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Journal of Soil Sciences and Agricultural Engineering
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Mustafa, A. (2023). Incorporate the Fertility Capability Classification and Geo-informatics for Assessing Soil: A Case Study on Some Soils of Sohag Governorate, Egypt. Journal of Soil Sciences and Agricultural Engineering, 14(7), 187-193. doi: 10.21608/jssae.2023.202544.1155
A. A. Mustafa. "Incorporate the Fertility Capability Classification and Geo-informatics for Assessing Soil: A Case Study on Some Soils of Sohag Governorate, Egypt". Journal of Soil Sciences and Agricultural Engineering, 14, 7, 2023, 187-193. doi: 10.21608/jssae.2023.202544.1155
Mustafa, A. (2023). 'Incorporate the Fertility Capability Classification and Geo-informatics for Assessing Soil: A Case Study on Some Soils of Sohag Governorate, Egypt', Journal of Soil Sciences and Agricultural Engineering, 14(7), pp. 187-193. doi: 10.21608/jssae.2023.202544.1155
Mustafa, A. Incorporate the Fertility Capability Classification and Geo-informatics for Assessing Soil: A Case Study on Some Soils of Sohag Governorate, Egypt. Journal of Soil Sciences and Agricultural Engineering, 2023; 14(7): 187-193. doi: 10.21608/jssae.2023.202544.1155

Incorporate the Fertility Capability Classification and Geo-informatics for Assessing Soil: A Case Study on Some Soils of Sohag Governorate, Egypt

Article 1, Volume 14, Issue 7, July 2023, Page 187-193  XML PDF (1.22 MB)
Document Type: Original Article
DOI: 10.21608/jssae.2023.202544.1155
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Author
A. A. Mustafa email
Soil and Water Department, Faculty of Agriculture, Sohag University, Sohag, Egypt
Abstract
Soil, as a natural and nonrenewable resource become the most fragile ecosystem due to long-term cultivation by human being. The knowledge and understanding the parameters that determine the quality of agricultural soils can improve their management of soil resources. Geo-informatics techniques have emerged for the assessment, mapping and modelling of various soil resources. Hence, an attempt has made to study the soils of Sohag Governorate and generate fertility capability classification (FCC) map using geo-informatics. Different remote sensing data such as Landsat 9 imageries and ASTER sensor integrated. Consequently, representative soil profiles chosen and samples collected for analyzing. The results indicated that the main landforms observed were Nile Alluvium (NA), Low recent river terraces (LR), High recent river terraces (HR) and Wadi Bottom (WB). Soil fertility limitations and condition modifiers characterizing different units were identified. The fertility of the NA and LR soils was good with fewer limitations. Whereas, both HR and WB soils have many limitations that render them under either poor or very poor fertility capability. Generally, this information is valuable for decision-makers and land managers to make informed decisions about soil conservation and management.
Keywords
Geoinformatics; Fertility capability classification; Landforms
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