NELDA: Monitoring and Validating the Distribution and Change in Land Cover across Northern Eurasia

Principal Investigator: Olga Krankina (Oregon State University)

UMd Co- Investigators: Ivan A. Csiszar and Guoqing Sun

University of Maryland, Department of Geography

Given the importance of Northern Eurasia for global ecosystem and climate processes, improved characterization of land cover and land-cover change in the region is a scientific priority. While multiple moderate and coarse-resolution land-cover products have been developed, their validation remains a challenge, particularly for boreal and temperate Northern Eurasia, where validation sites are sparse and several land-cover types are unique. The region is a locus for climate change, and there is mounting evidence of significant recent changes in vegetation patterns due to the shifting patterns of fire, timber harvest, insect outbreaks, melting permafrost, agricultural conversion and abandonment, and other types of disturbance and land-cover change. Coarse-resolution sensors such as MODIS can track many forms of vegetation change, and the MODIS record is now becoming long enough to support mapping of disturbance and recovery.

Northern Eurasia Land Dynamics Analysis (NELDA) project seeks to harness NASA remote sensing technology and local knowledge of land-cover conditions in order to validate and improve land cover / land-cover change products for Northern Eurasia. The project will establish a network of test sites across the region for analyzing land cover, land-cover change, and disturbance captured on time series of Landsat-resolution imagery.  The test sites will provide data for validation of coarse-resolution land-cover products and samples of important vegetation change and disturbance processes. We will use these samples to develop and test methods for continental mapping of vegetation disturbance; then integrate MODIS datasets (e.g., active fires, burned areas, NDVI time series, Vegetation Continuous Fields treecover changes, interannual land cover products) to produce a zero-order vegetation disturbance/change map for the period 2000-2006. Finally, we will produce a new, updated land cover map for Northern Eurasia based on MODIS data for circa 2005 at 500-m spatial resolution. By developing an improved training site data base, exploiting the high quality spectral-temporal information from MODIS, and integrating information from the GLC-2000 map directly into the classification process, we will produce the best possible map of land cover for the Northern Eurasia region.  This map will include a confidence layer, which provides a measure of the classification quality for each pixel. We will evaluate the achieved improvement in mapping accuracy at our independent set of test sites.

This work leverages off past and ongoing projects to develop tools, methods, data, and collaborations needed to better characterize land cover attributes and dynamics across the Northern Eurasia region. The project benefits from the participation of experts in key regions of Northern Eurasia and helps consolidate a regional network of test sites and researchers dedicated to monitoring land cover change.