Challenges in Photogrammetry and Remote Sensing

Transcription

1 Challenges in Photogrammetry and Remote Sensing Norbert Pfeifer Vienna University of Technology Institute of Photogrammetry and Remote Sensing I.P.F.

2 Statements Photogrammetry is finished Professor Rinner (bundle block formulation) 1960ies Remote Sensing has always been the method of the future Saying in Forest Science Old stuff, that never will work? 2

3 Economic Predictions Mapping Opportunities, Gewin, 2004: Nature 427(6972) 21st Century growth markets seen by US Bureau of Labour Nano-technology Bio-technology Geo-technology The economic value of the Dutch geo-information sector, Castelein et al., 2010: Int.J. Spatial Data Infrastructure Research Geo-Information sector is 0.25% of Dutch GDP 3

4 Obvious Demands Geoinformation for Disaster and Risk Management, Altan et al. (eds.), 2010: Presented at UNOOSA July

5 Obvious Demands Geoinformation for Disaster and Risk Management, Altan et al. (eds.), 2010: Presented at UNOOSA July, Climate Change and Adaptation Earth Observation Monitoring Remote Sensing 5

6 Obvious Demands Resources Forests is 25% of land mass Fauna-Flora-Habitat Directive Megacities, space consumption Cultural Heritage natura2000.eea.europa.eu Afghan Buddha Statues, TU Wien, Faculty of Architecture and Spatial Planning 6

7 to moving measurement platforms from single to multi-sensor systems to higher autonomy and automation to new fields of applications

8 Presentation outline the art and science of infering metric information from images Photogrammetry, Remote Sensing and their neighboring disciplines Challenges Sensors, Methods, and Applications

9 Photogrammetry Geo Geometry the Earth object-based area-based Germanisches Nationalmuseum Nürnberg 9

10 object based Photogrammetry Geo Geometry the Earth Photogrammetry area based Image object-based understanding area-based Physics Processes 10

11 from States to Processes 11

12 P & RS neighbor: Spatial Information Science Geo-data infrastructures (GDI) and ubiquituos geo-information Virtual Globes: NASA, Google, Microsoft, Navigation LBS Web 2.0 geodata mash-ups Omnipresent Geo-Data

13 Omnipresent Geo-data Geo-data infrastructures (GDI) and ubiquituos geo-information Virtual Globes: NASA, Google, Microsoft, Navigation LBS Web 2.0 geodata mash-ups Wiki mapping, collaborative mapping, crowd sourcing, interest driven update stream Free global Geo-data SRTM CBERS, open street map

14 Omnipresent Geo-data National GDI Commercial GDI Open-Source GDI Methods for collaboration not yet settled Academic contribution to Open Source GDI very little Free national Orthophotos, US-Lidar for the nation EuroSDR: Crowd sourcing for updating national databases

15 geo-referenced and geo-physical P&RS Mission geo-data and models for a sustainable development of the natural and cultural environment Where s the challenge? Exploit new sensor technology Increase automation in modeling Adopt new applications Strengthen Sensor Method Application feedback

16 New Sensors Vexcel Patent Vienna, July 4, SPOT, Microsoft, Leica, Riegl

17 Standard Imaging Sensors Texture sensors Digital aerial camera: digital workflow Digital semi-metric and consumer cameras Hi-Res/Med-Res RBGNir Satellite Imager (hardly large image blocks!) Radiometric and spectral sensors Multispectral Satellite Imager Airborne Imaging Spectroscopy Microwave/SAR Satellite Imager FLIR cameras Range sensors Aerial/Terrestrial Laser Scanner Active Triangulation Structured Light Leica, Specim, Optech, Minolta, SMOS

18 Sensors Developments Sensors combinations Radiometric exploitation of digital aerial cameras (EuroSDR-Test, FGI) Full Waveform Laser Scanning Multi-spectral Laser Scanning Time-of-Flight Cameras Single Lens Stepping Frame Terrestrial InSAR Antonov of Geokosmos: Optech, Z/I, Rollei u-blox GPS/Galileo chip xsens, MEMS IMU After Gordon Petrie

19 Challenges Tighter sensor integration physically Integrated processing of data streams e.g. of GNSS, INS, LiDAR, and imaging spectrometer Corresponding features, orientation Calibration: geometrically and geo-physically Understanding measurement processes Approach Tigther integration of physical and geometrical views Coupling of Orientation, calibration and primitive modeling

20 Improve Automation Photogrammetry: Remote Sensing: Lack of Automation Lack of Reliability / Transferability ,940,000 2 km 2 km Land SPOT Classification by Kressler, Kim, Steinocher 21

21 Improve Automation Photogrammetry: Remote Sensing: Lack of Automation Lack of Reliability / Transferability km Efficient represenation and retrieval of implicit and explicit knowledge and experience 2 148,940,000 km Land SPOT Classification by Kressler, Kim, Steinocher 22

22 Standardized Methods and Products Satellite image classifications Surface/terrain models, orthophotos, point clouds 3D city models (roof landscape, facades)

23 Challenges Modeling from different sources: time, scale, observable Reliability, correlated observations, quality control Represenation and retrieval of knowledge and experience Contradictory information Processing time Approach Exploit redundancy, compression Advance from empirical to geo-physical process models Exploit machine learning competence Difference: mirror left mirror right What is a house?

24 Different sources example Forest inventory data and airborne laser scanning Airborne and terrestrial point clouds W. Dorigo, M. Hollaus, W. Wagner, K. Schadauer: An application-oriented automated approach for co-registration of forest inventory and airborne laser scanning data; Int. J. of Remote Sensing, 31 (2010), 5; Doneus, Briese, Studnicka

25 New Applications Cartography, Urban Planning, GDI Industry, Cultural Heritage, Hydrology Quantification Processes Geography, Geomorphology, Geology Biology, Ecology, Forestry Simon Buckley, Norway biodiversity, hydraulic resistance, timber volume, channel erosion, dead ice, grain size distribution, Vienna, July 4, 2010 Beyond the ISPRS Centenary 26

26 Sensors Methods Applications Feedback Feed Forward Loops be scientifically sustainable by persistent development of methods 27

27 Loads of interesting work & research ahead Openness for applications & sensors essential Modeling of geo-physical (and geo-social!) processes Integration of geometry and physics 3D model global dynamic geo-physical etc. etc. model