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This study investigated forest changes over Jinhe town of Inner Mongolia among 2001, 2004, 2008, 2013 and 2015 by use of multi-temporal Landsat Thematic Mapper-5 (TM), Chinese high resolution satellite data, Gaofen-1 (GF-1) remote sensing and forest inventory data. Vegetation fractional coverage (VFC) was extracted by the dimidiate pixel model. Forest above-ground biomass (AGB) was estimated by k-nearest...
Forest vertical canopy cover (VCC) is an essential factor to be considered during forest resource inventory, sub-compartment division and thinning intensity. In order to monitor the forest canopy structure changes over the Greater Khingan, two temporal (2005 and 2010) forest VCC are derived by inverting the Li-Strahler geometric-optical model (GO) based on the extracted endmembers. The results show...
Forest is an important component of terrestrial ecosystems, so it is necessary to estimate the forest aboveground biomass (AGB) accurately in order to reduce the uncertainty of the carbon stock in forest ecosystem. In this study, a fast, efficient and automatic method has been proposed, called as Automatic KNN(AKNN). Using the Landsat 8 OLI data, airborne polmetric SAR (PolSAR) data, the AKNN has...
Air and space resiliency requires efficient and functioning avionics using a robust and scalable architecture. In satellite communication (SATCOM) networks, each satellite can be treated as a topological node, such that the overall constellation can be represented by a graph matrix (i.e., graph Laplacian or adjacency matrix), and the quality of service (QoS) of each inter-satellite link (ISL) captures...
This study explores retrieval of wall-to-wall forest above-ground biomass (AGB) over Jilin province in Northeast China, using the optimized non-parametric k-NN method, the 7th National Forest Inventory (NFI) data, and the remote sensing data: Landsat-TM/ETM+ images. For pixel-based validation, the estimated result was compared to the NFI data by leave-one-out process and R2 = 0.40 and RMSE = 54.29...
Large scale forest mapping and change detection plays a significant role in the study of global change, particularly in the research of carbon source and sink. This paper presents results from forest/non-forest classification using ENVISAT-ASAR data. Both pixel-based and object-based classification method were developed for ASAR HH/HV images acquired on a single date. For the object-based classification,...
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