首页|Analysis of Land Use/Cover Change and Landscape Patterns Based on Remote Sensing
Analysis of Land Use/Cover Change and Landscape Patterns Based on Remote Sensing
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Remote sensing technology enables the observation of terrestrial features on the Earth's surface at specific time intervals and over particular swaths， facilitating the analysis of land use/cover changes and landscape patterns in a study area over time， thereby enhancing planning and utilization。 In this study， we calculated the area， dynamic degree， and land use transition matrix for different land use types in the Yunzhou District of Datong City， and discovered the following: the rate of change in the area of construction residential land and forest land in the Yunzhou District of Datong City is significant。 The area of construction residential land has gradually increased， exhibiting a trend of continuous outward expansion， with all increases being a result of the conversion from cultivated land。 The river surface of the Sanggan River is continually shrinking， with cultivated land year by year engulfing riparian wetlands。 From the perspective of the landscape pattern index， the class area (CA) is highest for forest land， indicating that forest land has a higher degree of fragmentation。 Special land uses (landscape， cultural and historical sites) are also more dispersed。 The largest patch index (LPI) is highest for cultivated land， indicating that cultivated land is the dominant land use matrix type in the study area， with a high degree of dominance and concentrated distribution。 In addition， the landscape shape index (LSI) is highest for forest land， making its shape and distribution the most complex。
Remote sensing imageryland use/land cover changelandscape pattern indices
Xiaoyu Bian、Jiaxin Wu、William
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State Key Laboratory of Surveying, Mapping and Remote Sensing Information Engineering, Ministry of Information, Wuhan University, No. 129, Luoyu Road, Hongshan District, Wuhan City, Hubei Province, China
35 Qinghua East Road, Haidian District, Beijing Forestry University, Beijing, China
Central South University of Forestry and Technology, No. 498 Shaoshan South Road, Changsha City, Hunan Province, China
International Conference on Environmental Remote Sensing and Geographic Information Technology
Xi'an(CN)
Second International Conference on Environmental Remote Sensing and Geographic Information Technology
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