><li>R emote sensing -> thematic exploitation of imagery </li></ul><ul><li>SPOT (French RS satellite) broke down the barriers in the 1980’s and 1990’s with: </li></ul><ul><ul><li>digital linescanner </li></ul></ul><ul><ul><li>stereo imaging capability </li></ul></ul><ul><ul><li>high quality optics and orbital model </li></ul></ul><ul><ul><li> suitable for regional stereo mapping and remote sensing </li></ul></ul><ul><li>Ikonos and Quickbird (launched recently) provide high resolution stereo imagery  suitable for large scale mapping and remote sensing </li></ul><ul><li>Next step: digital aerial frame cameras </li></ul>
  16. 23. Digital Cameras   The image plane of a digital camera to be used to record spatial objects contains a two dimensional field of sensors. CCD sensors (Change Coupled Devices) predominate in digital photogrammetric cameras. Such cameras are known as CCD Cameras
  17. 24. Satellite topographic mapping <ul><li>Stereo data can be collected on same orbit, or different orbits (beware of changes) </li></ul><ul><li>Satellite may have to be rotated to point sensor correctly </li></ul><ul><li>Optimum base to height ratio is 0.6 to 1.0 </li></ul><ul><li>Atmospheric effects (refraction, optical thickness) become more significant at higher look angles </li></ul>Different orbits Same orbit
  18. 25. Stereo satellite imagery
  19. 26. SPOT <ul><li>1 panchromatic, 3 multispectral channels </li></ul><ul><li>Panchromatic pixel size of 10m </li></ul><ul><li>Multispectral pixel size of 20m </li></ul><ul><li>Good for relief mapping at 1:50000 </li></ul>
  20. 27. High resolution satellites <ul><li>Ikonos (SpaceImaging) </li></ul><ul><li>1m panchromatic and 4m multispectral imagery (NIR, R, G, B) </li></ul><ul><li>11 bit dynamic range </li></ul><ul><li>Camera specifications not available </li></ul><ul><li>Quickbird (Digital Globe) </li></ul><ul><li>0.61m panchromatic and 2.44m multispectral imagery (NIR, R, G, B) </li></ul><ul><li>11 bit dynamic range </li></ul><ul><li>Camera specifications available </li></ul>
  21. 28. BRANCHES OF PHOTOGRAMMETRY Analogue Photogrammetry - optical or mechanical instruments were used to reconstruct three-dimensional geometry from two overlapping photographs. The main product during this phase was topographic maps .
  22. 29. Analytical Photogrammetry <ul><li>The computer replaces some expensive optical and mechanical components. </li></ul><ul><li>The resulting devices were analog/digital hybrids. </li></ul><ul><li>Analytical aerotriangulation, analytical plotters, and orthophoto projectors were the main developments during this phase. </li></ul><ul><li>Outputs of analytical photogrammetry can be topographic maps, but can also be digital products, such as digital maps and DEMs </li></ul>
  23. 30. Digital Photogrammetry <ul><li>Digital photogrammetry is applied to digital images that are stored and processed on a computer. </li></ul><ul><li>Digital photogrammetry is sometimes called softcopy photogrammetry. </li></ul><ul><li>The output products are in digital form, such as digital maps, DEMs, and digital orthophotos saved on computer storage media. </li></ul>
  24. 31. <ul><ul><li>Single or pairs of digital images are loaded into a computer with image processing capabilities. </li></ul></ul><ul><ul><li>Images may be from satellite or airborne scanners, CCD cameras or are conventional photographs captured by a line scanner. </li></ul></ul><ul><ul><li>Images are either displayed on the screen for operator interpretation, enhanced by image processing or subjected to image correlation in order to form a digital elevation model (DEM) or extract details. </li></ul></ul>DIGITAL PHOTOGRAMMETRY
  25. 32. <ul><ul><li>Creating a 3-D model or map is a straight and linear process that includes several steps- </li></ul></ul><ul><ul><li>Sensor model defenition </li></ul></ul><ul><ul><li>Ground Control Point (GCP) measurement </li></ul></ul><ul><ul><li>Automated tie point collection </li></ul></ul><ul><ul><li>Block bundle adjustment (i.e. Aerial Triangulation) </li></ul></ul><ul><ul><li>Automated DEM extraction </li></ul></ul><ul><ul><li>Ortho-rectification </li></ul></ul><ul><ul><li>3-D feature collection and attribution </li></ul></ul>DIGITAL PHOTOGRAMMETRIC WORKFLOW
  26. 33. Applications of Photogrammetery <ul><li>Topographic mapping </li></ul><ul><li>Creation of value added products: </li></ul><ul><ul><li>Orthoimages </li></ul></ul><ul><ul><li>Digital Elevation Models </li></ul></ul><ul><ul><li>Virtual landscapes </li></ul></ul><ul><li>Nadir imagery is essential for mapping </li></ul><ul><li>Overlap and sidelap is required to give 3D information </li></ul>
  27. 34. Example products: maps
  28. 35. Example products: DTMs
  29. 36. Example products: Virtual landscapes
  30. 38. DTMs <ul><li>Sources of terrain models </li></ul><ul><ul><li>Stereo photogrammetry </li></ul></ul><ul><ul><li>Interferometric radar </li></ul></ul><ul><ul><li>Stereo radar </li></ul></ul><ul><ul><li>Laser scanning </li></ul></ul><ul><ul><li>Digitising maps </li></ul></ul>
