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Using remote sensing data and artificial intelligence to inventory and classify
field crops
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Obtaining a geographic database and digital maps of wheat, clover and sugar
beet crops in the governorates.
- Producing maps of soil, production capacity
and soil suitability for crop structures.
Dr.
Islam Abu El-Magd, Chairman of the National Authority for Remote Sensing and
Space Sciences, reviewed a number of projects implemented by the Authority in
cooperation with various institutions and entities during the past period.
The
Chairman of the Authority explained that there is great interest on the part of
Dr. Ayman Ashour, Minister of Higher Education and Scientific Research, in
enhancing cooperation between the research bodies affiliated with the Ministry
and various bodies and institutions, to achieve integration and cooperation
that benefits society, in line with achieving the objectives of the National
Strategy for Higher Education and Scientific Research.
Dr.
Islam Abu Al-Magd explained that the Authority, in cooperation with the
Ministry of Agriculture and Land Reclamation, produced a map of agricultural
crops for the winter agricultural season 2023/2024, where remote sensing data
and artificial intelligence were used to inventory and classify field crops
(winter season 2023-2024) and the summer season 2024 for the governorates of
the Republic.
The
Chairman of the Authority added that coordination had been made between the
Ministry of Agriculture and the Ministry of Higher Education and Scientific
Research, represented by the National Authority for Remote Sensing and Space
Sciences. To inventory and classify some strategic crops in the Arab Republic
of Egypt, based on remote sensing and artificial intelligence techniques,
explaining that relying on remote sensing data to inventory crops for the
2023-2024 winter season (wheat, clover, and sugar beets) shows the precise
spatial distribution of change in crop areas, In addition to the possibility of
monitoring the growth status of different crops during the agricultural season
using vegetative evidence, so that the type of crop is determined by the integration
of various factors.
Dr.
Abdul-Aziz Bilal, head of the Agricultural Applications Division at the
Authority and the main researcher of the project, explained that the project
contributed to obtaining a geographical database and digital and paper maps of
field verification points for the winter season (2023-2024) for wheat, clover
and sugar beet crops in the governorates.
Dr
Mohamed Abo El-Ghar, Head of the Department of Agricultural Applications and
member of the project's steering committee, stressed the importance of the
pivotal role played by remote sensing technologies supported by artificial
intelligence tools in periodic and accurate monitoring of crops throughout the
Republic to identify basic needs, estimate reserves of strategic crops, design
policies to manage the local trade, import or export of agricultural crops, and
develop future scenarios on scientific grounds for the preferred areas for the
establishment of industries based on agricultural products.
The
Authority also cooperated with the General Authority for Agricultural
Development and Reconstruction Projects to produce soil maps, production
capacity and soil suitability for crop structures.
Dr
Abdul-Aziz Bilal, head of the Agricultural Applications Division at the
Authority and principal researcher of the project, pointed out that the
Ministry of Agriculture, represented by the General Authority for
Reconstruction and Agricultural Development Projects, and the Ministry of
Higher Education and Scientific Research, represented by the National Authority
for Remote Sensing and Space Sciences, coordinated to study the natural and
land resources in Egyptian lands, and the study was concerned through a set of
projects to survey, classify and evaluate about 2.5 million acres across the
republic.
Dr. Mohamed Jalhoum, Head of the Soil Department and a member of the project team, reviewed the project’s most prominent outputs, including the creation of a digital database on land resources for each study area, and the production of a map of the physiographic units in the study areas based on the hydrological, morphometric, and spectral variables that were extracted through analysis of the digital elevation model and images. Satellites, producing a digital soil map to identify different types of lands on scientific grounds depending on the important natural, chemical and biological properties and surrounding conditions, producing a map of the soil’s productive capacity, and producing maps of optimal crop compositions to determine the most appropriate technical methods for exploiting the soil and choosing the most appropriate crops that have each type of Soil types.
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