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We present here the scientific outcomes of the 2021 Data Fusion Contest (DFC2021) organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society. DFC2021 was dedicated to research on geospatial artificial intelligence (AI) for social good with a global objective of modeling the state and changes of artificial and natural environments from multimodal and multitemporal remotely sensed data towards sustainable developments. DFC2021 included two challenge tracks: "Detection of settlements without electricity" and "Multitemporal semantic change detection". This paper mainly focuses on the outcome of the multitemporal semantic change detection track. We describe in this paper the DFC2021 dataset that remains available for further evaluation of corresponding approaches and report the results of the bestperforming methods during the contest.

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