Als seminar


Published on

  • Be the first to comment

Als seminar

  1. 1. Airborne Laser Scanning and its Applications Prof.Dr.S.Anbazhagan Centre for Geoinformatics & Planetary Studies Department of Geology Periyar University Salem
  2. 2.  About Airborne Laser Scanning Case study in parts of Elbe river basin Selected applications
  3. 3. What is Airborne Laser scanning?Airborne laser scanning (ALS) represents a new andindependent technology for the generation of highlyautomated digital terrain and surface models.ALS development goes back to the 1970’s and 1980’s,with an early NASA system and other attempts in USA and CanadaThe acronym ‘LASER’ stands for ‘Light Amplification bySimulated Emission of Radiation’LADAR – LAser Detection And RangingLIDAR – Light Detection And RangingALS is member of the LIDAR familyLIDAR includes terrestrial laser scanners, airborne laserScanners and even police speed detection equipment
  4. 4. ALS data and AccuracyLaser scanning systems furnish geometric results in terms ofdistance, position, altitude and coordinatesMeasuring rates 2KHz to 25KHz, go up to 80KHzSampling density on the ground range from about 1 point / 20Sqm area up to 20 points per sq m area.Vertical accuracy -0.15m & point spacing 1.5m with anaccuracy of 0.15 m
  5. 5. Airborne Laser Scanning (ALS) – Active SensingEfficient tool for generating accurate DTMs day or night, especially over large areas of featureless or densely covered terrain.All laser systems measure by some means the distance between the sensor and the illuminated spot on ground
  6. 6. A Typical ALS System Ranging Unit Scanner LaserControl monitoring Flight Footprintand recording units direction Swath WidthDGPS IMU
  7. 7. Components in ALS system A dual frequency GPS receiver mounted in the aircraft, positions the ALS unit, typically every 0.5 seconds An Inertial Measuring Unit (IMU) records orientation of the aircraft, 200 times/sec Laser distance measurement unit emits up to 50,000 discrete light beams/sec, records the travel time and calculates the distance to the ground
  8. 8. Laser rangingTwo ranging principles;The pulsed ranging principle involves by measuring the phase difference between the transmitted and the received signal back scattered from the object surface.The phase difference method applied with lasers that continuously emit light are called ‘ continuous wave’ (CW) lasers.
  9. 9. Time-of-flight rangingTransmittedamplitude R AT Transmitter Received amplitude Receiver AR tL Traveling Time
  10. 10. Range (distance between sensor and object) R = C t/2 C = velocity of light 300000 km/s t = traveling time of a light pulseRange resolution ∆R, in cm ∆R = C ∆t/2 ∆t = ns, resolution of time measurement t = ns, time between sending and receiving a pulse (or echo) 1 ns = 30 cm travel, then range = 15 cm (Baltsavias 1999)
  11. 11. Lasers and wavelengthAt present semiconductor diode laser and Nd: YAG lasers (neodymium-doped yttrium aluminum garnet; Nd:Y3Al5O12 ) pumped by semiconductor lasers are used in the ALS system.It covers optical band range 800 nm – 1600 nmMost sensitive detectors are available between 800 nm and 1000 nmFirst scanners were worked 900 nm. At this wavelength, powerfulpulsed semiconductor laser diodes were available on the market andon optimum system performance could be expected. However, at thiswavelength, eye safety is still concern.The TopoSys laser scanner operates at 1535 nm. At this wavelength,higher energy levels can be used without running the risk to hurt theeye.
  12. 12. Intensity of return laser ALS system intensity (or strength) of the return laser important White sand, most of the emitted beam will be reflected back to the aircraft Black bitumen road, much less of the beam will be reflected back
  13. 13. Backscattering properties of targetReflectivity of various materials for 900 nm wavelengths______________________________________________________________Material Reflectivity (%)______________________________________________________________Snow 80-90White masonry 85Limestone, clay up to 75Deciduous trees Typ.60Coniferous trees Typ.30Carbonate sand (dry) 57Carbonate sand (wet) 41Beach sand Typ.50Concrete, smooth 24Asphalt with pebbles 17Lava 8______________________________________________________________ (Wehr and Lohr, 1999)
  14. 14. Maximum Range vs. Target Reflectivity of LMS-Q280i Riegl web page
  15. 15. ALS and Atmospheric condition ALS best performance is achieved when the atmosphere is cool, dry and clear IR propagation is severely attenuated by water vapour, (rain, fog and/or humidity), CO2 Dust particles and smoke also reduce detection range Best result during night, worst during day with bright sunlight
  16. 16. Physical properties in Laser Scanning High power Short pulses High collimation Narrow optical spectrum (10 nm bandwidth) Narrow optical spectrum has an advantageous,because narrow optical interference filters can bemounted in the receiving path to suppress disturbingbackground radiation, caused by backscatteredsunlight.
