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Ain Shams University (2018)

Precision Agriculture Using Advanced remote sensing techniques in arid lands

El Sharkawy, Mohamed Mortada Ragab.

Titre : Precision Agriculture Using Advanced remote sensing techniques in arid lands

Auteur : El Sharkawy, Mohamed Mortada Ragab.

Etablissement de soutenance : Ain Shams University

Grade : Doctor of Philosophy (PhD) in Agricultural Sciences (Agriculture in Desert and Salt affected Areas) 2018

Résumé partiel
Soil characteristics play a major role in determining the cause and effects of crop selection and yield production. The soil morphology shows potential worrisome soil properties. Precision farming aim to manage fields according to topography, water consumption and soil types in different areas and its effect on crop yield. The current study aimed to use advanced techniques of remote sensing as a tools to solve the challenges facing the new reclaimed areas, especially in arid lands such as water scarcity and soil problems. Precision agriculture aims to reach the highest output and most appropriate production using lowest inputs while maintaining the safety of the surrounding environment and managing fields based on soil types in different areas. Moreover, the study discusses the impact of precision farming techniques on crop productivity and highlights the application of GPS techniques to adjust fertilizer nutrition according to Available Phosphorus, Available Potassium and soil Micro nutrients distribution and yield goals set by decision makers. The integrated management achieved using remote sensing and GIS techniques by producing of soil topography, various soil maps such as soil physical characteristics, EC, pH, CaCO3, Available phosphorus, Available potassium and Micro nutrients (Fe, Mn and Zn) linked to productivity crop of the study soil locations. Furthermore, study the relationship of plant spectral characteristics and yield response and to use the variable irrigation rate in irrigation scheduling precisely 5*5 meters. To achieve the main goal of the current study, Landsat satellite data were selected. The imagery information of the Landsat OLI provide visible reflective bands, shortwave infrared bands at 30 meter and thermal infrared bands resampled to 30-meter resolution, also the revisit time every eight days, allowing continuous monitoring of crop growth and the amount of water consumption by the presence of thermal bands. The advanced resolution merge techniques were used to increase high spatial resolution from 30 meter in Landsat sensors to 5 meters using Rapideye imagery which specially designed for precision agriculture service where it can be daily acquired and at a reasonable price and accurately spatial five meters. In this study we applied image fusion using Principal Component Spectral Sharpening (PCSS) method to integrate NDVI and plant water consumption calculated from Landsat satellite data. Furthermore, the ultra-multi-spectral devices has been used as a kind of new remote sensing modern techniques to study the vegetation characteristics and monitor vegetation healthy using narrow bands vegetation indices which easily can be linked to crop productivity. The global GPS system had a major role in locating training samples location, spectral measurements locations and revisiting the same places to take spectral measurements during different stages of crop growth. Collecting information on soil analyzes from previous studies allow identifying different soil units of the study area. Furthermore, the analysis of the soil gives a reasonable idea of the level of productivity in different soil units and also helps in developing new strategies to resolve the problems of soil to reach the highest productivity. The GIS techniques and geo-statistical models helped in the production of various soil maps for the study area, identifying the degree of soil fertility and adding the optimal fertilizer units, also GIS helps in producing yield map, soil samples grid system

Présentation étendue (EULC)

Page publiée le 30 mars 2020