Viet Nam GIS data

**UNOSAT code: TC20201028VNM** This map illustrates satellite-detected surface waters in Ha Tinh Province of Viet Nam as observed from a SAOCOM-1A image acquired on 3 November 2020 at about 16:52 local time. Within the analyzed area of about 5,800 km2, a total of about 580 km2 of lands appear to be flooded. The water extent appears to have increased of about 80 km2 since 30 October 2020. Based on Worldpop population data and the detected surface waters, about 260,000 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 UNITAR-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: TC20250826VNM** This map illustrates the satellite detected water extent in Northern part of Viet Nam as observed from Sentinel-1 satellite images acquired on 26 August 2025 at 05:51 local time (22:51 UTC). Within the analyzed area of approximately 74,000 km², about 1,200 km² of land appears to be affected by floodwaters. Based on WorldPop population data and the flood extent, approximately 708,000 people are potentially exposed or living close to the 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: TC20201013VNM** This map illustrates satellite-detected surface waters in Ha Tinh and Nghe An Provinces of Viet Nam as observed from a Sentinel-1 image acquired on 21 October 2020. Within the analyzed area of about 8,000 km2, a total of about 300 km2 of lands appear to be flooded. In Ha Tinh province, the water extent appears to have receded of about 200 km2 since 18 October 2020. Based on Worldpop population data and the detected surface waters, about 100,000 people are potentially exposed or living close to flooded areas. The potentially exposed population is mainly located in the districts of Cam Xuyen with ~15,000 people, Can Loc with ~15,000 people and Thach Ha with ~15,000 people. 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 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: TC20201028VNM** This map illustrates satellite-detected surface waters in Thua Thien Hue Province of Viet Nam as observed from a Sentinel-1 image acquired on 10 November 2020 at 05:43 local time. Within the analyzed area of about 5,000 km2, a total of about 200 km2 of lands appear to be flooded. The water extent appears to have increased of about 50 km2 since 4 November 2020. Based on Worldpop population data and the detected surface waters, about 65,000 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 UNITAR-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.

**ADAM ID: **1001199\_13 Category 1 during the period Aug 22 2025-Aug 25 2025 in China, Viet Nam, Laos. The center of the storm was located near latitude 18.6 longitude 105.7. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

**ADAM ID: **1001202\_10 Tropical depression during the period Aug 28 2025-Aug 30 2025 in Viet Nam, China, Laos, Thailand. The center of the storm was located near latitude 18.0 longitude 104.4. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

**ADAM ID: **1001214\_22 Category 1 during the period Sep 23 2025-Sep 28 2025 in Viet Nam, Philippines, Laos. The center of the storm was located near latitude 18.2 longitude 106.2. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

**ADAM ID: **1001219\_19 Category 1 during the period Oct 01 2025-Oct 05 2025 in China, Viet Nam, Philippines. The center of the storm was located near latitude 21.9 longitude 108.5. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

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 Viet Nam **Planet** Road Surface. The corresponding paper is available at: https://arxiv.org/abs/2512.04092 Road Surface Statistics Approximately 0.8443 million km of roads are mapped in OSM in this region. Based on AI-derived estimates: - Paved roads: 0.0657 million km (7.7851%) - Unpaved roads: 0.081 million km (9.594%) About 0.6975 million km (82.6209%) of road surface information is missing in OSM. To reduce this gap, the Mapillary-derived road surface dataset provides an additional 0.0123 million km (1.764%) 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

**UNOSAT code: TC20201028VNM** This map illustrates satellite-detected surface waters in Binh Dinh Province of Viet Nam as observed from a Sentinel-1 image acquired on 30 October 2020 at about 05:35 local time. Within the analyzed area of about 6,000 km2, a total of about 70 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 30,000 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 UNITAR-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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**ADAM ID: **1001281\_13 Tropical storm during the period Jul 01 2026-Jul 04 2026 in Viet Nam, China, Laos. The center of the storm was located near latitude 21.6 longitude 107.9. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

