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Accueil du site → Doctorat → Allemagne → 2006 → Precision farming in the small farmland in the eastern Nile Delta Egypt using remote sensing and GIS

Albert-Ludwigs - Universität Freiburg im Breisgau (2006)

Precision farming in the small farmland in the eastern Nile Delta Egypt using remote sensing and GIS

Belal, Abdelaziz Belal Abdel Elmontalbe

Titre : Precision farming in the small farmland in the eastern Nile Delta Egypt using remote sensing and GIS

Auteur : Belal, Abdelaziz Belal Abdel Elmontalbe

Université de soutenance : Albert-Ludwigs - Universität Freiburg im Breisgau

Grade : Doktor 2006

Résumé
The principal aims of this study are the application of precision farming technology with crop growth models in Egypt to increase the yield production and the monitoring of the change in the land use and land cover in the study area. To achieve these aims, remote sensing imagery was analysed. In addition, field surveys were done, from which ground control points and terrestrial data pertaining to land use and land cover were acquired. Ancillary information as to agricultural management strategies was also obtained through interviews with experts and farmers. Soil and water samples were collected and chemically analysed and the results from the analyses were used to produce crop growth models. The study area is located in the east of the Nile delta in between longitude 31o 50 and 32o 15´ E and latitude 30o 45´ and 31o 00´N. The total surface area is approximately 103,000 hectares. This area is an extension of the agricultural area in Egypt. Two types of the water are used for agriculture : fresh water and reused drainage water. Three test areas were selected for the application of the precision farming technique using high-resolution SPOT 5 image. The total area for test areas one, two and three were 37.29, 19.80 and 8.69 hectares respectively. These three test areas had different management zones. The work reports on how remote sensing data, soil variables and crop growth models (statistical and spatial models) can be used to asses the relationships between the crop yield production and soil variables and also to delineate the different management zones in the test areas

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