Potential of land degradation index for soil salinity mapping in irrigated agricultural land in a semi-arid region using Landsat-OLI and Sentinel-MSI data-Reference-Cited by-同舟云学术

Potential of land degradation index for soil salinity mapping in irrigated agricultural land in a semi-arid region using Landsat-OLI and Sentinel-MSI data

Published:2024-08-27 Issue:9 Volume:196 Page:
ISSN:0167-6369
Container-title:Environmental Monitoring and Assessment
language:en
Short-container-title:Environ Monit Assess

Author:

Chaaou Abdelwahed,Chikhaoui Mohamed,Naimi Mustapha,Miad Aissa Kerkour El,Bokoye Amadou Idrissa,Ennasr Marieme Seif,Harche Sanae El

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10661-024-13030-1.pdf

Reference52 articles.

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2. Abdullah, A. Y. M., Biswas, R. K., Chowdhury, A. I., & Billah, S. M. (2019). Modeling soil salinity using direct and indirect measurement techniques: A comparative analysis. Environmental Development, 29, 67–80. https://doi.org/10.1016/j.envdev.2018.12.007

3. Abou Samra, R. M., & Ali, R. R. (2018). The development of an overlay model to predict soil salinity risks by using remote sensing and GIS techniques: A case study in soils around Idku Lake, Egypt. Environmental Monitoring and Assessment, 190(12), 706. https://doi.org/10.1007/s10661-018-7079-3

4. Abuelgasim, A., & Ammad, R. (2019). Mapping soil salinity in arid and semi-arid regions using Landsat 8 OLI satellite data. Remote Sensing Applications: Society and Environment, 13, 415–425. https://doi.org/10.1016/j.rsase.2018.12.010

5. Aksoy, S., Yildirim, A., Gorji, T., Hamzehpour, N., Tanik, A., & Sertel, E. (2022). Assessing the performance of machine learning algorithms for soil salinity mapping in Google Earth Engine platform using Sentinel-2A and Landsat-8 OLI data. Advances in Space Research, 69(2), 1072–1086. https://doi.org/10.1016/j.asr.2021.10.024