**UNOSAT code: TC20201028VNM** This map illustrates satellite-detected surface waters in Thua Thien Hue Province of Viet Nam as observed from a Sentinel-1 image acquired on 4 November 2020 at about 05:43 local time. Within the analyzed area of about 4,700 km2, a total of about 150 km2 of lands appear to be flooded. The water extent appears to have receded of about 120 km2 since 29 October 2020. Based on Worldpop population data and the detected surface waters, about 40,000 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 UNITAR-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: TC20201028VNM** This map illustrates satellite-detected surface waters in Quang Ngai Province of Viet Nam as observed from a Sentinel-1 image acquired on 30 October 2020. Within the analyzed area of about 5,000 km2, a total of about 90 km2 of lands appear to be flooded. The water extent appears to have increased of about 80 km2 since 25 October 2020. Based on Worldpop population data and the detected surface waters, about 53,000 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 UNITAR-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: TC20201013VNM** This map illustrates satellite-detected surface waters in Minh Hoa and Tuyen Hoa district, Quang Binh province of Viet Nam as observed from a Kompsat-5 image acquired on 19 October 2020. Within the analyzed area of about 900 km2, a total of about 30 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 6,500 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 UNITAR-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: TC20201028VNM** This map illustrates satellite-detected surface waters in Thua Thien Hue Province of Viet Nam as observed from a Sentinel-1 image acquired on 29 October 2020 at about 05:43 local time. Within the analyzed area of about 5,000 km2, a total of about 270 km2 of lands appear to be flooded. The water extent appears to have increased of about 40 km2 since 25 October 2020. Based on Worldpop population data and the detected surface waters, about 100,000 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 UNITAR-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.

**ADAM ID: **1001307\_21 Tropical depression during the period Aug 20 2026-Aug 25 2026 in Viet Nam, China. The center of the storm was located near latitude 20.0 longitude 109.6. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

**UNOSAT code: TC20201028VNM** This map illustrates satellite-detected surface waters in Quang Tri Province of Viet Nam as observed from a Sentinel-1 image acquired on 29 October 2020 at about 05:43 local time. Within the analyzed area of about 4,600 km2, a total of about 230 km2 of lands appear to be flooded. The water extent appears to have increased of about 90 km2 since 25 October 2020. Based on Worldpop population data and the detected surface waters, about 65,000 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 UNITAR-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.

# EOS-RS Flood Proxy Map: Hanoi, Vietnam, Floods, 23 September 2026, v0.8 The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Flood Proxy Map (FPM) depicting areas that are likely flooded in Hanoi, Vietnam after heavy rainfall. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellite operated by the European Space Agency (ESA) before (12 Dec 2025 to 09 September 2026) and during (21 September 2026) the event. The map covers an area indicated by the white polygon. The preliminary map shows areas which are likely flooded (shown by light blue pixels of approximately 30m in size) due to the heavy rainfall. Preliminary validation was conducted using news reports and ground-level imagery in selected areas. This map should be used as a guide to identify areas that are likely flooded, and may be less reliable over urban and vegetated areas. This product contains modified Copernicus Sentinel data (2026), processed by ESA and analyzed by the Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS). **More map details and files:** **Legal Disclaimer:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Contains modified Copernicus Sentinel data (2026)

# EOS-RS Damage Proxy Map: North Central, Vietnam, Floods, 01 Oct 2025, v0.9 The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Damage Proxy Map (DPM) depicting areas that are likely damaged in North Central, Vietnam, due to typhoon Bualoi. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellite operated by the European Space Agency (ESA) before (27 Jul 2025 to 25 Sep 2025) and after (01 Oct 2025) the event. The map covers an area indicated by the white polygon. Damage is shown by colored pixels of 30m in size, where yellow to red indicates increasingly significant ground surface change before and after the event. Preliminary validation was conducted using news reports, and ground-level imagery in selected areas. This map should be used as a guidance to identify damaged areas, and may be less reliable over vegetated or mountainous areas. Scattered pixels over vegetated or mountainous areas may be false positives, and a lack of colored pixels over such areas may not mean no damage. This product contains modified Copernicus Sentinel data (2025), processed by ESA and analyzed by the Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS). **More map details and files:** **More map details and files:** leaflet/EOS-RS_202510_Vietnam_North_Central_Typhoon_Bualoi_Floods **Legal Disclaimer:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Contains modified Copernicus Sentinel data (2025)

