Yanbiao Ma, Yuxin Li, Kexin Feng, Yu Xia, Qi Huang, Hongyan Zhang, Colin Prieur, Giorgio Licciardi, Hana Malha, Jocelyn Chanussot, Pedram Ghamisi, Ronny Hansch, and Naoto Yokoya

Detection of settlements without electricity

Algorithm for detection of settlements without electricity.

In this article, we elaborate on the scientific outcomes of the 2021 Data Fusion Contest (DFC2021), which was organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society, on the subject of geospatial artificial intelligence for social good. The ultimate objective of the contest was to model the state and changes of artificial and natural environments from multimodal and multitemporal remotely sensed data towards sustainable developments. DFC2021 consisted of two challenge tracks: Detection of settlements without electricity (DSE) and multitemporal semantic change detection. We focus here on the outcome of the DSE track. This article presents the corresponding approaches and reports the results of the best-performing methods during the contest.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 12375, 2021-11-24.

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IARAI Authors
Dr. Pedram Ghamisi
Research
Remote Sensing
Keywords
Convolutional Neural Network, Data Fusion, Deep Learning, Land Cover, Random Forest, Weak Supervision

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