Agricultural drought is crucial in understanding the relationship to crop production functions which can be monitored using satellite remote sensors. The aim of this research is to combine temperature vegetation dryness index (TVDI) and normalized difference water index (NDWI) classifications for identifying drought areas in Chuping, Malaysia which has regularly recorded high temperatures. TVDI and NDWI are assessed using three images of the dry spell period in March for the years 2015, 2016 and 2017. NDWI value representing water content in vegetation decreases numerically to −0.39, −0.37 and −0.36 for the year 2015, 2016 and 2017. Normalized difference vegetation indices (NDVI) values representing vegetation health status in the given area for images of years 2015 to 2017 decreases significantly (p ≤ 0.05) from 0.50 to 0.35 respectively. Overall, TVDI in the Chuping area showed agricultural drought with an average value of 0.46. However, Kilang Gula Chuping area in Chuping showed a significant increase in dryness for all of the three years assessed with an average value of 0.70. When both TVDI and NDWI were assessed, significant clustering of spots in Chuping, Perlis for all the 3 years was identified where geographical local regressions of 0.84, 0.70 and 0.70 for the years 2015, 2016 and 2017 was determined. Furthermore, Moran’s I values revealed that the research area had a high I value of 0.63, 0.30 and 0.23 with respective Z scores of 17.80, 8.63 and 6.77 for the years 2015, 2016 and 2017, indicating that the cluster relationship is significant in the 95–99 percent confidence interval. Using both indices alone was sufficient to understand the drier spots of Chuping over 3 years. The findings of this research will be of interest to local agriculture authorities, like plantation and meteorology departments to understand drier areas in the state to evaluate water deficits severity and cloud seeding points during drought.

中文翻译：

---

利用 TVDI 和 NDWI 对马来西亚楚平农业干旱的严重程度进行分类

农业干旱对于了解与可使用卫星遥感器监测的作物生产功能的关系至关重要。本研究的目的是结合温度植被干度指数 (TVDI) 和归一化差异水指数 (NDWI) 分类，以识别马来西亚楚平经常记录高温的干旱地区。TVDI 和 NDWI 使用 2015、2016 和 2017 年 3 月干旱期的三幅图像进行评估。 代表植被含水量的 NDWI 值在 2015、2016 和 2017 年数值上分别下降至 -0.39、-0.37 和 -0.36 . 2015 年至 2017 年图像中代表给定区域植被健康状况的归一化差异植被指数 (NDVI) 值显着下降 ( p≤ 0.05) 分别从 0.50 到 0.35。总体来看，楚平地区的TVDI表现出农业干旱，平均值为0.46。然而，楚平的基朗古拉楚平地区的干燥度在所有评估的三年中均显着增加，平均值为 0.70。当评估 TVDI 和 NDWI 时，确定了所有 3 年玻璃市楚平的显着聚集点，其中 2015、2016 和 2017 年的地理局部回归分别为 0.84、0.70 和 0.70。此外，Moran's I值显示该研究区域具有较高的I2015、2016 和 2017 年的值分别为 0.63、0.30 和 0.23，Z 分数分别为 17.80、8.63 和 6.77，表明聚类关系在 95-99% 的置信区间内显着。单独使用这两个指数就足以了解楚平三年多来的干燥点。这项研究的结果将使当地农业部门（如种植园和气象部门）了解该州的干旱地区，以评估干旱期间缺水的严重程度和播云点。