Проекты
Project
System for earth observations, data access, processing & analysis for land monitoring (SEPAL) (на английском языке)
SEPAL is a system for earth observations, data access, processing & analysis for land monitoring. It is a free and open source cloud computing platform for geo-spatial data access and processing that empowers users to quickly process large amounts of data on their computer or mobile device. Users can create custom analysis ready data using freely available satellite imagery, generate and improve land use maps, analyze time series, run change detection and perform accuracy assessment and area estimation.
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FAOSTAT (на английском языке)
FAOSTAT provides free access to food and agriculture data for over 245 countries and territories and covers all FAO regional groupings from 1961 to the most recent year available.
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Earth Map (на английском языке)
Earth Map (earthmap.org) is a web-based FAO-Google tool for quick multi-temporal analysis of environment and climate parameters for evidence-based policies integrating cloud technologies and freely available datasets. Earth Map can analyse and display data that are already present in Google Earth Engine (earthengine.google.com) as other freely available datasets that have been gathered, processed and uploaded to the platform. Data domains range from temperature to precipitation, fires, population, vegetation, evapotranspiration, water, land use/cover, elevation, soil, satellite images, etc.
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Global Livestock Environmental Assessment Model (GLEAM) (на английском языке)
The Global Livestock Environmental Assessment Model is a GIS framework that simulates the bio-physical processes and activities along livestock supply chains under a life cycle assessment approach. The aim of GLEAM is to quantify production and use of natural resources in the livestock sector and to identify environmental impacts of livestock in order to contribute to the assessment of adaptation and mitigation scenarios to move towards a more sustainable livestock sector. The model can operate at (sub) national, regional and global scale and it is designed to analyze multiple environmental dimensions, such as feed use, greenhouse gas emissions, land use and land degradation, nutrient and water use and interaction with biodiversity.
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Agricultural Stress Index System (ASIS) (на английском языке)
Agricultural Stress Index System (ASIS) is a global agricultural drought monitoring system developed and operated by FAO which enables to monitor agricultural areas affected by dry spells, or severe drought in extreme cases, using satellite data. It provides a collective quick-look indicators that facilitate the early identification of cropland/grassland with a high likelihood of water stress (drought). ASIS related products (maps, spatial aggregation based on administrative unit) are processed by FAO GIEWS (Global Information and Early Warning System on Food and Agriculture) every 10 days.
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FAO Data Lab (на английском языке)
The Data Lab contributes to the Hand-in-Hand (HiH) Initiative,to enable “matchmaking” between countries with the highest poverty and hunger rates and the countries that are able to offer support. The HiH Initiative is characterised by data-intensive tasks like identifying bottlenecks and investment gaps, and developing a detailed monitoring and evaluation framework to assess the impact of its action by 2030. At the core of this initiative is the need to conduct complex analysis on cross-domain data, aggregating and enriching the existing information from non-conventional sources.
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National Forest Monitoring System (NFMS) (на английском языке)
FAO has supported more than 50 countries in their development of robust National Forest Monitoring Systems (NFMS) and assessments, with the goal of developing reliable forest resource information for application in creating national forest policies, planning and sustainable development. Forest monitoring systems include measurement, reporting and verification (MRV) functions and aim to produce high-quality, reliable data on forests, including forest-carbon estimates, that are critical to the battle against climate change caused by among others deforestation and degradation of forests.
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Global Soil Partnership (GSP) (на английском языке)
The Global Soil Partnership (GSP) is a globally recognized mechanism established in 2012. Its mission is to position soils in the Global Agenda through collective action. From land users through to policy makers, the key objectives are to promote Sustainable Soil Management (SSM) and improve soil governance to guarantee healthy and productive soils, and support the provision of essential ecosystem services towards food security and improved nutrition, climate change adaptation and mitigation, and sustainable development.
