Abstract：
This study authorizes processes and approaches using optical and microwave data to determine the availability of water in the study area at any given moment. This will aid in identifying the optimal time and location for irrigation to enhance crop growth. For this purpose, a set of spectral vegetation parameters (from Sentinel-2), soil moisture (from Sentinel-1), evapotranspiration, and surface temperature (from Landsat-8) were used, along with field data on water content and irrigation timing. The results showed that both NDVI and NDMI are highly sensitive to moisture, making them the best indices for determining the timing and location of irrigation. This research contributes to sustainable agricultural development. It has implications for farmers, policymakers, and researchers in optimizing irrigation schedules, developing policies for sustainable agriculture, and enhancing crop productivity while conserving water resources. This approach can be particularly useful in regions facing water scarcity, where the efficient use of water resources is crucial for sustainable agricultural development.
摘要：
本研究授权使用光学和微波数据的过程和方法来确定在任何给定时刻研究区域中的水的可用性。这将有助于确定灌溉的最佳时间和位置，以促进作物生长。为此,一组光谱植被参数（来自Sentinel-2），土壤湿度（来自Sentinel-1），蒸散,使用地表温度(来自Landsat-8)，以及含水量和灌溉时间的现场数据。结果表明,NDVI和Ndmi均对水分高度敏感,使它们成为确定灌溉时间和位置的最佳指标。这项研究有助于农业可持续发展。这对农民有影响，政策制定者，和研究人员优化灌溉时间表，制定可持续农业政策，在保护水资源的同时提高作物生产力。这种方法在面临缺水的地区特别有用，水资源的有效利用对可持续农业发展至关重要。
