Quantitative assessment of Land use/land cover changes in a developing region using machine learning algorithms: A case study in the Kurdistan Region, Iraq

The identification of land use/land cover (LULC) changes is important for monitoring, evaluating, and preserving natural resources. In the Kurdistan region, the utilization of remotely sensed data to assess the effectiveness of machine learning algorithms (MLAs) for LULC classification and change de...

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Detalles Bibliográficos
Autores principales: Rash, Abdulqadeer, Mustafa, Yaseen, Hamad, Rahel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638604/
https://www.ncbi.nlm.nih.gov/pubmed/37954393
http://dx.doi.org/10.1016/j.heliyon.2023.e21253

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638604/
https://www.ncbi.nlm.nih.gov/pubmed/37954393
http://dx.doi.org/10.1016/j.heliyon.2023.e21253

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