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Land Use/Land Cover Dynamic Monitoring and Analysis using Remote Sensing and GIS Techniques: Case Study of Qingpu District, Shanghai

机译:土地使用/陆地覆盖使用遥感和GIS技术的动态监测和分析:上海青浦区案例研究

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This paper illustrates almost twenty years (1986~2007) of Land use/land cover change (LULCC) in Qingpu-one district of Shanghai. Qingpu District is an area of Upper Huangpu Catchment for fresh water supply with considerable ecological value, but it is also experiencing urban sprawl from development. To reveal the trends underlie LULCC, we propose a novel procedure to quantify different land use/land covers and implement it in the case study. In this procedure, we first collect historical remote-sensing data and co-registered or corrected them to the same spatial resolution and radioactive level. Based upon preliminary interpretation or investigation, land use/land cover types in study area can be included in 5 categories, i.e. Water, Agricultural Land, Urban or Built-up Land, Forest Land, and Barren Land or others. Moreover, data is clipped via boundary of study area for reducing computation load, followed by FPCR-ISODATA classification to divide the data into k groups (k>the number of land types). After postprocessing, e.g., merge the same connoted subgroups and correct misclassified units accompany with validation and verification, the detailed land use/land cover results can be achieved accurately. The quantitative and regression analysis indicate that during the past twenty years the area of agricultural land of Qingpu decreased coupled with urban or built-up area increased linearly. The water area had the minimum change during the decades. Forests had the smallest average proportion (9.6%) of the total area. It occupied so small proportion of land that we can only find points of it in the maps. Barren land can be an indicator for monitoring uncompleted redevelopment or transition of land.
机译:本文用上海青浦区近二十年(1986〜2007年)的土地使用/土地覆盖变化(LULCC)。青浦区是鲜水供应的上黄埔集水区,具有相当大的生态价值,但它也在经历城市蔓延。为了揭示LULCC的趋势,我们提出了一种新的程序来量化不同的土地使用/陆地涵盖并在案例研究中实施。在此过程中,我们首先收集历史遥感数据并共同登记或将它们校正到相同的空间分辨率和放射性水平。基于初步解释或调查,研究区域的土地使用/陆地覆盖类型可以包含在5个类别中,即水,农业用地,城市或建筑陆地,林地和贫瘠的土地或其他类别。此外,通过研究区域的边界剪裁数据来减少计算负荷,然后是FPCR-ISODATA分类来将数据划分为K组(k>土地类型的数量)。在后处理后,例如,合并相同的内涵亚组和伴随验证和验证的正确错误分类单位,可以准确地实现详细的土地使用/陆地覆盖结果。定量和回归分析表明,在过去的二十年中,青浦农业地区与城市或建筑面积相连,线性增加。水域在几十年中有最小的变化。森林的平均比例最小(9.6%)。它占据了这么少的土地,我们只能在地图中找到它的积分。贫瘠的土地可以是监测未完成的重建或土地过渡的指标。

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