UNOSAT code: EQ20220622AFG This map illustrates potentially damaged structures/buildings in the northern part of Spera district, Khost province of Afghanistan as detected by Worldview-3 image acquired on 23 June 2022. Within the analyzed area, UNOSAT has identified 170 damaged buildings and 3 road obstacles, amongst the 2800 buildings identified in the analyzed zone. 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: FL20220525BGD This map illustrates satellite-detected surface waters in Rangpur Division, Bangladesh as observed from a Sentinel-1 images acquired on 21 Jun. 2022 at 18:05 local time and using an automated analysis with machine learning method. Within the analyzed area of about 12,400 km2, about 1,200 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 is mainly located in the district of Kurigram with ~537,000 people, and Gaibandha with ~355,000 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to 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: FL20220525BGD This map illustrates satellite-detected surface waters in Rajshahi, Rangur, Mymensingh, Dhaka and Khulna Divisions, Bangladesh as observed from a Sentinel-1 images acquired on 21 Jun. 2022 at 18:05 local time and using an automated analysis with machine learning method. Within the analyzed area of about 20,400 km2, about 2,950 km2 of lands appear to be flooded. Water extent appears to have increased of about 2,360 km2 since 9 Jun. 2022. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the division of Rajshahi with ~1,335,000 people, Dhaka with 674,000 people,and Mymensingh with ~ 640,000 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to 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: FL20220525BGD This map illustrates satellite-detected surface waters and impact in Sylhet and Sunamganj Districts, Sylhet Division, Bangladesh as observed from a RCM-1 image acquired on 18 Jun 2022 at 17:54 local time. Within the analyzed area of about 1,325 km2, about 840 km2 of lands appear to be flooded. In this area, about 140 km of roads and 1 km of railway appear to be likely affected by the flood waters. Based on Worldpop population data and the detected surface waters, about 839,000 people are potentially 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 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: FL20220525BGD This map illustrates satellite-detected surface waters in Sylhet, Mymensingh, Dhaka, and Chattogram Divisions, Bangladesh observed from a RCM-1 images acquired on 19 Jun. 2022 at 18:02 local time. Within the analyzed area of about 22,300 km2, about 9,500 km2 of lands appear to be flooded. In this area, about 7,860 km2 of croplands and 1,340 km2 of herbaceous wetland appear to be likely affected by the flood waters. Based on Worldpop population data and the detected surface waters, about 7,334,000 people are potentially 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 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: FL20220525BGD This map illustrates satellite-detected surface waters in Sylhet, Mymensingh, Dhaka, and Chattogram Divisions, Bangladesh as observed from a RCM-1 images acquired on 19 Jun. 2022 at 18:02 local time. Within the analyzed area of about 22,300 km2, about 9,500 km2 of lands appear to be flooded. Water extent appears to have increased of about 2,150 km2 since the period between 25 to 28 May 2022. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Sunamganj with ~1,822,000 people and Sylhet with ~1,550,000 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to 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: CE20220223UKR This map illustrates a satellite imagery based damage analysis within an area of interest (AOI) in the residential area of Mariupol City, Ukraine. Based on imagery collected on 7, 8, 12 May 2022 and 14 March 2022, and 21 June 2021, analysts found that 5,647 structures sustained visible damage in the AOI. This represents approximately 32% of the structures. Out of these, 315 are destroyed, 2,132 severely damaged, 3,002 moderately damaged and 194 possibly damaged. Compared to the 14 March 2022 analysis, 5% of previously affected buildings sustained additional damage, and the total damage has increased by 28%, with 4,910 new damaged buildings. While no complete count of buildings for Mariupol is available, an open source dataset, which is visibly incomplete indicates at least 17,568 structures in the area. This analysis is based on structures visibly damaged as of 12, 8, 7 May 2022 and 14 March 2022 as seen in marginally degraded satellite imagery. 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: FR20220605AFG This map illustrates satellite-detected areas of wildfires in Nurgaram District, Nuristan Province, Afghanistan as observed from Sentinel-2 imagery acquired on 2 Jun. 2022 about 10:39 am. The wildfire scars cover an approximate area of 68 ha and appear to have increased of about 33 ha since 28 May 22. The fire has been spread from the top to down direction of the mountain. 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).