Satellite detected water extents from 23 to 24 January 2026 in Gaza, Maputo and Maputo City Provinces, Mozambique
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✦ Suggested by OrionAI**UNOSAT code: FL20251229MOZ** This map illustrates the flood extent derived from Sentinel-1 imagery acquired on 23 January 2026. Within the analysed area of approximately 43,500 km², an estimated 3,000 km² of land appears to be affected by floodwaters. Based on WorldPop spatial demographic data, approximately 230,000 people are exposed to or living near the flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT). Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to the backscattering properties of the radar signal.
**UNOSAT code: TC20240313MOZ, GDACS ID: 1001053** This map illustrates satellite detected surface waters in Gaza and Maputo provinces, Mozambique, as observed from a Sentinel-1 images acquired on 16 March 2024 at 05:19 local time (03:19 UTC). Within the analyzed areas of about 5000 km², a total of about 67 km² of lands appear to be flooded. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).
**UNOSAT code: TC20240313MOZ, GDACS ID: 1001053** This map illustrates satellite detected surface waters in Maputo province, Mozambique, as observed from a Sentinel-1 images acquired on 27 March 2024 at 18:23 local time (16:23 UTC). Within the analyzed areas of about 2,000 km², a total of about 45 km² of lands appear to be flooded. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT). Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
**UNOSAT code: FL20251229MOZ, GDACS ID: 1103694** This map illustrates the flood extent derived from Sentinel-1 imagery acquired on 5 January 2026, using an automated machine-learning-based analysis. Within the analysed area of approximately 25,000 km², an estimated 870 km² of land appears to be affected by floodwaters, representing an increase of about 100 km² compared to 31 December 2025 within the same analysed area. Based on WorldPop spatial demographic data, approximately 7,300 people are exposed to or living in close proximity to the flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT). Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to the backscattering properties of the radar signal.
**UNOSAT code: TC20240313MOZ, GDACS ID: 1001053** This map illustrates satellite detected surface waters in Maputo province, Mozambique, as observed from a Sentinel-1 images acquired on 23 March 2024 at 05:19 local time (03:19 UTC). Within the analyzed areas of about 950 km², a total of about 10 km² of lands appear to be flooded. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).
**UNOSAT code: TC20220124MOZ** This map illustrates satellite-detected surface waters in Zambezia Province, Mozambique as observed from a Sentinel-1 image acquired on 28 January 2021 at 05:00 local time and using an automated analysis with Artificial Intelligence based methods. Within the analyzed area of about 44,000 km2, about 860 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population are mainly located in the districts of Maganja Da Costa with ~22,500 people, Namacurra with ~17,000 people and Pebane with ~7,000 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
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