1. 1 U.S. Department of the Interior U.S. Geological Survey National Center for EROS Remote Sensing Technologies Group Digital Aerial Imaging Systems: Current Activities and Issues American Society for Photogrammetry and Remote Sensing Annual Meeting, Baltimore, Maryland 09 March 2005

2. 2 U.S. Department of the Interior U.S. Geological Survey Why Laboratory Calibration Is Not The Answer For Digital Aerial Systems Diverse architectures Integration of cameras with other systems such as IMU and airborne-GPS equipment Integration with software processes The government can neither build a single instrument to calibrate all systems nor build multiple instruments to cover every possible architecture.

3. 3 U.S. Department of the Interior U.S. Geological Survey In Situ Methods In situ methodologies can account for and measure sources of error in an imaging system. Geopositional – Use checkpoints with known x, y, and z values Spatial – Ground Sample Distance and Modulation Transfer Function (MTF). Estimate MTF via: Point Spread Functions – point targets Line Spread Functions – pulse targets or edge targets Radiometric Absolute Radiometry Relative Radiometry

4. 4 U.S. Department of the Interior U.S. Geological Survey The Goals of the C2V2 Group Long-Term: Federal Civil Policies, Standards, and Guidelines for Digital Aerial Imaging Systems Short-Term: Remove the Barriers that Prevent the Use of Digital Aerial Imaging Systems

5. 5 U.S. Department of the Interior U.S. Geological Survey In the Interim… Product Characterization: Evaluate products and compare results to product specifications. An interim solution until policies, standards, and guidelines can be emplaced. Jointly conducted by USGS and NASA Operators submit orthoimagery of Stennis Space Center ‘Fee Area’ using Ground Sample Distances and elevation sources they would use to fill government contracts.

6. 6 U.S. Department of the Interior U.S. Geological Survey Product Characterization: Pro’s Straightforward implementation Product specification driven – not constrained by system architecture Each test increases experience with these systems and their datasets; the more we learn, the better our policies, standards, and guidelines will become

7. 7 U.S. Department of the Interior U.S. Geological Survey Product Characterization: Con’s Cost to both operators and government Voluntary participation ‘Benchmark’ type test is not an indicator of long-term or sustained performance. Orthoimage compilation process can introduce error to the product that does not originate with the imaging system.

8. 8 U.S. Department of the Interior U.S. Geological Survey Evaluation Components Geopositional – Compare measured coordinates of checkpoints in the orthoimagery to surveyed values. Spatial – Perform a Relative Edge Response analysis on imagery of edge targets. This is a technique that estimates the Line Spread Function of an imaging system. Radiometric – Deploy special tarps and other instruments.

9. 9 U.S. Department of the Interior U.S. Geological Survey Geopositional Use checkpoints to assess imagery Geodetic Targets Manhole Covers

10. 10 U.S. Department of the Interior U.S. Geological Survey Spatial Use Edge Targets to evaluate Relative Edge Response (RER) Image area selected for spatial response measurement in Northing direction The RER is a geometric mean of normalized edge response differences measured in two directions of image pixels (X and Y) at points distanced from the edge by -0.5 and 0.5 GSD. The RER estimates effective slope of the imaging system’s edge response because distance between the points for which the differences are calculated is equal to the GSD.

11. 11 U.S. Department of the Interior U.S. Geological Survey Radiometric Absolute correction: Correct radiance or reflectance should be measured or converted by using the sensor calibration data, the sun angle and view angle, atmospheric models and ground truth data. Relative Correction: Relative correction is to normalize multi- temporal data taken on different dates to a selected reference data at specific time. Typical techniques: Adjustment of average and standard deviation values. Conversion to normalized index: for example the normalized difference vegetation index (NDVI). Histogram matching: the histograms per band and/or per sensor are calculated and the cumulative histogram with cut-offs at 1% is determined, where y is reference data and x is data to be normalized.

12. 12 U.S. Department of the Interior U.S. Geological Survey Current Status Seven evaluations completed Applanix DSS 300 operated by Emerge (January 2003) – Geopositional Only Space Imaging Digital Airborne Imaging System operated by Space Imaging (November 2003) Leica Geosytems ADS40 operated by EarthData International (November 2002) IKONOS Satellite operated by Space Imaging (December 2003) Zeiss/Intergraph Digital Mapping Camera operated by AERO- METRIC, Inc. (February 2004) M7 Visual Intelligence AirRecon V operated by M7 Visual Intelligence (December 2004) – Geopositional Only

13. 13 U.S. Department of the Interior U.S. Geological Survey Current Status (Continued) Three evaluations pending Leica Geosystems ADS40 flown by Northwest Geomatics (October 2003) Zeiss/Intergraph Digital Mapping Camera operated by 3001, Ltd. (2004) Vexcel UltraCam-D operated by Sanborn (December 2004) Interest from other sensor operators: DeLorme; Digital Aerial Solutions; GeoVantage; Horizons, Inc.; Photo Science, Inc.; Spectrum Mapping; and Titan

14. 14 U.S. Department of the Interior U.S. Geological Survey Results Product Check OperatorSensorTypeGSD (M)CE 90 (M)CE 95 (M)RMSE Net (M)PointsRERRER Band EmergeApplanix DSS300RGB0.300.480.540.31150Saturated Space ImagingDAISRGB0.500.730.830.481500.85Blue 0.76Green 0.47Red 0.74Near IR Space ImagingIKONOSPAN1.002.282.531.65410.75Panchromatic EarthData Leica Geosystems ADS40RGB0.200.430.490.291830.49Panchromatic 0.39Blue 0.55Green 0.54Red 0.62Near IR AERO-METRIC, Inc.Z/I DMCPAN0.150.270.310.18430.41Panchromatic M7 Visual IntelligenceAirRecon VRGB0.250.640.720.4345Saturated RGB0.501.111.200.6645Saturated BOLD =Empirical CE Calculation

15. 15 U.S. Department of the Interior U.S. Geological Survey USGS Specifications for Orthoimagery *RMSE and CE values are in meters Specifications sources: 1.00M: USGS Orthoimagery Standards 0.50M, 0.25M, 0.15M: Large Scale Mapping Guidelines 0.30M: Product Specifications for High Resolution Urban Area Imagery for NGA Specifications sources: 1.00M: USGS Orthoimagery Standards 0.50M, 0.25M, 0.15M: Large Scale Mapping Guidelines 0.30M: Product Specifications for High Resolution Urban Area Imagery for NGA

16. 16 U.S. Department of the Interior U.S. Geological Survey Results-Specifications Comparison OperatorSensorGSD (m)GSD (ft)CE90CE95 0.150.501.311.49 AERO-METRIC, Inc.DMC0.15 0.270.31 0.250.802.622.99 M7 Visual IntelligenceAirRecon V0.25 0.640.72 EarthData InternationalADS400.20 0.430.49 0.301.004.555.19 EmergeDSS3000.30 0.480.54 0.501.647.628.69 M7 Visual IntelligenceAirRecon V0.50 1.111.20 Space ImagingDAIS0.50 0.730.83 1.003.2810.1611.59 Space ImagingIKONOS1.00 2.282.53

17. 17 U.S. Department of the Interior U.S. Geological Survey Issues Diversity: Operator capabilities and products vary; it is hard to make a meaningful comparison of one operator’s product to another. Variety of GSD’s: six-inch to one meter. Variety of image types: panchromatic, natural color, CIR. Variety of elevation data sources – USGS DEM’s, LiDAR, ISTAR, image autocorrelation Relative Edge Response Sensitivity: Vulnerable to image re-sampling and image saturation. Relevance: What is the significance of the RER value?