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Erschienen in:
2024 | OriginalPaper | Buchkapitel
Deep Multi-temporal Matching of Satellite Images for Agricultural Dams
verfasst von : Omaima El Bahi, Ali Omari Alaoui, Youssef Qaraai, Ahmad El Allaoui
Erschienen in: Sustainable and Green Technologies for Water and Environmental Management
Verlag: Springer Nature Switzerland
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Abstract
Accurate multi-temporal satellite image matching plays a crucial role in monitoring agricultural areas, particularly in the context of water resource management. This study presents a feature-based approach for multi-temporal satellite image matching, using the VGG16 model. More specifically, our research focuses on the application of this approach to satellite images of agricultural dams in order to assess the reduction in water quantity caused by drought. Using the discriminant features extracted by the VGG16 model, we establish points of correspondence between images captured at different times, enabling precise alignment. Experimental results demonstrate the effectiveness of our approach in achieving accurate alignment of agricultural dam images, this study contributes to the advancement of feature-based matching techniques and their application in satellite image analysis for agricultural monitoring.