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Current Aerial Mapping Sensor Test and Evaluation Activities and Results

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Digital Aerial Imaging Systems: Current Activities and Issues Current Aerial Mapping Sensor Test and Evaluation Activities and Results American Society for ... – PowerPoint PPT presentation

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Title: Current Aerial Mapping Sensor Test and Evaluation Activities and Results


1
Current Aerial Mapping Sensor Test and Evaluation
Activities and Results
  • American Society for Photogrammetry and Remote
    Sensing Annual Meeting
  • Baltimore, Maryland
  • March 2005

2
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
In Situ Methods
  • In-situ methodologies can account for and measure
    sources of error in an imaging system under
    operating conditions.
  • Geopositional Use checkpoints with known x, y,
    and z values
  • Spatial Ground Sample Distance
  • Spatial - Modulation Transfer Function (MTF).
    Estimate MTF via
  • Point Spread Function point targets
  • Line Spread Function pulse targets or edge
    targets
  • Radiometric
  • Absolute Radiometry
  • Relative Radiometry

4
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
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
Product Characterization Pros
  • 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
Product Characterization Cons
  • 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 into the product that does not originate
    with the imaging system

8
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
Geopositional
  • Use checkpoints to assess imagery
  • Geodetic Targets
  • Manhole Covers

10
Spatial
  • Use Edge Targets to evaluate Relative Edge
    Response (RER)

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
systems edge response because distance between
the points for which the differences are
calculated is equal to the GSD
11
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
Current Status
  • Seven evaluations completed
  • Applanix DSS 300 operated by Emerge
    Geopositional Only
  • Space Imaging Digital Airborne Imaging System
    operated by Space Imaging
  • Leica Geosytems ADS40 operated by EarthData
    International
  • IKONOS Satellite operated by Space Imaging
  • Zeiss/Intergraph Digital Mapping Camera operated
    by AERO-METRIC, Inc.
  • M7 Visual Intelligence AirReconV operated by M7
    Visual Intelligence Geopositional Only

13
Current Status (Continued)
  • Three evaluations pending
  • Leica Geosystems ADS40 operated by Northwest
    Geomatics
  • Zeiss/Intergraph Digital Mapping Camera operated
    by 3001, Ltd. (Draft report completed review
    and release pending)
  • Vexcel UltraCam-D operated by Sanborn
  • Interest from other sensor operators DeLorme
    Digital Aerial Solutions GeoVantage Horizons,
    Inc. Photo Science, Inc. Spectrum Mapping and
    Titan

14
Results
    Product Product       Check    
Operator Sensor Type GSD (M) CE90 (M) CE95 (M) RMSENet (M) Points RER RER Band
Emerge Applanix DSS300 RGB 0.30 0.48 0.54 0.31 150 Saturated
Space Imaging DAIS RGB 0.50 0.73 0.83 0.48 150 0.85 Blue
0.76 Green
0.47 Red
0.74 Near IR
Space Imaging IKONOS PAN 1.00 2.28 2.53 1.65 41 0.75 Panchromatic
EarthData International Leica Geosystems ADS40 RGB 0.20 0.43 0.49 0.29 183 0.49 Panchromatic
0.39 Blue
0.55 Green
0.54 Red
0.62 Near IR
AERO-METRIC, Inc. Z/I DMC PAN 0.15 0.27 0.31 0.18 43 0.41 Panchromatic
M7 Visual Intelligence AirReconV RGB 0.25 0.64 0.72 0.43 45 Saturated
RGB 0.50 1.11 1.20 0.66 45 Saturated
BOLD Empirical CE Calculation Empirical CE Calculation Empirical CE Calculation
15
USGS Specifications for Orthoimagery
RMSE and CE values are in meters
  • Specifications sources
  • 1.00M USGS Orthoimagery Standards
  • 0.50M, 0.25M, 0.15M ASPRS Large Scale Mapping
    Guidelines
  • 0.30M Product Specifications for High
    Resolution Urban Area Imagery for NGA

16
Results-Specifications Comparison
Operator Sensor GSD (m) GSD (ft) CE90 CE95
    0.15 0.50 1.31 1.49
AERO-METRIC, Inc. DMC 0.15   0.27 0.31
           
    0.25 0.80 2.62 2.99
M7 Visual Intelligence AirReconV 0.25   0.64 0.72
EarthData International ADS40 0.20   0.43 0.49
           
    0.30 1.00 4.55 5.19
Emerge DSS300 0.30   0.48 0.54
           
    0.50 1.64 7.62 8.69
M7 Visual Intelligence AirReconV 0.50   1.11 1.20
Space Imaging DAIS 0.50   0.73 0.83
           
    1.00 3.28 10.16 11.59
Space Imaging IKONOS 1.00   2.28 2.53
17
Issues
  • Diversity Operator capabilities and products
    vary it is hard to make a meaningful comparison
    of one operators product to another
  • Variety of GSDs six-inch to one meter
  • Variety of image types panchromatic, natural
    color, CIR.
  • Variety of elevation data sources USGS DEMs,
    LiDAR, ISTAR, image autocorrelation
  • Relative Edge Response
  • Estimate sensitive to image re-sampling and image
    saturation
  • What is the significance of the RER value?
  • Radiometry
  • No evaluations of radiometry for airborne systems
  • Difficult to arrange due to high cost and level
    of coordination.
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