Analyzing agricultural drought using remote sensing indices in the east bale zone, southeastern Ethiopian lowlands

Q2 Environmental Science Environmental Challenges Pub Date : 2024-10-09 DOI:10.1016/j.envc.2024.101031
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Abstract

The practical applications of satellite data in comprehending the changing environment must take in account quantitative awareness of the uncertainty across different satellite products. However, prior drought research efforts in Ethiopia paid less attention to evaluating satellite products although drought has led to agricultural failures in the lowlands of Ethiopia. This study aimed to evaluate the spatial-temporal distribution of agricultural drought in the lowlands of the Bale zone throughout the crop growing season (March to May) from 2012 to 2022. The dataset utilized in this study was chosen by assessing the performance of enhanced MODerate resolution Imaging Spectroradiometer (eMODIS) and enhanced Visible Infrared Imaging Radiometer Suite (eVIIRS) Normalized difference vegetation index (NDVI) in comparison to observed gridded rainfall, employing the simple linear regression model. The assessment of agricultural drought was conducted using the NDVI anomaly and the vegetation condition index (VCI). The eMODIS exhibited a coefficient of determination of 0.45 with a p-value of 0.02, whereas the eVIIRS had a coefficient of determination of 0.47 with a p-value of 0.01. Thus, eVIIRS NDVI was selected as the best dataset for evaluating agricultural drought in the research site. The findings indicated that in both 2012 and 2022, there were periods of agricultural drought. During these periods, severe to extreme drought conditions were seen in 7.6 % to 54.98 % of the study area, encompassing both lowland and midland regions. The biggest influence was detected in the northern, middle, and southern regions of the research area. Severe and moderate drought dominated study area as depicted by NDVI anomaly while extreme and severe as seen from VCI. Whereas the years 2014 and 2020 were the wettest. The study implies that eVIIRS NDVI might be an alternate approach to give empirical information that would aid stakeholders in limiting the consequences of agricultural drought on farming activities.
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利用遥感指数分析埃塞俄比亚东南部低地东巴莱区的农业干旱情况
卫星数据在理解不断变化的环境方面的实际应用必须考虑到对不同卫星产品的不确定性的定量认识。然而,尽管干旱已导致埃塞俄比亚低地农业歉收,但埃塞俄比亚之前的干旱研究工作较少关注对卫星产品的评估。本研究旨在评估 2012 年至 2022 年整个作物生长季节(3 月至 5 月)巴莱州低地农业干旱的时空分布情况。本研究使用的数据集是通过评估增强型中分辨率成像分光仪(eMODIS)和增强型可见光红外成像辐射计套件(eVIIRS)归一化差异植被指数(NDVI)的性能与观测到的网格降雨量进行比较后选择的,并采用了简单线性回归模型。利用归一化差异植被指数异常和植被状况指数对农业干旱进行了评估。eMODIS 的决定系数为 0.45,p 值为 0.02,而 eVIIRS 的决定系数为 0.47,p 值为 0.01。因此,eVIIRS NDVI 被选为评估研究地点农业干旱的最佳数据集。研究结果表明,2012 年和 2022 年都出现了农业干旱期。在此期间,研究区域 7.6% 至 54.98% 的地区出现了严重至极端干旱,包括低地和中原地区。影响最大的是研究区的北部、中部和南部地区。从归一化差异植被指数(NDVI)异常中可以看出,严重和中度干旱在研究区域占主导地位,而从 VCI 中可以看出极端和严重干旱。而 2014 年和 2020 年是最湿润的年份。这项研究表明,eVIIRS NDVI 可能是提供经验信息的另一种方法,有助于利益相关者限制农业干旱对农业活动造成的影响。
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来源期刊
Environmental Challenges
Environmental Challenges Environmental Science-Environmental Engineering
CiteScore
8.00
自引率
0.00%
发文量
249
审稿时长
8 weeks
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