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Land Cover Classification in Qinling Mountains in China, using Time-Series MODIS NDVI Data

机译:秦岭山区土地覆盖分类,使用时间系列Modis NDVI数据

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A new classification logic for land cover at regional scale is proposed. The critical features of this classification are that: it is based on spectrum (color) and primary attributes of plant-canopy structure, that are important to globe change modeling and can be measured in the field for validation or/and by remote sensing; according to the phonological difference among broadly defined vegetation, some typical land cover is easily distinguished by using the characteristics of land cover with the change of seasons; mixed land cover is differentiated by its constituent characteristics and influence on land surface processes. A first test of this logic for the middle Qinling Mountains in Shanxi Province, China is presented based on time-series MODIS 250 m NDVI imageries. Seven basic classes and eleven sub-classes were identified and mapped for the study area. The overall classification accuracy equals to 74.41% and overall kappa statistics 66.65%.
机译:提出了区域规模土地覆盖的新分类逻辑。该分类的关键特征是:它基于频谱(颜色)和植物冠层结构的主要属性,对全球变化建模很重要,并且可以在现场测量用于验证或/和遥感;根据广泛定义的植被之间的语音差异,通过使用季节的陆地覆盖的特点,一些典型的陆地覆盖物很容易区分;混合陆地覆盖物由其组成特征和对土地表面过程的影响来区分。这是山西省中秦岭逻辑的第一次考验,基于时间系列MODIS 250 M NDVI成像仪。识别七个基本类和十一子类别,并为研究区映射。整体分类准确性等于74.41%,总体κ统计量为66.65%。

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