A GIS-Based Approach for the Quantitative Assessment of Soil Quality and Sustainable Agriculture

Mostafa A. Abdellatif, Ahmed A. El Baroudy, Muhammad Arshad, Esawy K. Mahmoud, Ahmed M. Saleh, Farahat S. Moghanm, Kamal H. Shaltout, Ebrahem M. Eid and Mohamed S. Shokr
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Mostafa A. Abdellatif: National Authority for Remote Sensing and Space Science (NARSS), Cairo 11843, Egypt
Ahmed A. El Baroudy: Soil and Water Department, Faculty of Agriculture, Tanta University, Tanta 31527, Egypt
Muhammad Arshad: Department of Chemical Engineering, College of Engineering, King Khalid University, Abha 61321, Saudi Arabia
Esawy K. Mahmoud: Soil and Water Department, Faculty of Agriculture, Tanta University, Tanta 31527, Egypt
Ahmed M. Saleh: National Authority for Remote Sensing and Space Science (NARSS), Cairo 11843, Egypt
Farahat S. Moghanm: Soil and Water Department, Faculty of Agriculture, Kafrelsheikh University, Kafr El-Sheikh 33516, Egypt
Kamal H. Shaltout: Botany Department, Faculty of Science, Tanta University, Tanta 31527, Egypt
Ebrahem M. Eid: Biology Department, College of Science, King Khalid University, Abha 61321, Saudi Arabia
Mohamed S. Shokr: Soil and Water Department, Faculty of Agriculture, Tanta University, Tanta 31527, Egypt

Sustainability, 2021, vol. 13, issue 23, 1-24

Abstract: Assessing soil quality is considered one the most important indicators to ensure planned and sustainable use of agricultural lands according to their potential. The current study was carried out to develop a spatial model for the assessment of soil quality, based on four main quality indices, Fertility Index (FI), Physical Index (PI), Chemical Index (CI), and Geomorphologic Index (GI), as well as the Geographic Information System (GIS) and remote sensing data (RS). In addition to the GI, the Normalized Difference Vegetation Index (NDVI) parameter were added to assess soil quality in the study area (western part of Matrouh Governorate, Egypt) as accurately as possible. The study area suffers from a lack of awareness of agriculture practices, and it depends on seasonal rain for cultivation. Thus, it is very important to assess soil quality to deliver valuable data to decision makers and regional governments to find the best ways to improve soil quality and overcome the food security problem. We integrated a Digital Elevation Model (DEM) with Sentinel-2 satellite images to extract landform units of the study area. Forty-eight soil profiles were created to represent identified geomorphic units of the investigated area. We used the model builder function and a geostatistical approach based on ordinary kriging interpolation to map the soil quality index of the study area and categorize it into different classes. The soil quality (SQ) of the study area, classified into four classes (i.e., high quality (SQ2), moderate quality (SQ3), low quality (SQ4), and very low quality (SQ5)), occupied 0.90%, 21.87%, 22.22%, and 49.23% of the total study area, respectively. In addition, 5.74% of the study area was classified as uncultivated area as a reference. The developed soil quality model (DSQM) shows substantial agreement (0.67) with the weighted additive model, according to kappa coefficient statics, and significantly correlated with land capability R 2 (0.71). Hence, the model provides a full overview of SQ in the study area and can easily be implemented in similar environments to identify soil quality challenges and fight the negative factors that influence SQ, in addition to achieving environmental sustainability.

Keywords: developed soil quality model; GIS; Egypt; NDVI; geomorphologic index (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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