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评估 SWIR 波段在探测农业作物胁迫中的作用:以印度卡纳塔克邦拉久尔区为例。

Assessing the role of SWIR band in detecting agricultural crop stress: a case study of Raichur district, Karnataka, India.

机构信息

Department of Geology, Central University of Karnataka, Kalaburagi, Karnataka, 585367, India.

出版信息

Environ Monit Assess. 2019 Jun 16;191(7):442. doi: 10.1007/s10661-019-7566-1.

Abstract

The potential consequence of global climatic change caused the rise in temperature and precipitation decline, the aftermath of which has led to phenomenon like drought. As the agriculture is mainly dependent on the timely availability of water, delayed arrival of rainfall or decrease in the intensity of precipitation highly affects the growth of crops. If such situation persists for a longer period, the soil moisture content will be exploited completely and maturity of the crop will be stunted, finally adversely affecting the annual crop yield. In the present study, the capability of shortwave-infrared (SWIR) channels in detecting the agricultural crop stress in Raichur district of Karnataka state, India, using spectral vegetation indices namely Global Vegetation Moisture Index (GVMI) and Normalized Multi-band Drought Index (NMDI) has been analyzed using multi-temporal MODIS data. The vegetation health analysis by utilizing both indices were carried out from year 2002 to 2012 for the Kharif season, and it was seen that the year 2002 suffered major agricultural drought where the lower GVMI and NMDI values were covering the majority of the crop areas and in the year 2010 agricultural crop production was observed to be good. The average values of GVMI and NMDI for the years 2002 and 2010 were plotted with the average NDVI values of all months of both years and the results revealed that NDVI values were in concurrence with both NMDI and GVMI.

摘要

全球气候变化导致气温上升和降水减少,这可能会引发干旱等现象。由于农业主要依赖于水资源的及时供应,降雨延迟或降水强度降低会严重影响作物的生长。如果这种情况持续较长时间,土壤中的水分含量将被完全耗尽,作物的成熟度将受到抑制,最终对农作物的年度产量产生不利影响。在本研究中,使用多时间 MODIS 数据,分析了印度卡纳塔克邦赖乔尔地区短波红外 (SWIR) 通道通过光谱植被指数(即全球植被水分指数 (GVMI) 和归一化多波段干旱指数 (NMDI))检测农业作物胁迫的能力。利用这两个指数对植被健康进行了分析,从 2002 年到 2012 年进行了 Kharif 季节的分析,结果表明 2002 年遭受了严重的农业干旱,较低的 GVMI 和 NMDI 值覆盖了大部分作物区,而 2010 年农业作物产量良好。绘制了 2002 年和 2010 年的 GVMI 和 NMDI 平均值与这两年所有月份的平均 NDVI 值的关系图,结果表明 NDVI 值与 NMDI 和 GVMI 一致。

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