Paper Info
Title
Spatiotemporal analysis of land use/cover changes in Nanchang area, China.
Abstract
Based on remote sensing and Geographic Information System techniques, multi-temporal Landsat data were used to monitor land use/cover changes (LUCC) in the Nanchang area during 1989-2010. Quantitative and spatiotemporal indicators derived from the transition matrix for overall changes, intensity analysis for inter-category transitions, and spatiotemporal analysis of intra-category variations were constructed to analyze the spatiotemporal LUCC evolution. The study results show that urban and industrial land rapidly and continually expanded. The spatial extent of rural settlements shrunk while their distribution density increased. Cultivated land showed a tendency of spatially continuous loss and fragmented distribution, whereas the spatial pattern of forest tended to concentrate. The extents of ponds and reservoirs remained stable, but spatial changes were obvious. Rivers and bottomlands decreased significantly and tended toward fragmentation. The overall LUCC pattern showed that construction land rapidly sprawled while cultivated land decreased substantially, indicating an accelerating stage of urbanization and industrialization. Although rigid land requirements for urbanization had to be satisfied, land development and consolidation across forests and water body areas, as well as adjustment of agricultural structure, laid the foundation for a transition toward intensive land use in the Nanchang area.
Year
DOI
Venue
2015
10.1080/17538947.2014.894145
INTERNATIONAL JOURNAL OF DIGITAL EARTH
Keywords
Field
DocType
Nanchang area,GIS,land use/cover change,Poyang Lake Ecological Economic Region,spatiotemporal pattern,remotely sensed data
Common spatial pattern,Geographic information system,China,Remote sensing,Fragmentation (computing),Rural settlement,Spatiotemporal Analysis,Geography,Spatiotemporal pattern,Land use
Journal
Volume
Issue
ISSN
8.0
4.0
1753-8947
Citations 
PageRank 
References 
2
0.46
5
Authors
2
Name
Order
Citations
PageRank
Yang Zhang1113.28
Bin Xu213323.23