Titlebook: Remote Sensing of Land Use and Land Cover in Mountain Region; A Comprehensive Stud Duo Chu Book 2020 Springer Nature Singapore Pte Ltd. 202

SEVER

Aboveground Biomass of Grassland,e effective to estimate grassland AGB in the study area with .. = 0.63 than EVI with .. = 0.50 and is an optimal regression model for AGB estimation. For green AGB estimation, the performance of NDVI (.. = 0.69) is also better than EVI (.. = 0.59). In the study area, AGB spatially presents decreases

破裂

Longitude

Study Area,o as Tibet), is situated within the study area. The region has a long history of land resources development and utilization and the highest population density in TAR, which makes that the impact of human activities on regional environment is marked and extensive compared to other areas in the TP.

evasive

Ecoregion Classification,egion classification is implemented based on these indicators using principal component analysis (PCA) and artificial neural networks (ANN) techniques, and main results are presented. The chapter ends with conclusion and discussion.

MORPH

, in-situ observations, and various scientific methods.DemonThis book presents the spatial and temporal dynamics of land use and land cover in the central Tibetan Plateau during the last two decades, based on various types of satellite data, long-term field investigation and GIS techniques. Further,

思想流动

BYRE

Land-Use Status,water body (5.25%). Other land-use types account for less than 4%. Among these, cultivated land is 70021.72 ha., covering 2.37% of total land area, and is distributed in all counties except Damshung County in the north.

冷淡一切

Land-Use Change,er 26, 2007, through updating changes of main land-use types. Of which, based on the land-use status in 1990, 1995, 2000, and 2007, the spatial and temporal land-use change and dynamics in the Lhasa area located at central Tibetan Plateau from 1990 to 2007 are analyzed using GIS spatial analysis techniques in this chapter.

FOR

Land-Cover Change,.01) than temperature (. = 0.63, . < 0.01) in this semiarid climate zone. The study also indicated that DFT is a very useful tool to understand vegetation phenologies and dynamic change through decomposition of temporal data to frequency domain.

SSRIS