Comparing MODIS Net Primary Production Estimates with Terrestrial National Forest Inventory Data in Austria
AbstractThe mission of this study is to compare Net Primary Productivity (NPP) estimates using (i) forest inventory data and (ii) spatio-temporally continuous MODIS (MODerate resolution Imaging Spectroradiometer) remote sensing data for Austria. While forest inventories assess the change in forest growth based on repeated individual tree measurements (DBH, height etc.), the MODIS NPP estimates are based on ecophysiological processes such as photosynthesis, respiration and carbon allocation. We obtained repeated national forest inventory data from Austria, calculated a “ground-based” NPP estimate and compared the results with “space-based” MODIS NPP estimates using different daily climate data. The MODIS NPP estimates using local Austrian climate data exhibited better compliance with the forest inventory driven NPP estimates than the MODIS NPP predictions using global climate data sets. Stand density plays a key role in addressing the differences between MODIS driven NPP estimates versus terrestrial driven inventory NPP estimates. After addressing stand density, both results are comparable across different scales. As forest management changes stand density, these findings suggest that management issues are important in understanding the observed discrepancies between MODIS and terrestrial NPP. View Full-Text
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Neumann, M.; Zhao, M.; Kindermann, G.; Hasenauer, H. Comparing MODIS Net Primary Production Estimates with Terrestrial National Forest Inventory Data in Austria. Remote Sens. 2015, 7, 3878-3906.
Neumann M, Zhao M, Kindermann G, Hasenauer H. Comparing MODIS Net Primary Production Estimates with Terrestrial National Forest Inventory Data in Austria. Remote Sensing. 2015; 7(4):3878-3906.Chicago/Turabian Style
Neumann, Mathias; Zhao, Maosheng; Kindermann, Georg; Hasenauer, Hubert. 2015. "Comparing MODIS Net Primary Production Estimates with Terrestrial National Forest Inventory Data in Austria." Remote Sens. 7, no. 4: 3878-3906.