Kass Green

Assessing the accuracy of remotely sensed data : principles and practices

Introduction Why Accuracy Assessment? Overview Historical Review Aerial Photography Digital Assessments Data Collection Considerations Classification Scheme Statistical Considerations Data Distribution Randomness Spatial Autocorrelation Sample Size Sampling Scheme Sample Unit Reference Data Collection Basic Collection Forms Basic Analysis Techniques Non-Site Specific Assessments Site Specific Assessments Area Estimation/Correction Practicals Impact of Sample Design on Cost Recommendations for Collecting Reference Data ASources of Variation in Reference Data Photo Interpretation vs. Ground Visitation Interpreter Variability Observations vs. Measurements What is Correct? Labeling Map vs. Labeling the Reference Data Qualitative vs. Quantitative Analysis Local vs. Regional vs. Global Assessments Advanced Topics Beyond the Error Matrix Modifying the Error Matrix Fuzzy Set Theory Measuring Variability Complex Data Sets Change Detection Multi-Layer Assessments California Hardwood Rangeland Monitoring Project Case Study Balancing Statistical Validity with Practical Reality Bibliography

Comparison of DMC, UltraCam, and ADS40 Imagery for Benthic Habitat and Propeller Scar Mapping

This article compares the use of ADS40-52, DMC, and ULTRA-CAMD digital airborne camera imagery for mapping benthic habitat and identifying boat propeller scars in seagrass habitats. The three image data sets were collected over Redfish Bay, Texas on the same day, under almost identical environmental conditions. Next, the data sets were compared to each another using a variety of criteria. Finally, automated methods were used to create maps of propeller scars and the accuracy of each map was analyzed. Significant findings include • Digital airborne ADS40-52, DMC, and ULTRACAM imagery can be used to effectively map benthic habitat and propeller scars. • Imagery from the DMC and ADS40-52 had the highest spatial accuracy. • Spectral separatability of benthic habitat class and propeller scars is best in the DMC and the ADS40-52 imagery. • The accuracy of propeller scar maps was highest for maps produced from the ADS40-52 data.

Landsat in context : The land remote sensing business model

Earth remote sensing has long been considered essential to human endeavors. Beginning with military reconnaissance and evolving to weather, agriculture, environmental, and disaster monitoring, remote sensing broadens our view and provides context for our actions. While the provision of airborne remote sensing data is overwhelmingly a function of the commercial sector, space remote sensing remains predominately the purview of the public sector. Most attempts to commercialize space remote sensing have failed because there has not been a consumer base large enough to finance the enormous fixed costs of designing, building, launching, and operating space remote sensing systems. This paper reviews the business models for remote sensing with a particular emphasis on the Landsat program including its history and its political economy.