Indian Institute of Remote Sensing (ISRO), 4-Kalidas Road, Dehradun, 248001 Uttranchal, India.
Environ Monit Assess. 2012 Dec;184(12):7153-63. doi: 10.1007/s10661-011-2487-7. Epub 2011 Dec 27.
The most commonly used normalized difference vegetation index (NDVI) from remote sensing often fall short in real-time drought monitoring due to a lagged vegetation response to drought. Therefore, research recently emphasized on the use of combination of surface temperature and NDVI which provides vegetation and moisture conditions simultaneously. Since drought stress effects on agriculture are closely linked to actual evapotranspiration, we used a vegetation temperature condition index (VTCI) which is more closely related to crop water status and holds a key place in real-time drought monitoring and assessment. In this study, NDVI and land surface temperature (T (s)) from MODIS 8-day composite data during cloud-free period (September-October) were adopted to construct an NDVI-T (s) space, from which the VTCI was computed. The crop moisture index (based on estimates of potential evapotranspiration and soil moisture depletion) was calculated to represent soil moisture stress on weekly basis for 20 weather monitoring stations. Correlation and regression analysis were attempted to relate VTCI with crop moisture status and crop performance. VTCI was found to accurately access the degree and spatial extent of drought stress in all years (2000, 2002, and 2004). The temporal variation of VTCI also provides drought pattern changes over space and time. Results showed significant and positive relations between CMI (crop moisture index) and VTCI observed particularly during prominent drought periods which proved VTCI as an ideal index to monitor terminal drought at regional scale. VTCI had significant positive relationship with yield but weakly related to crop anomalies. Duration of terminal drought stress derived from VTCI has a significant negative relationship with yields of major grain and oilseeds crops, particularly, groundnut.
最常用的遥感归一化差异植被指数（NDVI）由于植被对干旱的响应滞后，往往无法实时监测干旱。因此，最近的研究强调了同时使用地表温度和 NDVI 的组合，这种组合可以同时提供植被和水分状况。由于干旱对农业的影响与实际蒸散量密切相关，我们使用了植被温度状况指数（VTCI），它与作物水分状况更密切相关，在实时干旱监测和评估中具有关键地位。在本研究中，采用 MODIS 8 天合成数据在无云期（9-10 月）的 NDVI 和地表温度（T（s））构建 NDVI-T（s）空间，从中计算 VTCI。作物水分指数（基于潜在蒸散量和土壤水分消耗的估计）每周计算一次，代表 20 个气象监测站的土壤水分胁迫情况。尝试进行了相关和回归分析，以将 VTCI 与作物水分状况和作物表现相关联。VTCI 准确地评估了所有年份（2000、2002 和 2004 年）的干旱胁迫程度和空间范围。VTCI 的时间变化也提供了干旱模式在空间和时间上的变化。结果表明，CMI（作物水分指数）与 VTCI 之间存在显著正相关关系，尤其是在显著干旱时期，这证明 VTCI 是监测区域尺度终端干旱的理想指标。VTCI 与产量呈显著正相关关系，但与作物异常的关系较弱。VTCI 得出的终端干旱胁迫持续时间与主要粮食和油料作物的产量呈显著负相关关系，尤其是花生。
