Floods - Southern Malawi - March 2019

Product ============= This priority index was derived by combining a detailed flood extent mapping with detailed human settlement geo-data. Both sources were combined to produce the location and magnitude of population living in flooded areas. This was subsequently aggregated to admin-4 areas (GND) as well as admin-3 areas (DS divisional). The flood extent mapping was derived in turn by combining two sources: Flood extent maps could be produced rather faster using satellite imageries captured by either optical sensors or Synthetic Aperture Radar (SAR) sensors. In most places flood is cause by heavy rainfall which means in most cases cloud is present, this is a limitation for optical sensors as they can’t penetrate clouds. Radar sensors are not affected by cloud, which make them more useful in presence of cloud. In This analysis we analyzed sentinel2 optical image from May 28th and Sentinel 1 SAR image from May 30th. Then we combine the two results adding up the flood extents. Main cloud covered areas and permanent water bodies are removed from the flood extent map using the Sentinel 2 cloud mask. The scale/resolution of the flood extent map is 30mts where as the permanent water body map has 250m scale resolution. This will introduce some discrepancy: part of flood extent map could be permanent water body. Scope ============= Analysis focused on 4 districts in South-West Sri Lanka based on news reports (https://www.dropbox.com/s/n0qdqe7qfgq6fyv/special_situation.pdf?dl=0). Based on the admin-3-level analysis, highest percentages of population living in flooded areas were seen in Matara district. Admin-4 level analysis concentrated only on Matara district for that reason. Caveats ============= The dataset is showing percentage flooded. The data has not yet been corrected for small populations. We believe the product is currently pointing to the high priority areas. In the shp or csv files the user of this data could easily correct for small populations, if there is a wish to target on the amount of people affected. Data used from partners ============= The human settlement data was retrieved from http://ciesin.columbia.edu/data/hrsl/. Facebook Connectivity Lab and Center for International Earth Science Information Network - CIESIN - Columbia University. 2016. High Resolution Settlement Layer (HRSL). Source imagery for HRSL © 2016 DigitalGlobe. Accessed 01-06-2017. The Radar imagery analysis was done by NASA JPL, whose input in this product has been crucial. Visualization =========== An example map is available here: http://bit.ly/SriLankaFloodMap Linked data ========== Admin boundaries 3 and 4 can be found here (link on OBJECT_ID): https://data.humdata.org/group/lka?q=&ext_page_size=25&sort=score+desc%2C+metadata_modified+desc&tags=administrative+boundaries#dataset-filter-start How to use ============= The ratio column in the SHPs or CSVs can be multiplied by 100 to get the percentage of flooding in the area.

**UNOSAT code: TC20220126MWI** This map illustrates population potentially exposed to floods (cumulative) aggregated by district in Malawi from Sentinel-1 images acquired between 26 January and 2 February 2022 about 05:00 local time. The flood analysis was carried out by using automated analysis with an Artificial Intelligence based method, and Worldpop spatial demographic data. About 102,000 people were exposed or living close to flooded areas. The population potentially exposed to floods are mainly located in the districts of Chikwawa with ~ 33,700 people and Nsanje with ~ 33,700 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.

**UNOSAT code: TC20220126MWI** This map illustrates the floods (cumulative) aggregated using Sentinel-1 images acquired between 26 January and 2 February 2022 about 05:00 local time. The flood analysis were carried out by using automated analysis with an Artificial Intelligence based method, and Worldpop spatial demographic data. About 102,000 people were exposed or living close to flooded areas. The population potentially exposed to floods are mainly located in the districts of Chikwawa with ~ 33,700 people and Nsanje with ~ 33,700 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.

**UNOSAT code: TC20220126MWI** This map illustrates satellite-detected surface waters in Balaka, Blantyre, Neno, and Zomba districts, Southern region, Malawi as observed from a Sentinel-1 image acquired on 26 January 2021 at 05:16 local time and using an automated analysis with Artificial Intelligence based methods. Within the analyzed area of about 1,000 km2, about 28 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, about 5,400 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.

Flood impact records for districts in Malawi, with each row covering a district and listing flooded area, flooded cropland, total population, croplands area, and counts of directly affected people, children and elderly. Published by Orion Terrametrics.

**UNOSAT code TC20230314MWI, GDACS Id: 1000961** This map illustrates cumulative satellite-detected surface waters in Southern Region, Malawi between 17 to 21 March 2023 as observed from: VIIRS imagery from 17 to 21 March 2023; Sentinel-1 imagery acquired on 17 Mar. 2023 and Sentinel-2 imagery acquired on 21 Mar. 2023. Within the analyzed area of about 30,000 km2, about 2,100 km2 of land appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, ~280,000 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 the backscattering properties of the radar signal.