Modeling Land Suitability for Rice Crop Using Remote Sensing and Soil Quality Indicators: The Case Study of the Nile Delta

Ahmed A. El Baroudy, Abdelraouf. M. Ali, Elsayed Said Mohamed, Farahat S. Moghanm, Mohamed S. Shokr, Igor Savin, Anton Poddubsky, Zheli Ding, Ahmed M.S. Kheir, Ali A. Aldosari, Abdelaziz Elfadaly, Peter Dokukin and Rosa Lasaponara
Additional contact information
Ahmed A. El Baroudy: Soil and Water Department, Faculty of Agriculture, Tanta University, Tanta 31527, Egypt
Abdelraouf. M. Ali: Agrarian-Technological Institute of the Peoples’ Friendship University of Russia, ul. Miklukho-Maklaya 6, 117198 Moscow, Russia
Elsayed Said Mohamed: National Authority for Remote Sensing and Space Sciences (NARSS), Cairo 11843, Egypt
Farahat S. Moghanm: Soil and Water Department, Faculty of Agriculture, Kafrelsheikh University, Kafrelsheikh 33516, Egypt
Mohamed S. Shokr: Soil and Water Department, Faculty of Agriculture, Tanta University, Tanta 31527, Egypt
Igor Savin: Ecological Faculty of the Peoples’ Friendship University of Russia, ul. Miklukho-Maklaya 6, 117198 Moscow, Russia
Anton Poddubsky: Agrarian-Technological Institute of the Peoples’ Friendship University of Russia, ul. Miklukho-Maklaya 6, 117198 Moscow, Russia
Zheli Ding: Haikou Experimental Station, Chinese Academy of Tropical Agricultural Sciences (CATAS), Haikou 570100, China
Ahmed M.S. Kheir: Soils, Water and Environment Research Institute, Agricultural Research Center, Giza 12112, Egypt
Ali A. Aldosari: Geography Department, King Saud University, 11451 Riyadh, Saudi Arabia
Abdelaziz Elfadaly: National Authority for Remote Sensing and Space Sciences (NARSS), Cairo 11843, Egypt
Peter Dokukin: Agrarian-Technological Institute of the Peoples’ Friendship University of Russia, ul. Miklukho-Maklaya 6, 117198 Moscow, Russia
Rosa Lasaponara: Italian National Research Council, C.da Santa Loja, Tito Scalo, 85050 Potenza, Italy

Sustainability, 2020, vol. 12, issue 22, 1-25

Abstract: 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 R 2 values was provided by the model herein proposed, with R 2 equal to 0.92, followed by MicroLES, Storie, ALES and Root as R 2 with value equal to 0.87, 0.86, 0.84 and 0.84, respectively, with increasing percentage in R 2 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.

Keywords: Sentinel-2; SRTM; NDVI; GIS; soil health; soil suitability for rice; Nile Delta (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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