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Application research of MODIS data in monitoring land use change in Fujian

机译:MODIS数据在福建省土地利用变化监测中的应用研究。

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It was necessary and significant to explore the low-cost, high-precision and real-time access method of land-use/cover using the MODIS data multi-temporal and multi-spectral for quickly assess regional land use/cover change. Firstly, the study used maximum values compose (MVC) to select the optimal MODIS data in Fujian study area because there were mountainous landform and cloudy climatic condition in study area. Secondly, the characteristic variables of surface albedo, vegetation index(NDVI), water index(NDWI) and so on were combined, Moreover, the decision tree classifier system was established based on multi-factors composition for land cover/use classification in Fujian province. The results showed that the decision tree classifier was better than conventional maximum likelihood classifier, and was well applied the MODIS data to classify the land-use/cover of Fujian, because the decision tree classifier system took advantage of the MODIS multi-spectrum characters and artificial intelligence and could achieve a certain high precision, which made an important impact on monitoring land change and protecting arable land.
机译:为了快速评估区域土地利用/覆盖的变化,使用MODIS数据多时间和多光谱数据探索低成本,高精度和实时的土地利用/覆盖的访问方法是必要且重要的。首先,由于研究区存在山区地貌和多云的气候条件,本研究采用最大值组合法(MVC)选择了最优的MODIS数据。其次,结合地表反照率,植被指数(NDVI),水分指数(NDWI)等特征变量,建立了基于多因素组成的福建省土地覆盖/利用分类决策树分类器系统。 。结果表明,决策树分类器系统利用了MODIS的多谱特征和优势,使得决策树分类器优于传统的最大似然分类器,并且很好地应用了MODIS数据对福建省土地利用/覆被进行分类。人工智能并能达到一定的精度,这对监测土地变化和保护耕地产生了重要影响。

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