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16 October 2009 Plantation change in Wuhan and its driving force analysis during 1978-2008
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Proceedings Volume 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining; 74924O (2009) https://doi.org/10.1117/12.837433
Event: International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, 2009, Wuhan, China
Abstract
This study is the purpose to detect effectively spatial-temporal change of plantation in Wuhan city and its driving force during 1978-2008. Firstly, according to study area, to acquire 4-phase remotely sensed images, Landsat MSS image of 1978, Landsat TM image of 1992, Landsat ETM image of 2002, HJ1b CCD image of 2008 and corresponding topography maps. Using remote sensing image processing software ERDAS to register, correct and resample these images. Applying to remotely sensed imagery classification method, to class images to urban built-up area, plantation, forest land and water body. Using map algebra arithmetic and spatial model to acquire plantation change map during the period of 1978~1992,1992~2002, 2002~2008 and 1978~2008. It reflects spatial distribution of plantation change. Attribute analysis can get quantities and change ratio of plantation. The result is shown that change of plantation area is divided to two phases. Plantation area decreases from 6560.73km2 to 4262.49km2 during 1978-2002, and increases by 904.59km2 after 2002. Viewing from spatial distribution, plantation area of central city zone decrease rapidly and is replaced by urban construction use land. In suburban, plantation partly transforms into forest land, water body and village inhabitancy, increases or decreases. The research finds out that main driving force of plantation change is urban built-up area increase and plantation policy.
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Wensheng Deng, Huanhuan Xiang, Changzuo Wang, Jianying Zhu, and Gang Chen "Plantation change in Wuhan and its driving force analysis during 1978-2008", Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74924O (16 October 2009); https://doi.org/10.1117/12.837433
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