Ukraine GIS data

**UNOSAT code FL20230606UKR** This map illustrates satellite-detected surface waters evolution using Sentinel-1 images acquired on the 09th of June 2023 at 15:36 UTC and compared with surface waters extracted using ICEYE acquired on the 07th of June 2023 compared with a pre-flood water extracted using a Sentinel-2 images acquired on the 03rd and the 05th of June 2023. Within the analysed area of 500 km², surface waters appear to have receded by about 14 km². 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 FL20230606UKR** This map illustrates satellite-detected flood waters along the 90km downstream of Dnipro River between the damaged Nova Kakhovka Dam wall and the Dnipro River mouth in Ukraine as observed from a Sentinel-1 images acquired on 21 June 2023 at 15:36 UTC. Within the analysed area of about 10,800 km², about 20 km² of land appear to remain flooded. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).

**UNOSAT code FL20230606UKR** This map illustrates satellite-detected flood waters and affected structures next to Nova Kakhova Dam in Khersonska Oblast (Ukraine) as observed from Skysat image acquired on 6 June 2023 at 08:07 UTC; and a pre-event Worldview-2 image acquired on 5 June 2023. Within the analysed area of 80 km², about 5 km² of land appear to be flooded. 346 structures and 07 harbours are damaged. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).

**UNOSAT code FL20230606UKR** This map illustrates satellite-detected surface waters over Khersonska Oblast, Ukraine observed from a Sentinel-3 image acquired on 6 June 2023 at 08:30 UTC; and a Sentinel-2 image acquired on 3 & 5 June 2023. Within the analysed area of 19,000 km², about 120 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 United Nations Satellite Centre (UNOSAT).

**UNOSAT code FL20230606UKR** This map illustrates satellite-detected surface waters using Sentinel-1 images acquired on the 09th of June 2023 at 15:36 UTC. Within the analysed area of 260 km², along the Dnieper River, surface waters appear to have receded by about 12km². The water level of the cooling pond seems to be stable as of 09 June 2023. 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 FL20230606UKR** This map illustrates satellite-detected flood waters over Oleshky City, in the east bank of the Dnieper/Dnipro River in Khersonska Oblast, Ukraine as observed from a Landsat-9 satellite images acquired on 9 June 2023 at 08:37 UTC. 50% (8km2) of Olehsky appears to be affected by flood waters. Water extent appeared to have decreased by about 2 km2 since 7 June 2023. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).

**UNOSAT code FL20230606UKR** This map illustrates satellite-detected water using Sentinel-2 image acquired on the 15th of July 2023 and compared with the water extent between the 03rd and the 05th of July 2023 after the Nova Kakhovka dam wall break of the 06th of June 2023. Within the analysed area of 25,000 km², surface waters appear to have receded by about 100 km² in cloud free zone since the 5th of July 2023. No major changes observed in water level of the cooling pond of the Zaporizhia nuclear power plant as of 15 July 2023 compared to 5 July 2023. 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 FL20230606UKR** This map illustrates satellite-detected flood water extent and evolution using Sentinel-2 images acquired on the 13th of June 2023 at 08:46 UTC and compared with pre-flood waters detected from Sentinel-2 images acquired on the 03rd and the 05th of June 2023. Within the analysed area of 19,000 km², about 180 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 the United Nations Satellite Centre (UNOSAT).

**UNOSAT code FL20230606UKR** Live web map providing geospatial information using satellite imagery data about floods along the Dnipro River, Ukraine following the Nova Khakovka Dam break.

**UNOSAT code FL20230606UKR** This map illustrates cumulative satellite-detected water using ICEYE images and Sentinel-3 images acquired between the 06th and the 09th of June 2023. Within the analysed area of 19,000 km², about 620 km² of land appear to be flooded. Based on Worldpop population data from 2020 and the flood water extent, ~110,000 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 the United Nations Satellite Centre (UNOSAT). Important note: Population data used for this estimate is from 2020. Current population count is not available.

