Food security has become a global concern for humanity with rapid population growth, requiring a sustainable assessment of natural resources. Soil is one of the most important sources that can help to bridge the food demand gap to achieve food security if well assessed and managed. The aim of this study was to determine the soil quality index (SQI) for El Fayoum depression in the Western Egyptian Desert using spatial modeling for soil physical, chemical, and biological properties based on the MEDALUS methodology. For this purpose, a spatial model was developed to evaluate the soil quality of the El Fayoum depression in the Western Egyptian Desert. The integration between Digital Elevation Model (DEM) and Sentinel-2 satellite image was used to produce landforms and digital soil mapping for the study area. Results showed that the study area located under six classes of soil quality, e.g., very high-quality class represents an area of 387.12 km² (22.7%), high-quality class occupies 441.72 km² (25.87%), the moderate-quality class represents 208.57 km² (12.21%), slightly moderate-quality class represents 231.10 km² (13.5%), as well as, a low-quality class covering an area of 233 km² (13.60%), and very low-quality class occupies about 206 km² (12%). The Agricultural Land Evaluation System for arid and semi-arid regions (ALESarid) was used to estimate land capability. Land capability classes were non-agriculture class (C6), poor (C4), fair (C3), and good (C2) with an area 231.87 km² (13.50%), 291.94 km² (17%), 767.39 km² (44.94%), and 416.07 km² (24.4%), respectively. Land capability along with the normalized difference vegetation index (NDVI) used for validation of the proposed model of soil quality. The spatially-explicit soil quality index (SQI) shows a strong significant positive correlation with the land capability and a positive correlation with NDVI at R² 0.86 (p < 0.001) and 0.18 (p < 0.05), respectively. In arid regions, the strategy outlined here can easily be re-applied in similar environments, allowing decision-makers and regional governments to use the quantitative results achieved to ensure sustainable development.

中文翻译：

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干旱和半干旱条件下土壤质量评价空间模型的建立

随着人口的快速增长，粮食安全已成为人类关注的全球问题，需要对自然资源进行可持续的评估。如果评估和管理得当，土壤是最重要的来源之一，可以帮助弥合粮食需求缺口以实现粮食安全。这项研究的目的是使用基于MEDALUS方法的土壤物理，化学和生物学特性的空间模型，确定埃及西部沙漠El Fayoum洼地的土壤质量指数（SQI）。为此，开发了空间模型以评估西埃及沙漠中El Fayoum洼地的土壤质量。数字高程模型（DEM）与Sentinel-2卫星图像之间的集成用于生成研究区域的地貌和数字土壤图。结果表明，研究区域位于土壤质量的六个类别下，例如，非常高质量的类别代表的面积为387.12 km ²（22.7％），高质量的类别为441.72 km ²（25.87％），中等质量等级代表208.57 km ²（12.21％），中等质量等级代表231.10 km ²（13.5％），以及低质量等级，覆盖233 km ²（13.60％），并且非常低质量的等级大约占206 km ²（12％）。干旱和半干旱地区的农业土地评估系统（ALESarid）用于估算土地能力。土地能力等级为非农业等级（C6），差（C4），一般（C3）和良（C2），面积分别为231.87 km ²（13.50％），291.94 km ²（17％），767.39 km ²（ 44.94％）和416.07 km ²（24.4％）。土地功能以及归一化差异植被指数（NDVI）用于验证所提出的土壤质量模型。空间明确土壤质量指数（SQI）与土地能力之间呈极显着正相关，与R ²处与NDVI呈正相关分别为0.86（p <0.001）和0.18（p <0.05）。在干旱地区，此处概述的策略可以轻松地在相似的环境中重新应用，从而使决策者和区域政府可以使用所获得的定量结果来确保可持续发展。