Improving forest aboveground biomass estimation using seasonal Landsat NDVI time-series

• Published in: ISPRS journal of photogrammetry and remote sensing Vol. 102; pp. 222 - 231
• Main Authors: Zhu, Xiaolin, Liu, Desheng
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.04.2015
• Subjects: Aboveground biomass; Accuracy; autumn; Biomass; carbon footprint; Empirical analysis; Empirical model; Estimates; Forest inventory and analysis; Forests; Landsat; NDVI; normalized difference vegetation index; Ohio; remote sensing; Saturation; Seasonal time-series; Seasons; time series analysis; Ohio; Forest inventory and analysis; Seasonal time-series; NDVI; Empirical model; Landsat; Aboveground biomass

Spatially explicit knowledge of aboveground biomass (AGB) in large areas is important for accurate carbon accounting. Landsat data have been widely used to provide efficient and timely estimates of forest AGB because of their long archive and relatively high spatial resolution. Previous studies have...