estimating forest leaf area index using satellite images : comparison of k - nn based landsat - nFi lai with moDis - rsr based lai product for Finland
نویسنده
چکیده
Leaf area index (LAI) is a key variable for many ecological models, but it is typically not available from basic forest inventories. In this study, we (1) construct a high-resolution LAI map using k nearest-neighbor (k-NN) imputation based on National Forest Inventory data and Landsat 5 TM images (Landsat-NFI LAI), and (2) examine a moderate-resolution LAI map produced based on reduced simple ratio derived from MODIS reflectances (MODISRSR LAI). The maps cover all the forested areas in Finland. Country-level averages of Landsat-NFI and MODIS-RSR LAI were at same level, but several geographical and land-use related differences between them were detected. Difference was the largest in the lake district of Finland and in northern Finland, and it increased with decreasing share of forests and increasing share of deciduous trees. As MODIS-RSR LAI does not take into account the subpixel variation in land use, Landsat-NFI LAI was found to produce more reliable estimates.
منابع مشابه
Evaluation of the MODIS LAI algorithm at a coniferous forest site in Finland
Leaf area index (LAI) collected in a needle-leaf forest site near Ruokolahti, Finland, during a field campaign in June 14–21, 2000, was used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) LAI algorithm. The field LAI data was first related to 30-m resolution Enhanced Thermal Mapper Plus (ETM+) images using empirical methods to create a high-resolution LAI map. The analysis of...
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