**UNOSAT code FL20230606UKR** This map illustrates satellite-detected surface waters using Sentinel-1 images acquired on the 09th of June 2023 at 15:36 UTC. Within the analysed area of 20,000 km², surface waters appear to have receded of about 220 km². 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 CE20220223UKR** This map illustrates a satellite imagery based building damage assessment in the city of Kremenchuk, Ukraine. Based on imagery collected on 29 June 2022, the analysis showed 26 structures with visible damage. Out of these, 1 is destroyed, 7 severely damaged, 3 moderately damaged and 15 possibly damaged. Inset 1 shows a building identified as severely damaged on 29 June 2022. While no complete count of buildings for Kremenchuk is available, an open source dataset, which is visibly incomplete, indicates at least 19,209 structures in the area. This analysis is based on visibly damaged structures as of 29 June 2022, as seen in marginally degraded satellite imagery affected by light clouds and other limiting factors. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).

**UNOSAT code FL20230606UKR** This map illustrates satellite-detected flood waters and affected structures over Solontsi Village and Pidlisne Village, Khersonskyi Region, Khersonska Oblast (Ukraine) as observed from a WorldView-3 image acquired on 7 June 2023 at 08:19 UTC; and ICEYE image acquired on 7 June 2023. Within the analysed area of 330 ha, about 97% (320 ha) of Solontsi Village area appears to be flooded and 1,070 structures are affected. About 3% (1 ha) of Pidlisne Village area appears to be flooded and 13 structures are potentially affected. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).

**UNOSAT code: CE20220223UKR** This map illustrates a satellite imagerybased Rapid Damage Building Assessment (RDBA) in the North of Kharkiv, Ukraine. The RDBA divides the area of interest into 500m x 500m cells, each of which is analyzed to determine whether or not there are damaged buildings inside the cell. Based on imagery collected on 21, 22 and 23 March 2022, analysts found that 72 cells out of 1,866 cells in the North of Kharkiv sustained visible damage. This represents approximately 4% of the cells over the city. This analysis is based on structures visibly damaged as of 21, 22 and 23 March 2022 as seen in marginally degraded satellite imagery affected by precipitation, seasonality, and other limiting factors. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes: - macroregion (admin-1 including region) - region (admin-2 including state, province, department, governorate) - macrocounty (admin-3 including arrondissement) - county (admin-4 including prefecture, sub-prefecture, regency, canton, commune) - localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb) The dataset also contains human settlement points and polygons for: - localities (city, town, and village) - neighbourhoods (borough, macrohood, neighbourhood, microhood) The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the README.md file for complete data source metadata. Refer to our blog post for explanation of field names. Data corrections can be proposed using Write Field, an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

**UNOSAT code: FL20200626UKR** This map illustrates satellite-detected surface waters in Ivano-Frankivska and Ternopilska Oblastof Ukraine as observed from a Sentinel-1 image acquired on 24 June 2020. Within the ana lyzed area of about 642 km2, a total of a bout 35 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 UNITAR-UNOSAT .

**UNOSAT code: CE20220223UKR** This map illustrates a satellite imagery based Rapid Damage Building Assessment (RDBA) in Sumy City, Ukraine. The RDBA divides the city into 500m x 500m cells, each of which is analyzed to determine whether or not there are damaged buildings inside the cell. Based on imagery collected on 20 and 22 March 2022, analysts found that 5 cells out of 1,111 cells sustained visible damage. This represents approximately 0.4% of the cells over the city. This analysis is based on structures visibly damaged as of 20 and 22 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 United Nations Satellite Centre (UNOSAT).

