Abstract
Land evaluation is imperative for its efficient use in agriculture. Therefore, this study aimed at assessing the suitability of a region in West El-Minia for cultivating some of the major crops using the geographical information system (GIS). The results focus on allocating space for cultivating sugar beet and utilizing the free period of sugar beet in other crops. This exploitation helps to maintain the quality of the land and increase its fertility by using crop rotation with integrated agricultural management. A machine learning technique was implemented using the random forest algorithm (RF) to predict soil suitability classes for sugar beet using geomorphology, terrain attribute and remote sensing data. Fifteen major crops were evaluated using a suitability multicriteria approach in GIS environment for crop rotation decisions. Soil parameters were determined (soil depth, pH, texture, CaCO3, drainage, ECe, and slope) to characterize the land units for soil suitability. Soils of the area were found to be Entisols; Typic Torrifluvents, Typic Torripsamments and Typic Torriorthents and Aridsols; Typic Haplocacids, Calcic Haplosalids and Sodic Haplocalcids. Overall, the studied area was classified into four suitability classes: high “S1”, moderate “S2”, marginal “S3”, and not suitable “N”. The area of each suitability class changed depending on the crop tested. The highest two crops that occupied S1 class were barley with 471.5 ha (representing 6.8% of the total study area) and alfalfa with 157.4 ha (2.3%). In addition, barley, sugar beet, and sorghum occupied the highest areas in S2 class with 6415.3 ha (92.5%), 6111.3 ha (88.11%) and 6111.3 ha (88.1%), respectively. Regarding the S3 class, three different crops (sesame, green pepper, and maize) were the most highly represented by 6151.8 ha (88.7%), 6126.3 ha (88.3%), and 6116.7 ha (88.2%), respectively. In the end, potato and beans occupied the highest areas in N class with 6916.9 ha (99.7%) and 6853.5 ha (98.8%), respectively. The results revealed that the integration of GIS and soil suitability system consists of an appropriate approach for the evaluation of suitable crop rotations for optimized land use planning and to prevent soil degradation. The study recommends using crop rotation, as it contributes to soil sustainability and the control of plant pests and diseases, where the succession of agricultural crops on a scientific basis aims at maintaining the balance of nutrients and fertilizers in the soil.
Highlights
Egypt suffers from water deficit, which affects agricultural production, as well as the growing gap between food production and consumption for most agricultural crops in light of the continuous population increase [1]
The results demonstrated that multiple linear regression (MLR), support vector regression (SVR), and artificial neural networks (ANN) are more prone to overfitting, whereas random forest (RF) algorithm avoids the risk of overfitting, and takes less time to compute
The output of the research concluded that potato and beans have the lowest suitability class N with areas of 6916.8 ha (99.73%) and 6853.4 ha (98.82%), respectively, while for S2 classes were barley, alfalfa, onion, sorghum, sugar beet, soybean, sunflower and tomato with areas of 6415.3 ha (92.5%), 5547.2 ha (80%), 5704.5 ha (82.3%) 6111.3 ha (88.1%), 6111.3 ha (88.1%), 3971.1 ha (57.3%), 5700 ha (82.2%), and 3967.6 ha (57.2%), respectively
Summary
Egypt suffers from water deficit, which affects agricultural production, as well as the growing gap between food production and consumption for most agricultural crops in light of the continuous population increase [1]. Agricultural suitability assessment is the evaluation of the methodological performance of land when using alternative cultivation options [5,6]. The primary purpose of assessing the suitability of agricultural land is to predict the potential and limitations of land for crop production [7]. Several researchers [8,9] have documented remote sensing and geographic information system capabilities to assess land suitability. A combination of GIS and multicriteria evaluation techniques with a weighted overlay approach for land suitability analysis proves to be a useful methodology for further research in the concept of crop suitability for the optimized irrigation method [12]. The suitability of agricultural land for the area was not documented previously
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