Drought Monitoring Based on the Vegetation Temperature Condition Index by IDL Language Processing Method

Drought Monitoring Based on the Vegetation Temperature Condition Index by IDL Language Processing Method
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IDL语言处理方法基于植被温度状况指数的干旱监测

DOI:
10.1007/978-3-642-27275-2_5
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发表时间:
2011-10
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--
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其他
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Landsat TM5 图像用于计算和检索归一化植被指数 (NDVI) 和地表温度 (LST)。结合上述两个指标,可以反演植被温度状况指数(VTCI),作为黑龙江省军川农场干旱监测指标。 IDL语言良好的矩阵运算性能,可以在短时间内检索VTCI,快速进行批量计算和绘图工作,很大程度上节省了时间和人力,也为政府的宏观调控政策提供了实时数据。
Landsat TM5 images are used to calculate and retrieve normalized difference vegetation index (NDVI) and land surface temperature (LST). Combining with two index mentioned, vegetation temperature condition index (VTCI) can be retrieved for drought monitoring indicator applied in Junchuan farm of Heilongjiang Province in Northeast China. With well performance in matrix operation of IDL language, retrieving VTCI in a short time, fast batch calculation and mapping work as well, to a great extent, saving time and laborites, also providing real-time data for the government’s macroeconomic regulatory policy.
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