This dataset provides detailed information on road surfaces from OpenStreetMap (OSM), distinguishing between **paved** and **unpaved** roads across the region. Surface classification is derived using a hybrid deep learning approach. For methodological details, see: http://arxiv.org/abs/2410.19874 Recently, we also published a new country-level dataset based on PlanetScope satellite imagery with near-complete coverage of all arterial roads. It is available on HDX under the name Ukraine **Planet** Road Surface. The corresponding paper is available at: https://arxiv.org/abs/2512.04092 Road Surface Statistics Approximately 1.188 million km of roads are mapped in OSM in this region. Based on AI-derived estimates: - Paved roads: 0.1364 million km (11.4784%) - Unpaved roads: 0.1342 million km (11.2956%) About 0.9175 million km (77.226%) of road surface information is missing in OSM. To reduce this gap, the Mapillary-derived road surface dataset provides an additional 0.0 million km (0.0008%) of the missing surface information. Intended Use This dataset supports transportation planning, infrastructure analysis, climate emissions assessment, and GIS applications. AI Features - **pred_class**: Model-predicted surface class ("paved" or "unpaved") - **pred_label**: Binary label (0 = paved, 1 = unpaved) - **osm_surface_class**: Surface classification derived from OSM tags - **combined_surface_osm_priority**: Combined classification prioritizing OSM - **combined_surface_DL_priority**: Combined classification prioritizing DL prediction - **n_of_predictions_used**: Number of predictions used for estimation - **predicted_length**: Predicted length based on DL estimation (meters) - **DL_mean_timestamp**: Mean timestamp of predictions used OSM Attributes - **name** - **name:en** - **name:* (local language)** - **highway** - **surface** - **smoothness** - **width** - **lanes** - **oneway** - **bridge** - **layer** - **source** Urban Classification Attributes - **continent** - **country_iso_a2** - **urban** (0 = rural, 1 = urban) - **urban_area** - **osm_id** - **osm_type** Data Sources The dataset originates from OpenStreetMap (OSM) and is augmented with deep learning predictions based on Mapillary street-level imagery, combined with the GHSU Global Human Settlement Urban Layer 2019 and AFRICAPOLIS 2020 urban layer. More HeiGIT datasets: https://data.humdata.org/organization/heidelberg-institute-for-geoinformation-technology More information: https://heigit.org/ Contact: communications@heigit.org

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**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 14 March 2022 and 21 June 2021, analysts found that 773 out of 17,594 structures sustained visible damage in the AOI. This represents approximately 4% of the structures. Out of these, 62 are destroyed, 315 severely damaged, 321 moderately damaged and 75 possibly damaged. This includes 8 schools and 4 health facilities. This analysis is based on structures visibly damaged as of 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).

Ukraine administrative level 0-4 boundaries (COD-AB) dataset version 05. This dataset is structured into 4 levels: - Admin 1: 27 Oblast (Region) - Admin 2: 139 Raion (District) - Admin 3: 1769 Hromada (Community) - Admin 4: 29706 Settlement, partial coverage Note: This dataset is structured into 4 levels: - Admin 1: 27 oblast (region) with three exceptions - Admin 2: 139 raion (district) with three exceptions - Admin 3: 1769 hromada (community) with three exceptions - Admin 4: 29706 populated place (city, settlement or village), partial coverage Dates associated with this dataset: - 18 December 2025: dataset reviewed for accuracy and completeness - 01 September 2025: valid for use by the humanitarian community - 01 September 2025: last edit to the dataset before publishing Contributed by OCHA Ukraine. Quality assured, configured, and published by OCHA Field Information Services (FIS) and HDX. Part of the dataset: Global Subnational Administrative Boundaries

**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: CE20220223UKR** This map illustrates a satellite imagery-based Rapid Damage Building Assessment (RDBA) of the Mariupolska Hromada, Ukraine. The RDBA divides the city into 500m x 500m cells, each of which is analyzed to determine whether or not there are damaged buildings inside the cell. Based on imagery collected on 26 March 2022, analysts found that 556 cells out of 3,456 sustained visible damage. This represents approximately 16% of the cells over the Hromada. Note that not all 6,456 cells include buildings. Numerous craters are also visible in the fields but were not taken into account for this analysis. This analysis is based on structures visibly damaged as of 26 March 2022 as seen in marginally degraded satellite imagery affected by precipitation, seasonality, and other limiting factors. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).