Optimizing Crop-Water Productivity Using Remote Sensing and Multi-Sources Data (WatSens)

Summary

The project aims to help the farmers by supporting them with the optimal water management to irrigate their farms for saving as much as possible of water and in the same time obtaining the optimal yield. The idea is to introduce the image processing and machine learning technology to serve the agriculture field. Analyzing the different satellite images of the same location during the agricultural season in addition to the field data (crop and soil) will help building a model that use the satellite images directly for estimating the dryness level of the crop. Hence, the information of optimal timing for irrigation would be estimated. The project will be implemented in Sidi Salem district in Kafr El-Sheikh governorate. The stakeholders will be the farmers, agricultural engineer and researchers. Workshops will be held to the stakeholders for explaining the importance of the water irrigation management. An AI model will be designed for managing the utilized irrigation water at the selected crops. The model will be evaluated with independent data. At the end of the project the established model would be able to use the future satellite images, which contain the researched crops, and recognize the wetness/dryness level of the crop and that will guarantee the sustainability of the model. Furthermore, additional crops could be inserted to the model in the future in case of managing a supplementary financial support. The project will be done under the management of Computer Engineering, Ain Shams University. The ARC will be the executive partner, who will manage the field work from selecting the research areas (farms) in Sidi Salem, collecting the crop and soil data frequently (each 2 weeks), developing the AI model to cover the research target using the collected data and the satellite images, connecting with the stakeholders for explaining the importance of research, collecting the data and evaluating the model results. MCIT will be the industrial partner.

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