Satellite detected water extent, as of 16 and 18 July 2019 over Kachin state, Myanmar

**UNOSAT code: FL20190715MMR** This map illustrates the cumulative satellite detected surface waters in Kachin and Saigang States, Myanmar by using a Sentinel-1 images acquired on 16 and 18 July 2019. Over an area of about 879km2 of lands appear to be likely flooded. By using the population data from Worldpop, total of about 987,000 people appear to have been affected by floods as of 18 July 2019. This is preliminary analysis that has not yet been validated in the field. Please send your comments to UNITAR-UNOSAT.

This map illustrates satellite-detected flood waters in the northwestern part of Rakhine State in the townships of Kyauktaw, Mrauk-U and Ponnagyun, Myanmar as imaged by the SENTINEL-1 satellite on 14 July 2016. Heavy rains at the onset of the monsoon season have caused flooding. The most affected lands seem to be mainly agricultural and/or paddy fields, many of which are of course frequently inundated at other times as well. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.

**UNOSAT code: FL20190715MMR** This map illustrates the cumulative satellite detected surface waters in Mandalay and Saigang States, Myanmar by using a Sentinel-1 images acquired on 16 and 18 July 2019. Over an area of about 450km2 of lands appear to be likely flooded. By using the population data from Worldpop, total of about 185,000 people appear to have been affected by floods as of 18 July 2019. This is preliminary analysis that has not yet been validated in the field. Please send your comments to UNITAR-UNOSAT.

**UNOSAT code: FL20240912MMR** This map illustrates aggregated satellite detected floods using Sentinel-1 images acquired on 03 to 20 September 2024 using an automated analysis with a machine learning method. Within the analysed area of about 80,000 km², a total of about 5,100 km² of land appears to be affected by flood waters and about 4,500 km² of cropland appears to be inundated. Based on Worldpop spatial demographic data, about 760,000 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: FL20190905LAO** This map illustrates satellite-detected surface water in Khammouan and Savannakhet Province of Lao PDR as observed from Sentinel-1 imagery acquired on 11 September 2019. Within the analysed extent of about 8,300 km2, a total about 332 km2 of land appear to be flooded as of 11 September 2019. 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 11 September 2019 may seriously underestimate presence of standing flood water in built up areas due to backscattering of the radar signal

**UNOSAT code: FL20210831MMR** This map illustrates satellite-detected surface waters over the Boga, Yangon regions and Mon state, surrounding the Gulf of Martaban, Myanmar as observed from a Sentinel-1 image acquired on 1 September 2021 at 05:55 local time. Within the analyzed area of about 10,000 km2 , 240 km2 of lands appear to be flooded. The water extent appears to have decreased of about 470 km2 since 25 August 2021. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the township of Thanatpin with ~ 7,300 people. Thaton with ~ 7,000 people. and Paung with ~ 5,700 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.