The study was conducted in the Rift Valley Basin in 2020–2022, with the objective of evaluating the newly developed techniques for irrigated area mapping of spatially large areas and assessing the current irrigated area in the basin. Methods used for irrigated area mapping are imagery analysis using the NDVI and EVI methods and land use classification. All results were verified with ground-truthing data using the sample locations selected. A 10 m × 10 m spatial resolution image derived from the European Space Agency Sentinel-2 satellite was used to create a time series spanning 2020, 2021, and 2022. Irrigated area maps from all three techniques were obtained and evaluated. Metric indicators were used to evaluate the performance of the irrigated area mapping techniques, the mean overall accuracy was 0.82, with a kappa coefficient of 0.76 and an F1-score of 0.86 with the highest and lowest overall accuracy observed in 2020 (0.86) and 2022 (0.76), respectively. Coefficient of determination was used to quantify the correlation of geospatial information and the multispectral remote sensing data analysis results maps agreed with irrigated area mapping with respect to ground truthing with R² mean value of 0.87 which suggests a strong agreement.

该研究于 2020-2022 年在东非大裂谷盆地进行，目的是评估新开发的大空间灌溉面积测绘技术，并评估该流域当前的灌溉面积。用于灌溉面积绘图的方法是使用 NDVI 和 EVI 方法进行图像分析以及土地利用分类。所有结果均使用所选样本位置的地面实况数据进行了验证。使用来自欧洲航天局 Sentinel-2 卫星的 10 m × 10 m 空间分辨率图像来创建跨越 2020 年、2021 年和 2022 年的时间序列。获得并评估了所有三种技术的灌溉面积地图。使用度量指标来评估灌溉面积绘图技术的性能，平均总体精度为 0.82，kappa 系数为 0.76，F1 得分为 0.86，其中观察到的最高和最低总体精度分别为 2020 年 (0.86) 和 2022 年（0.76），分别。使用确定系数来量化地理空间信息的相关性，多光谱遥感数据分析结果图与地面实况灌溉区制图一致，R ²平均值为0.87，表明非常一致。