A drought/dzud monitoring system known as “DroughtWatch-Mongolia” has been officially handed over to Mongolia on 17 September by the United Nations Economic and Social Commission for Asia and the Pacific (UNESCAP) and the Institute of Remote Sensing and Digital Earth (RADI) of the Chinese Academy of Sciences.
DroughtWatch-Mongolia is a system based on satellite data which aims to provide real-time drought monitoring for disaster prevention and mitigation departments in Mongolia.
Following a request by Mongolia to UNESCAP to pilot its Regional Drought Mechanism, a project entitled, “Strengthening Mongolia's capacity to monitor and warn drought/dzud” was…
In order to encourage the targeted retrieval of space-based information and data by disaster risk reduction practitioners, content on the Portal is systematically enriched with metadata. For instance, data sources are marked up with data about their file type, satellite/sensor and spatial coverage and whether they relate to the disaster risk management or emergency response phase. The tool features a range of filters that draw on the metadata, thereby allowing users to narrow down their search, for example, filtering available GIS software by hazard type. This ensures that users efficiently find the content that is most relevant to them. At the same time, the Portal encourages the discovery of resources related to those accessed by the user, by providing links to them on the same page. This allows for contextualisation and highlights links between resources…
read moreBased on optical and radar images of different resolutions, UNOSAT products are also enriched with the available baseline GIS datasets and crowdsourcing data. Satellite-derived analysis performed by UNOSAT is delivered in the form of GIS Data, Static Maps, Live Web Maps, and Reports, and is then shared with a wide range of end-users such as UN Agencies, International Organizations, and Governments.
The Global Human Settlement (GHS) framework produces global open source spatial information about the human presence on the planet over time. This is in the form of built up maps, population density maps and settlement maps. This information is generated with evidence-based analytics and knowledge using new spatial data mining technologies. The framework uses heterogeneous data including global archives of fine-scale satellite imagery, census data, and volunteered geographic information. The data is processed fully automatically and generates analytics and knowledge reporting objectively and systematically about the presence of population and built-up infrastructures.
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