Moso bamboo forest extraction and aboveground carbon storage estimation based on multi-source remotely sensed images

Using a combination of moso bamboo forest thematic maps derived from Landsat Thematic Mapper (TM) images, field inventory data, and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) images, moso bamboo forest was extracted using the matched filtering (MF) technique and its aboveground carbon storage (AGC) was then estimated. This study presents a feasible method for extracting large-scale moso bamboo forests and for estimating moso bamboo forest AGC based on low-spatial resolution MODIS images. The results showed that moso bamboo forests in the majority of counties can be accurately estimated between actual area and estimates, with an R 2 of 0.8453. The fitted accuracy of the AGC model was high (R 2 = 0.491). The prediction accuracy of the AGC model was also evaluated using validation samples collected from Lin'an City, with an R 2 and root mean square error prediction of 0.4778 and 3.06 Mg C ha−1, respectively. The AGC in the majority of counties or cities in Zhejiang Province was between 0 and 15 Mg C ha−1, and to a certain extent the predicted AGC estimates were close to observed ground truth data and representative of the study area.

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