当前位置:网站首页>Google Earth Engine(GEE)——长时间序列逐月VCI数据提取分析和面积计算(墨西哥为例)
Google Earth Engine(GEE)——长时间序列逐月VCI数据提取分析和面积计算(墨西哥为例)
2022-06-23 03:32:00 【此星光明2021年博客之星云计算Top3】
Kogan等提出的植被状态指数(vegeta-tion condition index,VCI)植被状况指数 (VCI) 将当前的 NDVI 与前几年同期观察到的值范围进行比较。VCI 以 % 表示,并提供了一个概览,其中观察值位于前几年的极值(最小值和最大值)之间。较低和较高的值分别表示不良和良好的植被状态条件。。与NDVI-样,VCI也可以通过NOAA卫星的AVHRR传感器获取,VCI对干旱敏感可以消除地理位置、生态系统对NDVI的影响,成为了大规模遥感干旱监测的理想数据,它的可靠性得到了大量数据的证明。

采用VCI作为干旱指标。VCI要用到近红外波段和红外波段的数值可以通过NOAA数据获得长时间序列的产品,消除或减弱由于地理位置、土壤条件、太阳高度等因素对ND-VI产生的影响,适合大面积的早情分析,在植被监测和干旱监测中有广泛的应用。

代码:
var admin2 = ee.FeatureCollection("FAO/GAUL_SIMPLIFIED_500m/2015/level2"),
table = ee.FeatureCollection("projects/essential-rider-326809/assets/mexico&边栏推荐
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