Citation:

Iiames, J., D Pilant, T E. Lewis, AND R. O. Congalton. ACCOUNTING FOR ERROR PROPAGATION IN THE DEVELOPMENT OF A LEAF AREA INDEX (LAI) REFERENCE MAP TO ASSESS THE MODIS LAI MODI5A LAI PRODUCT. Presented at TIES and the Spatial Accuracy Symposium, Portland, MN, June 28-July 1, 2004.

Impact/Purpose:

Our research objectives are to: (a) develop new methods using satellite remote sensor data for the rapid characterization of LC condition and change at regional to national scales; (b) evaluate the utility of the new NASA-EOS MODIS (Moderate Resolution Imaging Spectrometer) leaf area index (LAI) measurements for regional scale application with landscape process models (e.g., biogenic emissions and atmospheric deposition); (c) provide remote sensor derived measurement data to advance the development of the next generation of distributed landscape process-based models to provide a predictive modeling capability for important ecosystem processes (e.g., nutrients, sedimentation, pathogens, etc.); and (d) integrate in situ monitoring measurement networks with UAV and satellite based remote sensor data to provide a continuous environmental monitoring capability.

Description:

The ability to effectively use remotely sensed data for environmental spatial analysis is dependent on understanding the underlying procedures and associated variances attributed to the data processing and image analysis technique. Equally important, also, is understanding the error associated with the given reference data used to assess the accuracy of the image product. This paper details measurement variance accumulated in the development of a leaf area index (LAI) reference map used to assess the accuracy of the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD15A LAI 1000-m product in the southeastern United States.

MODIS LAI was compared with reference data derived from Landsat Enhanced Thematic Mapper (ETM+) during the 2002 field season in the Albemarle-Pamlico Basin in Virginia and North Carolina. Ground-based optical LAI estimates were correlated with various ETM+ derived vegetation indices (VI's) at a 30-m resolution pixel. These 30-m pixels were scaled up to the 1000-m MODIS LAI pixel resolution and averaged to give one LAI value. A detailed listing of error propagation for this reference data set includes uncertainty associated with: (1) two integrated optical LAI field estimating techniques (Tracing Radiation and Architecture of Canopies, TRAC instrument, and hemispherical photography), (2) choice of site-specific VI's, and (3) image-to-image registration.

Record Details: