5 datasets found

This map illustrates the structures/buildings damaged by Tropical Cyclone MELISSA-25. The analysis focuses on Crawford Village, Black River District, Saint Elizabeth Parish, as of 29 October 2025, where damage was detected using a WorldView-2 very high-resolution satellite image acquired on 29 October 2025. UNOSAT identified approximately 1,089 buildings as 100% damaged.

This is a preliminary analysis and has not yet been validated in the field. Ground verification is encouraged, and feedback can be sent to the United Nations Satellite Centre (UNOSAT).

The MAR Portal contains the Global MAR Inventory, an inventory of over 1200 sites where Managed Aquifer Recharge is or has been implemented. The Global MAR Inventory includes information on site name, MAR type, year of scheme deployment, the source of infiltration water, the final use of abstracted water, as well as the main objectives of the project.

This dataset presents a MAR suitability map for Jordan, developed by Steinel et al. (2016). The study evaluates hydrogeological, climatic, and land use conditions to identify areas suitable for MAR implementation across the country. The dataset provides geospatial information that can support water resources planning, groundwater recharge strategies, and climate change adaptation measures in Jordan. It is part of the global collection of MAR suitability assessments compiled by IGRAC.

If you would like to contribute data to the MAR portal, please contact us at info@un-igrac.org.

This dataset, compiled by Solar Chapter's Mengalir.co initiative, provides essential information on water infrastructure and access across 22 regencies in Indonesia's East Nusa Tenggara province. The data captures key water access metrics, infrastructure status, and demographic information to support water resource management, development planning, and humanitarian efforts in this semi-arid region. The dataset includes geospatial coordinates, administrative divisions, population demographics, water facility operations, access metrics, infrastructure types, water sources, and management entities for each regency.

The data synthesizes information from national and local government records, community participatory reports, and partner organization databases in an accessible CSV format for stakeholders addressing regional water challenges. This collection effort aims to support better planning and implementation of water solutions in East Nusa Tenggara, where many communities experience seasonal water shortages.

This dataset illustrates satellite-detected mudflow extent in Sao Vicente, Cabo Verde as observed from Pleiades very high-resolution satellite image. About 12 km² of land appears to be affected by the flood / mudflow extent. UNOSAT identified around 4200 affected buildings with around 12600 people potentially affected. In addition, approximately 80 km of roads with 5 bridges were affected.

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).

The Randolph Glacier Inventory (RGI) is a globally complete inventory of glacier outlines (excluding the ice sheets in Greenland and Antarctica). It is a subset of the database compiled by the Global Land Ice Measurements from Space (GLIMS) initiative. While GLIMS is a multi-temporal database with an extensive set of attributes, the RGI is intended to be a snapshot of the world’s glaciers at a specific target date, which in RGI 7.0 and all previous versions has been set as close as possible to the year 2000 (although in fact its range of dates can still be substantial in some regions). The RGI includes outlines of all glaciers larger than 0.01 km², which is the recommended minimum of the World Glacier Inventory.

The RGI was not designed for the measurement of glacier-by-glacier rates of area change, for which the greatest possible accuracy in dating, delineation and georeferencing is essential. While many RGI outlines meet these requirements, the primary focus of the RGI is on achieving global coverage, consistency, and proximity in a specific year. The strength of the RGI lies in its ability to handle large numbers of glaciers simultaneously. This allows, for example, for the estimation of glacier volumes and rates of elevation change at regional and global scales, as well as the simulation of cryospheric responses to climatic forcing.

Who develops and hosts the RGI? The RGI has been developed in an international community-driven effort of glaciologists starting in 2010. The inventory was named after “Randolph”, a town in New Hampshire, USA, where the team met for one of their meetings [Pfeffer et al., 2014]. In 2014 development of the RGI became the responsibility of the Working Group on the Randolph Glacier Inventory and Infrastructure for Glacier Monitoring, which operated under the International Association of Cryospheric Sciences (IACS). In 2019, a new Working Group was established to build upon the previous achievements and further expand its objectives: the IACS Working Group on the Randolph Glacier Inventory (RGI) and its role in future glacier monitoring and GLIMS.

The RGI datasets are listed on glims.org, and the RGI files can be downloaded through the data portal at the National Snow and Ice Data Center (NSIDC), which is the host for GLIMS.

Glacier product: includes outlines, attributes and auxiliary data for each individual glacier.