Satellite detected water extent over Jawa Tengah Province, Indonesia as of 19 Mar. 2024
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✦ Suggested by OrionAI**UNOSAT code: EQ20240326IDN, GDACS ID: 1420595** This map illustrates satellite-detected surface waters in Jawa Tengah Province, Indonesia, as observed from a Sentinel-1 image acquired on 27 March 2024 at 22:17 UTC. and a Fucheng-1 image acquired on 27 March 2024 at 14:51 UTC. Within the analysed area of about 4,400 km², a total of about 260 km² of land appears to be flooded, receding of about 60 km² compared to 19 March 2024. 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: FL20200101IDN** This map illustrates satellite-detected surface water in Banten, Dki Jakarta and Jawa Barat Province of Indonesia as observed from Sentinel-1 imagery acquired on the 2 January 2020. Approximately 258 km2 of land appear to be flooded. 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 Sentinel-1 imagery acquired on 2 January 2020 may seriously underestimate presence of standing flood water in built up areas due to 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 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: 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: FL20240928NPL** This map illustrates the floods using Sentinel-1 images acquired on 29 September 2024 at 18:15 local time (12:30 UTC). Within the analysed area of about 20,000 km², a total of about 110 km² of land appears to be affected by flood waters. Based on Worldpop spatial demographic data, about 58,000 people are exposed or living close to 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: FL20240603LKA, GDACS ID: 1102660** This map illustrates satellite-detected water extent in the North Western Province, Sri Lanka, as observed from a Sentinel-1 image acquired on June 4, 2024, at 00:25 UTC. Within the analyzed area of about 4,000 km², a total of about 46 km² of land appears to be affected by floodwaters. The water extent appears to have receded by about 34 km² since May 23, 2024. Based on WorldPop population data and the flood extent, approximately 16,000 people are potentially exposed. 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.
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