Evaluation of the Performance of Remote Sensing-based Drought Indices for Agricultural Drought Characterization: The case of Tigray Region, Northern Ethiopia
| dc.contributor.advisor | Berhan, Gessesse (PhD) | |
| dc.contributor.author | Haregeweyen, Minas | |
| dc.date.accessioned | 2022-03-21T09:49:00Z | |
| dc.date.accessioned | 2023-11-28T13:46:16Z | |
| dc.date.available | 2022-03-21T09:49:00Z | |
| dc.date.available | 2023-11-28T13:46:16Z | |
| dc.date.issued | 2022-03 | |
| dc.description.abstract | The increasing drought severities and consequent devastating effects on agriculture in the Tigray Region needs better monitoring of drought. For this purpose, numerous remote sensing-based drought indices have been proposed. However, the performance of remote sensing-based drought indices varies among regions and sensor characteristics. In addition, their different assumptions and data input requirements make it necessary to evaluate their suitability for drought monitoring before they become operational in a specific region. Using Landsat and MODIS images in the Tigray Region, this study assesses and compares the efficacy of four remote sensing-based drought indices for agricultural drought characterization. Drought indices investigated in this study include temperature condition index (TCI), NDVI deviation (DevNDVI), vegetation condition index (VCI), and vegetation health index (VHI). The drought indices obtained from each satellite image were compared to crop yield data and a selected in-situ-based drought indicator (SPEI) to meet the study's goal. According to the results, the VHI outperformed other drought indices in both satellite images, having the best association with crop yieldand SPEI, followed by DevNDVI, then the VCI, and finally the TCI. In both satellite images, the VHI was found as a suitable index for agricultural drought characterization among the four indices analyzed. VHI is followed by DevNDVI, VCI, and TCI. Furthermore, as compared to MODIS images with a coarser geographical resolution, all drought indicators produced from Landsat data with a medium spatial resolution show a stronger connection with crop yield and SPEI. As a result, Landsat data is a useful satellite image for describing agricultural dryness in the research region, and VHI is the appropriate drought index. Accordingly, the agricultural drought situation in the research region throughout the study period was analyzed. According to the findings, drought affected most of the research areas in the years 2000, 2011, 2012, 2015, and 2016. However, during 2006, 2013, and 2018, the study region had near-normal and normal vegetation conditions. Hence, agricultural drought characterization and mapping can be used to guide decision-making processes in drought monitoring and to reduce the adverse effects of the drought on agriculture and the economy. | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/12345678/30728 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | Agriculture | en_US |
| dc.subject | drought indices | en_US |
| dc.subject | drought monitoring | en_US |
| dc.subject | Landsat | en_US |
| dc.subject | MODIS | en_US |
| dc.title | Evaluation of the Performance of Remote Sensing-based Drought Indices for Agricultural Drought Characterization: The case of Tigray Region, Northern Ethiopia | en_US |
| dc.type | Thesis | en_US |