4.7 Article

Object-based mapping of the circumpolar taiga-tundra ecotone with MODIS tree cover

期刊

REMOTE SENSING OF ENVIRONMENT
卷 115, 期 12, 页码 3670-3680

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2011.09.006

关键词

Taiga-tundra ecotone; MODIS; VCF; CAVM; CAPI

资金

  1. NASA's Earth Science Division

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The circumpolar taiga-tundra ecotone was delineated using an image-segmentation-based mapping approach with multi-annual MODIS Vegetation Continuous Fields (VCF) tree cover data. Circumpolar tree canopy cover (TCC) throughout the ecotone was derived by averaging MODIS VCF data from 2000 to 2005 and adjusting the averaged values using linear equations relating MODIS TCC to Quickbird-derived tree cover estimates. The adjustment helped mitigate VCFs overestimation of tree cover in lightly forested regions. An image segmentation procedure was used to group pixels representing similar tree cover into polygonal features (segmentation objects) that form the map of the transition zone. Each polygon represents an area much larger than the 500 m MODIS pixel and characterizes the patterns of sparse forest patches on a regional scale. Those polygons near the boreal/tundra interface with either (1) mean adjusted TCC values from 5 to 20%, or (2) mean adjusted TCC values <5% but with a standard deviation >5% were used to identify the ecotone. Comparisons of the adjusted average tree cover data were made with (1) two existing tree line definitions aggregated for each 1 longitudinal interval in North America and Eurasia, (2) Landsat-derived Canadian proportion of forest cover for Canada, and (3) with canopy cover estimates extracted from airborne profiling lidar data that transected 1238 of the TCC polygons. The adjusted TCC from MODIS VCF shows, on average, <12% TCC for all but one regional zone at the intersection with independently delineated tree lines. Adjusted values track closely with Canadian proportion of forest cover data in areas of low tree cover. A comparison of the 1238 TCC polygons with profiling lidar measurements yielded an overall accuracy of 67.7%. Published by Elsevier Inc.

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