Title :
Down scaling vegetation fraction by fusing multi-temporal MODIS and Landsat data
Author :
Jinying Wang ; Hongyan Wang ; Xiaosong Li
Author_Institution :
Sch. of Forestry, Northeast Forestry Univ., Harbin, China
Abstract :
Vegetation fraction is an important indicator of ecosystem change, a high spatial and temporal resolution vegetation fraction product was essential in many spatially distributed models. Recent developments of coarse resolution remote sensing (e.g. MODIS) provide the potential to estimate the vegetation fraction with a high temporal resolution. However, coarse resolution products usually provide insufficient spatial resolution to fully characterize the heterogeneity of vegetation fraction at the local scale. Successful downscaling of vegetation fraction to high spatial resolution would be indispensable for describing the vegetation fraction difference in regional studies. A new downscaling approach is developed by fusing multitemporal MODIS and Landsat TM data based on the assumption that a simple scale-invariant linear relationship exist between vegetation fraction and NDVI. Land cover map was incorporated for refining Landsat scale pixels to determine the transformation coefficients. The downscaled vegetation fraction was validated through the comparison with field measured vegetation fraction. The results shows that the new proposed downscaling method was effective, the accuracy of the result was significantly improved, while the vegetation type information was took into consideration.
Keywords :
ecology; land cover; radiometry; remote sensing; sensor fusion; vegetation mapping; Landsat scale pixel; NDVI; coarse resolution product; coarse resolution remote sensing development; downscaling approach; downscaling method; ecosystem change indicator; field measured vegetation fraction comparison; high spatial resolution vegetation fraction product; high temporal resolution vegetation fraction product; insufficient spatial resolution; land cover map; local scale; multitemporal LANDSAT data fusing; multitemporal Landsat TM data fusing; multitemporal MODIS data fusing; simple scale-invariant linear relationship assumption; spatially distributed model; transformation coefficient determination; vegetation fraction difference; vegetation fraction downscaling; vegetation fraction estimation; vegetation fraction heterogeneity full characterization; vegetation type information; Biological system modeling; Earth; MODIS; Remote sensing; Satellites; Spatial resolution; Vegetation mapping; Landsat; MODIS; downscale; multi-temporal; vegetation fraction;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
DOI :
10.1109/IGARSS.2014.6946534