  31. 39. Contour digitizing <ul><li>Digital terrain model – Digitizing contour maps </li></ul><ul><li>Two step procedure: click on the contours, then grid the data </li></ul><ul><li>Liable to error if the DEM spacing grid is too large </li></ul>
  32. 40. Contour digitizing
  33. 41. Contour map
  34. 42. Radar mapping from space <ul><li>Two methods of topographic mapping using synthetic aperture radar (SAR): </li></ul><ul><ul><li>Stereo imaging ( radargrammetry ) </li></ul></ul><ul><ul><li>Radar interferometry </li></ul></ul><ul><li>Advantages of Radargrammetry: </li></ul><ul><ul><li>24 hour imaging </li></ul></ul><ul><ul><li>Physics of the imaging process is well understood </li></ul></ul><ul><ul><li>Radar relief mapping at 1:50000 is possible </li></ul></ul><ul><li>Disadvantages of Radargrammetry : </li></ul><ul><ul><li>Radar images have significant geometric distortions </li></ul></ul><ul><ul><li>Shadow and layover caused by relief </li></ul></ul><ul><ul><li>Radiometric interpretation is difficult </li></ul></ul>
  35. 43. Radar mapping from space
  36. 44. Stereo radar imagery
  37. 45. DEM
  38. 46. Stereo photogrammetry
  39. 47. Airborne laser scanning <ul><li>Digital terrain model generation – airborne laser scanning </li></ul><ul><li>Laser pulse is emitted from the sensor – return journey time is measured, giving distance between sensor and target </li></ul><ul><li>Location of the sensor is determined by GPS </li></ul><ul><li>Therefore target can be located </li></ul><ul><li>Significant post processing is required: </li></ul><ul><ul><li>Data thinning </li></ul></ul><ul><ul><li>Gridding </li></ul></ul>
  40. 48. LIDAR data Horizontal resolution: 2m Vertical accuracy: ± 2cm
  41. 50. Modelling building and topological structures <ul><li>Two main approaches: </li></ul><ul><ul><li>Digital Elevation Models (DEMs) based on data sampled on a regular grid (lattice) </li></ul></ul><ul><ul><li>Triangular Irregular Networks (TINs) based on irregular sampled data and Delaunay triangulation </li></ul></ul>
  42. 51. DEMs and TINs DEM with sample points TIN based on same sample points
  43. 52. Advantages/disadvantages <ul><li>DEMs: </li></ul><ul><ul><li>accept data direct from digital altitude matrices </li></ul></ul><ul><ul><li>must be resampled if irregular data used </li></ul></ul><ul><ul><li>may miss complex topographic features </li></ul></ul><ul><ul><li>may include redundant data in low relief areas </li></ul></ul><ul><ul><li>less complex and CPU intensive </li></ul></ul><ul><li>TINs: </li></ul><ul><ul><li>accept randomly sampled data without resampling </li></ul></ul><ul><ul><li>accept linear features such as contours and breaklines (ridges and troughs) </li></ul></ul><ul><ul><li>accept point features (spot heights and peaks) </li></ul></ul><ul><ul><li>vary density of sample points according to terrain complexity </li></ul></ul>
  44. 53. DEM Hill shaded DEM Aspect Shaded Aspect Slope Slope draped on DEM DEM derived Variables
  45. 54. height slope aspect hillshading plan curvature Feature extraction DEM derived Variables
  46. 55. Hydrologic Modeling <ul><li>DEMs allows automated modeling of hydrology </li></ul><ul><li>Hydrologic modeling is a process that begins with a DEM </li></ul><ul><li>Types of models: flow direction, flow accumulation, watershed delineation, and flow length </li></ul>
  47. 56. Flow Direction <ul><li>Calculates flow direction for every cell in the GRID </li></ul><ul><li>Based on direction of steepest slope in local neighborhood </li></ul>1 2 4 8 16 32 64 128
  48. 57. Flow Accumulation <ul><li>Based on flow direction grid </li></ul><ul><li>Creates a grid of accumulated flow to each cell </li></ul><ul><li>Can be used to create a stream network </li></ul>
  49. 58. Flow Accumulation -> Streams <ul><li>Use a conditional statement to create a stream network from a flow accumulation grid </li></ul><ul><li>streams =con (flow > 100, 1) </li></ul>
  50. 59. Delineating Watersheds <ul><li>Determines the contributing area above a set of cells in a grid </li></ul><ul><li>Needs a flow direction grid and sources </li></ul>
  51. 60. Flowlength <ul><li>Calculates distance along a flow path for each cell </li></ul><ul><li>Goes either upstream (to the nearest ridge) or downstream (to the nearest sink or outlet) </li></ul><ul><li>Primary use is to determine the length of the longest flow path in a basin </li></ul>
  52. 61. Visibility Analysis <ul><li>Requires: </li></ul><ul><ul><li>DEM </li></ul></ul><ul><ul><li>Viewpoint/s </li></ul></ul><ul><li>What it tells you: </li></ul><ul><ul><li>Line of sight </li></ul></ul><ul><ul><li>Viewshed </li></ul></ul><ul><ul><li>Combined Viewshed </li></ul></ul><ul><ul><li>Cumulative Viewshed </li></ul></ul>Viewing point
  53. 62. Calculating an inter-visibility matrix Offset b Offset a v v v nv nv nv visible not visible without offset b with offset b