# EOS-RS Flood Proxy Map: North Central Vietnam, Tropical Storm Trami Floods, 28 Oct 2024, v0.9 The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Flood Proxy Map (FPM) depicting areas that are likely flooded in North Central Vietnam due to heavy rainfall from Tropical Storm Trami. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellite operated by the European Space Agency (ESA) before (14 Jan 2024 to 4 Oct 2024) and during (28 Oct 2024) the event. The map covers an area indicated by the white polygon. The preliminary map shows areas which are likely flooded (shown by light blue pixels of approximately 30m in size) due to the heavy rainfall from Tropical Storm Trami. Preliminary validation was conducted using news reports, aerial imagery, and ground-level imagery in selected areas. This map should be used as a guide to identify areas that are likely flooded, and may be less reliable over urban and vegetated areas. This product contains modified Copernicus Sentinel data (2024), processed by ESA and analyzed by the Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS). **More map details and files:** **More map details and files:** **Legal Disclaimer:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Contains modified Copernicus Sentinel data (2024)

The International Best Track Archive for Climate Stewardship (IBTrACS) project is the most complete global collection of tropical cyclones available. It merges recent and historical tropical cyclone data from multiple agencies to create a unified, publicly available, best-track dataset that improves inter-agency comparisons. Fields available: SID: A unique storm identifier (SID) assigned by IBTrACS algorithm. ISO_TIME: Time of the observation in ISO format (YYYY-MM-DD hh:mm:ss) BASIN: Basin of the current storm position SUBBASIN: Sub-basin of the current storm position NATURE: Type of storm (a combination of the various types from the available sources) NUMBER: Number of the storm for the year (restarts at 1 for each year LAT: Mean position - latitude (a combination of the available positions) LON: Mean position - longitude (a combination of the available positions) WMO_WIND: Maximum sustained wind speed assigned by the responsible WMO agency WMO_PRES: Minimum central pressure assigned by the responsible WMO agency.

**UNOSAT code: TC20201028VNM** This map illustrates satellite-detected surface waters in Quang Binh Province of Viet Nam as observed from a Sentinel-1 image acquired on 29 October 2020 at about 05:43 am local time. Within the analyzed area of about 6,000 km2, a total of about 250 km2 of lands appear to be flooded. The water extent appears to have increased of about 40 km2 since 24 October 2020 Based on Worldpop population data and the detected surface waters, about 70,000 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 UNITAR-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: TC20201013VNM** This map illustrates satellite-detected surface waters in Quang Nam Province of Viet Nam as observed from a Radarsat Constellation 1 image acquired on 17 October 2020. Within the analyzed area of about 6,000 km2, a total of about 135 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 84,000 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 UNITAR-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: TC20201013VNM** This map illustrates satellite-detected surface waters in Ha Tinh and Nghe An Provinces of Viet Nam as observed from a Sentinel-1 image acquired on 18 October 2020. Within the analyzed area of about 9,000 km2, a total of about 500km2 of lands appear to be flooded. In Ha Tinh province, the water extent appears to have increased of about 300 km2 since 15 October 2020. Based on Worldpop population data and the detected surface waters, about 220,000 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 UNITAR-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: TC20201013VNM** This map illustrates satellite-detected surface waters in Quang Binh Province of Viet Nam as observed from a Sentinel-1 image acquired on 22 October 2020. Within the analyzed area of about 6,000 km2, a total of about 230 km2 of lands appear to be flooded. The water extent appears to have receded of about 190 km2 since 18 October 2020. Based on Worldpop population data and the detected surface waters, about 55,000 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 UNITAR-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.