article · Sustainability
A new land evaluation method combines soil quality indicators and remote sensing data to evaluate and map soil suitability for rice cultivation. Tested in the northern Nile Delta, the method was evaluated against established parametric and qualitative models, including the square root, Storie, ALES, and MicroLEIS approaches. Suitability outputs aligned closely with Sentinel-2 Normalised Difference Vegetation Index values and actual crop yields. Across comparative tests, the new model delivered the highest accuracy, achieving an R-squared value of 0.92. Mapping revealed that roughly 44.4 per cent of the surveyed soils are highly suitable for rice, 44 per cent are moderately suitable, and about 11.6 per cent are unsuitable due to negative chemical and physical soil traits. The framework can be applied across arid regions to support crop planning.
Rice demand in Africa continues to rise, yet many countries depend heavily on costly imports. Accurate land suitability mapping identifies underutilised fertile land and pinpoints severe soil constraints. By showing exactly where rice can be grown productively, agricultural planners and regional governments can target investments, improve local crop yields, and strengthen food security in arid environments.
The framework is an applied and tested methodology ready to inform agricultural planning agencies and regional governments seeking to optimise rice production in arid zones. It can enable software-based land evaluation and geospatial advisory services for agricultural development programmes. Because it has been validated against field yield records and satellite data, the technique is well positioned for deployment in regional spatial planning and crop suitability forecasting.
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Today, the global food security is one of the most pressing issues for humanity, and, according to Food and Agriculture Organisation (FAO), the increasing demand for food is likely to grow by 70% until 2050. In this current condition and future scenario, the agricultural production is a critical factor for global food security and for facing the food security challenge, with specific reference to many African countries, where a large quantities of rice are imported from other continents. According to FAO, to face the Africa’s inability to reach self-sufficiency in rice, it is urgent “to redress to stem the trend of over-reliance on imports and to satisfy the increasing demand for rice in areas where the potential of local production resources is exploited at very low levels” The present study was undertaken to design a new method for land evaluation based on soil quality indicators and remote sensing data, to assess and map soil suitability for rice crop. Results from the investigations, performed in some areas in the northern part of the Nile Delta, were compared with the most common approaches, two parametric (the square root, Storie methods) and two qualitative (ALES and MicrioLEIS) methods. From the qualitative point of view, the results showed that: (i) all the models provided partly similar outputs related to the soil quality assessments, so that the distinction using the crop productivity played an important role, and (ii) outputs from the soil suitability models were consistent with both the satellite Sentinel-2 Normalize Difference Vegetation Indices (NDVI) during the crop growth and the yield production. From the quantitative point of view, the comparison of the results from the diverse approaches well fit each other, and the model, herein proposed, provided the highest performance. As a whole, a significant increasing in R2 values was provided by the model herein proposed, with R2 equal to 0.92, followed by MicroLES, Storie, ALES and Root as R2 with value equal to 0.87, 0.86, 0.84 and 0.84, respectively, with increasing percentage in R2 equal to 5%, 6% and 8%, respectively. Furthermore, the proposed model illustrated that around (i) 44.44% of the total soils of the study area are highly suitable, (ii) 44% are moderately suitable, and (iii) approximately 11.56% are unsuitable for rice due to their adverse physical and chemical soil properties. The approach herein presented can be promptly re-applied in arid region and the quantitative results obtained can be used by decision makers and regional governments.
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DOI: 10.3390/su12229653
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