  17. 17. Position and Orientation System (POS)The 3D position of a point on the earth surface can be computed, if the position and orientation (POS) of the laser system is known with respect to a coordinate system.Integrated POS consisting of DGPS and an Inertial Measurement Unit (IMU)Geocoding of laser scanner measurements requires an exact synchronization of all systems : IMU, DGPS and laser scanner dataTime synchronization of better than 10 µs in achieved operationally by this scheme Wehr and Lohr (1999)
  18. 18. Determination of laser pointsAfter a surveying flight, basically two data sets are available: the POS data and the laser ranges with the instantaneousscanning angles. Data visualization and manual editing is necessary in different stages of the processing chain.Major advancements have been achieved by improvement mainly of the post-processing software and less of the laser scanner hardware.Interpolated data can be further processed and analyzed by commercial software e.g. Scop, Microstation, EASI-PACE, and ARC/INFO.Currently, the processing time for a DTM computed from laser scanner data is typically three times the data acquisition time.
  19. 19. Processing steps in ALS data Typical processing steps for laser scanner data POS Data Ranges and Scan Calibration Data (DGPS, IMU) Angels and Mounting Parameters Laser Points X, Y, Z in WGS84 or Lat., Long., H in WGS84 Map Projection Sorting Filtering Rasterizing and Thinning Out
  20. 20. Case study Airborne laser scanning and high resolution satellite data for Geomorphicstudy in Elbe river valley, Germany (Anbazhagan et al 2005)
  21. 21. ObjectiveIntegration of high resolution satellite data with Airborne Laser Scanner (ALS) data to study the various geomorphic features in parts of Elbe river valley, Saxony, Germany.
  22. 22. Study area Elbebasin in parts of Sächische Schweiz National park zone is mostly covered by forest Airborne laser scanning data give more informations on terrain condition covered under dense forest and enable to interpret the different types of landforms
  23. 23. Data used Airborne Laser Scanning (ALS) data was obtained from TopScan GmbH, Germany The density of ALS cloud point is 1 point per 9 sq m area. The accuracy of height is in between ± 10.8 cm and ± 12.6cm IKONOS satellite data acquired on 1st August 2000 is used in the present study. The satellite data in digital format is obtained from Hansa Luftbild GmbH, Germany. The imagery covered 97 sq km area in parts of Sächsischen Schweiz region IKONOS satellite data comprises of panchromatic band (PAN) with 1m spatial resolution and four multi-spectral bands with 4m spatial resolution. Multi-spectral bands were merged with geometrically rectified PAN data (1m resolution). The output image has 1m spatial resolution with 8 bit format
  24. 24. Software usedThe laser point cloud data were processed with help of SCOP++ software developed by Institute of Photogrammetry and Remote sensing, Technical University, ViennaIKONOS satellite data & DEM,DSM, DGM done through Erdas imagine 8.7 image processing software
  25. 25. IKONOS-PAN
  28. 28. IKONOS_High pass filter
  29. 29. IKONOS_ Histogram equalisation
  30. 30. IKONOS-Elbe river valley
  31. 31. Digital Elevation Model generated from Laser point data, Elbe river valley
  32. 32. Digital Surface Model (DSM) derived from ALS data
  33. 33. ALS Digital Surface Model showing differentlandforms
  34. 34. Terrace surface and River Terraces in ALS DSM
  35. 35. IKONOS FCC superimposed over DSM data
  38. 38. ALS Digital Ground Model (DGM), Part of Elbe river basin
  39. 39. Airborne Laser Scanning data – Shaded relief, Elbe river basin
  40. 40. Geomorphology in parts of Elbe river basin (based on IKONOS and ALS data)
  42. 42. Digital Elevation ModelsDTM (Digital Terrain Model)DEM (Digital Elevation Model)DSM (Digital Surface Model)DCM (Digital Canopy Model)DGM (Digital Ground Model)DTM and DSM generation in urban areas, automated building extraction, generation of 3-D city models for urban planning, wireless telecommunication, microclimate models, propagation of noise and pollutantsHigh accuracy and very dense measurement applications e.g. flood mapping, DTM generation and volume calculation in open pit mines, road design and modeling
  43. 43. Disaster ManagementRapid mapping and damage assessment after natural disastere.g after hurricanes, earthquakes, landslides etc., NRSC has done ALS survey in Tsunami affected area
  44. 44. Mapping of CorridorsMapping corridors e.g. roads, railway tracks, pipelines, waterway landscapesMapping of electrical transmissions lines and towers including ground / tree clearanceDTM generation, especially in forested areas (in forest road and path planning, drainage, etc)
  45. 45. Urban City Modeling ALS data has become an important source for generating high quality 3D urban city modeling. 3D city model using high resolution IKONOS imagery and airborne laser scanning data (Tao and Yasuoka 2002). Digital Surface Models (DSM) acquired at different occasions to successfully detect the building changes (Murakani et al 1999).
