Modeling soil quality in Dakahlia Governorate, Egypt using GIS techniques

被引:39
作者
Abuzaid, Ahmed S. [1 ]
Abdellatif, Abdellatif D. [2 ]
Fadl, Mohamed E. [3 ]
机构
[1] Benha Univ, Fac Agr, Soil & Water Dept, Banha, Egypt
[2] Agr Res Ctr, Soil Water & Environm Res Inst SWERI, Giza, Egypt
[3] Natl Author Remote Sensing & Space Sci NARSS, Div Sci Training & Continuous Studies, Cairo, Egypt
关键词
Soil quality; GIS; Modeling; North Nile Delta; DEGRADATION; INDICATORS; PROVINCE; LAND;
D O I
10.1016/j.ejrs.2020.01.003
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Evaluating soil quality (SQ) is essential to track changes in soil performance in response to management practices. The current work aimed at using remote sensing and GIS to assess SQ in Dakahlia Governorate, north Nile Delta of Egypt. Twenty-one soil profiles representing the main geomorphic units in the area were dug and samples were collected from different horizons and analysed. Twenty-nine parameters were used to calculate 4 soil quality indices; chemical, physical, fertility and environmental. The four indices were assembled with the geomorphic units in four thematic layers, which were overlain in accordance with geometric mean algorism in a single map. The proposed model showed that about 29% of the total agricultural lands were classified as very high, 30% as high, 33% as moderate, 3% as low and 5% as very low quality. Results of the proposed model agreed with those calculated by the additive index in 95% of the cases, while they agreed with the weighted additive index in 71% of the cases. The Kappa statics indicated an almost perfect agreement between the proposed model and the additive model, while a moderate agreement with the weighted additive model. The proposed model had the highest sensitivity index, indicating its accuracy for evaluating SQ in the studied area. The developed model would provide a useful tool for proper monitoring of soil performance in the studied area. (c) 2020 National Authority for Remote Sensing and Space Sciences. Production and hosting by Elsevier B. V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).
引用
收藏
页码:255 / 264
页数:10
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