{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T02:13:32Z","timestamp":1771553612750,"version":"3.50.1"},"reference-count":73,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2023,11,6]],"date-time":"2023-11-06T00:00:00Z","timestamp":1699228800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The assessment of ecosystem quality and the maintenance of optimal ecosystem function require understanding vegetation area dynamics and their relationship with climate variables. This study aims to detect vegetation area changes downstream of the Hali dam, which was built in 2009, and to understand the influence of the dam as well as climatic variables on the region\u2019s vegetation areas from 2000 to 2020. The case study is located in an arid area with an average rainfall amount from 50 to 100 mm\/year. An analysis of seasonal changes in vegetation areas was conducted using the Normalized Difference Vegetation Index (NDVI), and supervised image classification was used to evaluate changes in vegetation areas using Landsat imagery. Pearson correlation and multivariate linear regression were used to assess the response of local vegetation areas to both hydrologic changes due to dam construction and climate variability. The NDVI analysis revealed a considerable vegetation decline after the dam construction in the dry season. This is primarily associated with the impoundment of seasonal water by the dam and the increase in cropland areas due to dam irrigation. A significantly stronger correlation between vegetation changes and precipitation and temperature variations was observed before the dam construction. Furthermore, multivariant linear regression was used to evaluate the variations in equivalent water thickness (EWT), climate data, and NDVI before and after the dam construction. The results suggested that 85 percent of the variability in the mean NDVI was driven by climate variables and EWT before the dam construction. On the other hand, it was found that only 42 percent of the variations in the NDVI were driven by climate variables and EWT from 2010 to 2020 for both dry and wet seasons.<\/jats:p>","DOI":"10.3390\/rs15215252","type":"journal-article","created":{"date-parts":[[2023,11,6]],"date-time":"2023-11-06T13:24:53Z","timestamp":1699277093000},"page":"5252","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["The Impact of Dam Construction on Downstream Vegetation Area in Dry Areas Using Satellite Remote Sensing: A Case Study"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0514-9942","authenticated-orcid":false,"given":"Raid","family":"Almalki","sequence":"first","affiliation":[{"name":"School of Environmental and Life Science, University of Newcastle, Callaghan, NSW 2308, Australia"},{"name":"Department of Geography, Umm Al-Qura University, Makkah 21955, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3718-2843","authenticated-orcid":false,"given":"Mehdi","family":"Khaki","sequence":"additional","affiliation":[{"name":"School of Engineering, University of Newcastle, Callaghan, NSW 2308, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2478-3025","authenticated-orcid":false,"given":"Patricia M.","family":"Saco","sequence":"additional","affiliation":[{"name":"School of Engineering, University of Newcastle, Callaghan, NSW 2308, Australia"}]},{"given":"Jose F.","family":"Rodriguez","sequence":"additional","affiliation":[{"name":"School of Engineering, University of Newcastle, Callaghan, NSW 2308, Australia"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"AghaKouchak, A., Mirchi, A., Madani, K., Di Baldassarre, G., Nazemi, A., Alborzi, A., Anjileli, H., Azarderakhsh, M., Chiang, F., and Hassanzadeh, E. 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