  46. 46. Terrain Mapping Landscape modeling using integrated airborne multi- spectral and laser scanning data (Hill et al 2002). Generation of digital surface models and digital elevation models that can provide information on the geomorphology of the earth’s surface (Pereira and Wicherson 1999). Merging of high resolution satellite data and airborne laser scanning data provide information geomorphological features like cuesta, mesa, escarpments and river terraces (Anbazhagan et al 2005)
  47. 47. Forest Resource Mapping ALS technology can provide information about tree height, crown diameter, tree density, and biomass estimation. Vegetation height is a function of species composition, climate and site quality, and can be used for land cover classification. Forest structure and biophysical parameters, and digital elevation models for watershed delineation and water flows.
  48. 48. (A) The unprocessed lidar height surface (i.e., digital surface model, DSM),(B) elevation surface (i.e., digital terrain model, DTM), and(C) the estimated vegetation height surface (i.e., digital canopy model, DCM) resulting from the subtraction of the DTM (B) from the DSM (A). Clark et al 2004
  49. 49. Management of Fluvial zones Accurate and updated models of flood plains are critical for flood plain monitoring and disaster planning. Laser data used to generate hydrodynamic model. Such model is determine the effect of high water levels and of earth works, such as removal of sand in river areas (Pereira and Wicherson 1999). LIDAR and Photogrammetry data used for monitoring water elevation and volume changes in riparian resources within the Grand Canyon region (Davis et al 2002).
  50. 50. Coastal zone ManagementHighly dynamic coastal zone require constant updating of baseline survey data. ALS offers a cost effective method to do this on a routine basis.Mapping and monitoring of shore lines, beaches, tidal flats, dunes, and wetlands.Measurement of coastal areas, determination of coastal change and erosion
  52. 52. LIDAR points
  53. 53. DTM
  54. 54. DTM from LIDAR +aerophotgrammetric elements
  55. 55. HIGWAY ENGINEERINGPROJECTS The product generated by DSM, orthophotos mosaic and highway geometric project integration made possible a high quality visualization of highway project. This product can be used as much visualization element for customer project presentation as for public hearings.
  56. 56. Coastal Bathymetric studies Bathymetric layers operated same principle as the topographic lasers, but emit in two wavelength, usually 1064 nm and 532 nm. The infrared wavelength is reflected on the water surface, while the green one penetrates the water and reflected by bottom surface or other objects in the water. Laser data used for water depth measurement and monitor the submerged jetty and disposal areas.
  57. 57. ALS development 1995 LIDAR commercial operations 5 world wide 2001 75 organizations 60 sensor commercial 2002 120 organizations 75 sensors 2005 150 – 200 sensors Major commercial sensors N.America (50%), Europe (28%) 15% Asia- pacific mostly Japan Remote Sensing 9.1% annual growth rate Forecast 2006 – LIDAR, SAR, Hyperspectral data (Lohani and Flood, 2003)
  58. 58. ALS development$30 - $50 million per year for Lidar data acquisitiongrowth in the rate 20% - 40%30% private sector in USA , leading marketenergy utilities35% state/local government35% federal government
  59. 59. Conclusion Airborne Laser scanning data is an accurate, fast and versatile measurement technique, and open up new exciting area of application. Integration of airborne laser data and high resolution satellite data will give excellent information on landscape modeling Potential integration with imaging sensors is expected to put airborne data acquisition on a revolutionary level of system performance
  60. 60. ReferencesAbbott,R.H., Penny,M.F., 1975.Ackermann. F., 1999.Anbazhagan,S., Trommler.M., Csaplovics.E., 2005Cunningham,L.L., 1972.Davis.P.A., et al., 2002.Haala,N., Brenner,C., Anders,K.H., 1997.Hill.R.A., and Veitch.N., 2002Hill et al 2002. Irish.L.J, Lillycrop.W.J. 1999.Kushwaha.S.P.S., and Behera.M.D., 2002.Lohani.B., and Flood.M., 2004Maas, H.G., and Vosselman.G.,1999.Murakami et al (1999).Pereira.L.M.G, Weicherson.R.J.1999Tao.G., Yasuoka.Y.,Vosselman.G., Suveg.I., 2001Wehr.A., and Lohr.U., 1999.Wulder. M., Onge,B., Treitz.P., 2000.
  61. 61. Thank you