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A comprehensive agricultural drought stress monitoring method integrating MODIS and weather data (A case study of Iowa)

机译:结合MODIS和天气数据的综合农业干旱胁迫监测方法(以爱荷华州为例)

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This article aims to propose a new method that detects the occurrence and severity of agricultural drought by evaluating and investigating vegetation performance of and drought stress upon croplands using remote sensing techniques combined with station based observations. It is based on the assumption that crops suffer from agricultural drought stress only when vegetation and water stresses exist at the same time. Merely using NDVI or VCI can hardly determine whether a vegetation stress is drought related, because a lower NDVI/VCI could mean that the crop land is suffering from vegetation stress due to many reasons - drought, flood, extreme temperature, wild fire, pesticides or lack of fertilizers, etc. In conclusion, this research is designed to combine visibleear-infrared/shortwave-infrared remote sensing approaches (namely, from MODIS products) for vegetation drought stress estimation, based on a pre-knowledge of the crop type per pixel, and to validate the estimated result with the observed temperature, precipitation, and soil moisture levels. The new approach is to provide more accurate result than a single vegetation index used alone.
机译:本文旨在提出一种新方法,该方法通过使用遥感技术与基于站点的观测相结合,通过评估和调查农田的植被表现和干旱胁迫,来检测农业干旱的发生和严重程度。它基于这样的假设,即只有在同时存在植被和水分胁迫的情况下,农作物才会遭受农业干旱胁迫。仅使用NDVI或VCI几乎无法确定植被压力是否与干旱有关,因为较低的NDVI / VCI可能意味着由于多种原因(干旱,洪水,极端温度,野火,农药或其他原因),耕地正遭受植被压力。总之,本研究旨在根据作物类型的预知,结合可见/近红外/短波红外遥感方法(即来自MODIS产品)来估算植被干旱胁迫。每个像素,并使用观察到的温度,降水量和土壤湿度来验证估计结果。与单独使用单个植被指数相比,新方法可提供更准确的结果。

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