1. ASPRS Digital Imagery Guideline Update Fall 2007

2. 2 Status ASPRS Digital Imagery Guideline is being updated with new image chips NASA SSC contractor funded through DHS University of Mississippi led grant for Hurricane Decision Support Tool Development –Building off ASPRS Digital Imagery Guideline concept to develop a process for defining and developing products Web Based Decision Support Tool that generates prototype specification Uses image chips to help select product resolution and type Developing automated spatial resolution assessment Coordinating with USGS and others Looking for high resolution Digital Imagery Donation –2-30 cm GSD –Pan, RGB, CIR Planning to present results at Spring ASPRS meeting

3. Background

4. 4 Digital Imagery Guidelines Goals Build Imagery Markets By: –Facilitating user purchasing –Improving communication between user/supplier –Promoting standards to improve market education level –Facilitating QA/QC Processes Promote Market-Driven Technology Innovation By: –Improving communication with supplier/manufacturer with common dialog –Bringing critical technical issues to surface

5. 5 Civil Government Mapping Environmental National/Global Security Insurance Transportation Utilities Telecommunications Agriculture Exploration & Mining Real Estate Forestry Entertainment/Media Other Image Gallery Image Product Requirements Geolocation NMAS FGDC NSSDA Spectral Panchromatic Color CIR Spatial GSD Edge Response Radiometry Cosmetic Relative Dynamic Range Legacy Data Bases Requirements Derived From User Needs

6. 6 Digital Imagery Request Form Type (Panchromatic, CIR, Color) GSD or Scale Geolocation Accuracy Collection Area Collection Constraints Post Processing Requirements Delivery Format (datum, compression, tiling) Request begins online at http://www.asd/image_gallery/default.htmhttp://www.asd/image_gallery/default.htm

7. 7 Image chips are produced from features from Emerge imagery of Lakeland, Florida Image Gallery

8. 8 Image Gallery Generation High spatial resolution imagery is systematically modified to produce a variety of image chips with varying image quality

9. 9 Example Simulated Image Chips Original 8 “ GSD 16 “ GSD 24 “ GSD 32 “ GSD

10. 10 Imagery Requirement Generation Process Market Segment Data Selection Intrinsic Verification & Validation Spatial Resolution, SNR, etc. Simulated Imagery Varying Spatial Resolution

11. Imagery Spatial Resolution Verification and Validation

12. 12 Spatial Resolution Most spatial resolution specifications are written in terms of MTF as a function of spatial frequency –Dominant parameter is typically MTF @ Nyquist frequency –Nyquist frequency depends on GSD Nyquist frequency = 1/(2*GSD) –MTF at Nyquist is a measure of aliasing –MTF measurements at Nyquist are difficult to estimate in-flight Edge Response is more intuitive –RER (Relative Edge Response) –Ringing

13. 13 Edge Response Point Spread Function xx * Edge Edge Response Slope ~ 1/  x Spatial Domain Steepness of edge response effects spatial resolution

14. 14 Relative Edge Response -2.5-2.0-1.5-0.500.51.01.52.02.5 -0.2 0 0.2 0.4 0.6 0.8 1 1.2 Ringing Overshoot Ringing Undershoot Region where mean slope is estimated Edge Response Pixels

15. 15 GSD 8 inch RER ~0.7 GSD 8 inch RER ~0.35 GSD 8 inch RER ~0.23GSD 8 inch RER ~ 0.17

16. 16 GSD 8 inch RER ~0.7 GSD 32 inch RER ~1.0 GSD 16 inch RER ~1.0 GSD 24 inch RER ~1.0

17. 17 Standard Method Spatial Resolution Method Verification and validation of spatial resolution is typically performed using specially designed edge targets –Deployable: Radiometric tarp edges –Permanent: Painted conrete edge targets These types of targets will not be available in the imagery to validate spatial resolution QuickBird Imagery Panchromatic Imagery Feb 17 2002 10 m 20 m 3.7 deg QuickBird Imagery Panchromatic Imagery Nov 14 2002 Concrete Edge Tarp Edge Concrete Edge

18. Urban Target Edge Response Determination

19. 19 Vicarious Spatial Resolution Estimation MTF edge response estimation without dedicated targets Exploit features in nominal imagery Developing automated process –Edge identification –Edge spread function construction –MTF calculation Required to properly generate array of products

20. 20 Vicarious Edge Response Matlab code being developed for automated edge detection and analysis algorithms using scene data Data points across the edge to estimate edge response Edge found with Sobel methodSimulated image with noise

21. 21 Vicarious Edge Targets Examples Natural edge targets from within the imagery will be used for the spatial resolution analysis Examples of probable edge targets that will be detectable using automated methods are shown below Building Shadows Rooflines Street center lines (pulse targets)

22. 22 Example Smoothed Edge Response A 

23. 23 Next Steps/Summary Acquire high resolution imagery out of archives Automated spatial resolution assessment and image generation –New tool for quickly estimating spatial resolution and producing image chips Release next generation ASPRS Digital Imagery Guideline in Spring

24. 24 Points of Contact Bob Ryan Stennis 228-688-1868/ reryan@nasa.govreryan@nasa.gov George Lee USGS 650-329-4255/ gylee@usgs.gov