9 November 2004 Dynamic monitoring of land-use change in Loess Plateau using multi-temporal Landsat TM data
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Loess Plateau is a unique region in the world where the human activities are very intensive and the eco-environment is highly frangible. During the past two decades, the Land Use/Cover Change has been considered as one of the most important reasons for the eco-environment degeneration in Loess Plateau. In this paper, land use data in 1990, 1995 and 2000 were got based on the Landsat TM Remote Sensing images, and the 1km-grid land use change data of 1990-1995, 1995-2000 and 1990-2000 was made using the data management and spatial analysis techniques of ArcGIS 8.3 software. Furthermore, statistical tabular data of Grain for Green Project on county level in recent years were joined in the administrative regionalism spatial data. Based on all of these data, temporal-spatial characteristics of land use change in Loess Plateau were studied in detail, and its driving forces were discussed either. It turned out that land use change in different periods had very different characteristics. On the whole, from 1990 to 2000, farmland and built-up increased greatly, and forest, grassland, water body and unused land decreased remarkably. On the contrary, conversions from farmland and unused to forest or grassland has become the dominant land use change process since 2000. The regional social-economic development and the national macro-control policy have been the most important driving forces of land use change since 1990. Especially, from 2000 to now, the widely implemented Grain for Green Project, under which farming on fragile land gives way to forestation, has become and will remain the most radical and effective driving force to both the land use change and the regional eco-environment restoration.
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Xiyong Hou, Xiyong Hou, Jiyuan Liu, Jiyuan Liu, Zhiqiang Gao, Zhiqiang Gao, Dafang Zhuang, Dafang Zhuang, Xinfang Yu, Xinfang Yu, } "Dynamic monitoring of land-use change in Loess Plateau using multi-temporal Landsat TM data", Proc. SPIE 5544, Remote Sensing and Modeling of Ecosystems for Sustainability, (9 November 2004); doi: 10.1117/12.558876; https://doi.org/10.1117/12.558876

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