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Global Agro-Ecological Zoning version 4 (GAEZ v4) (на английском языке)
The AEZ methodology was implemented to assess the capacity of the world's natural resources to meet the needs for food of a fast-growing global population, particularly in developing countries.
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Land Cover Legend Registry (LCLR) (на английском языке)
The Land Cover Legend Registry (LCLR) provides access to available land cover legends used to describe land cover. The description of the land cover classes have been extracted from the original documents. Several of them were prepared using LCCS.v2 and/or LCCS.v3 tool, a user-friendly metadata tool, applying Land Cover Meta Language (LCML) with a graphical user friendly interface that allows the classification of the land cover features in a comprehensive system. When available, the link to the land cover map on FAO GeoNetwork and FAO HiH is provided.
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Climate Risk Toolbox (CRTB) (на английском языке)
The Climate Risk Toolbox (CRTB) allows users to conduct climate risk screenings in a few steps, and to obtain a comprehensive report that includes climate-resilient measures and tailored recommendations to prevent and reduce climate risk.
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Climate Information Tool (CWR) (на английском языке)
The Climate Information Tool is an interactive tool to query a spatial dataset containing long-term mean monthly climate data. The dataset covers the global land surface at a 10 minute spatial resolution for the period 1961-1990. The tool displays the latitude, longitude and elevation of the chosen location, and several climate variables per month (average over the period 1961-1990) related to: precipitation, temperature, relative humidity, sunshine, wind speed, reference evapotranspiration.
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Crop Calendar (на английском языке)
The Crop Calendar is a tool that provides timely information about seeds to promote local crop production. It contains information on planting, sowing and harvesting periods of locally adapted crops in specific agro-ecological zones. It also provides information on the sowing rates of seed and planting material and the main agricultural practices.
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Desert Locust Monitoring, Forecasting and Assessment (на английском языке)
FAO closely monitors the global Desert Locust situation 24/7 and provides forecasts, early warning and alerts on the timing, scale and location of invasions and breeding through its global Desert Locust Information Service (DLIS). All locust-affected countries transmit locust data to FAO who in turn analyse this information in conjunction with weather and habitat data and satellite imagery in order to assess the current locust situation, provide forecasts up to six weeks in advance and issue warnings on an ad-hoc basis.
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Global Forest Resources Assessments (FRA) (на английском языке)
The Global Forest Resources Assessments (FRA) are produced every five years in an attempt to provide a consistent approach to describing the world’s forests and how they are changing. The Assessments are based on two primary sources of data: Country Reports prepared by National Correspondents and remote sensing that is conducted by FAO together with national focal points and regional partners.These assessments make an interesting history of global forest interests, both in terms of their substantive content, but also in their changing scope.
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Food Price Monitoring and Analysis (FPMA) Domestic Market Prices (на английском языке)
FPMA provides the latest information and analysis on domestic prices of basic foods mainly in developing countries, complementing FAO analysis on international markets. It also provides early warning on high food prices at country level that may negatively affect food security.
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Rift Valley fever (RVF) Early Warning Decision Support Tool (RVF DST) (на английском языке)
The web-based Rift Valley fever (RVF) Early Warning Decision Support Tool (RVF DST) integrates near real-time RVF risk maps with geospatial data and expert knowledge on RVF eco-epidemiology. The tool is used to build capacity for early warning and forecasting at country level, and demonstrates how near real-time modelling, risk forecasting and digital innovation can enhance preparedness and anticipatory actions. In addition, the tool offers expert knowledge on RVF eco-epidemiology (such as the FAO–International Livestock Research Institute Decision Support Framework), risk assessment and categorization, analytical functions and charts of trends in major risk factors, as well as recommended actions to guide appropriate responses to RVF at country level.
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FAO Global Animal Disease Information System (EMPRES-i) (на английском языке)
EMPRES Global Animal Disease Information System (EMPRES-i) supports veterinary services by facilitating the organization and access to regional and global disease information.
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Gridded Livestock of the World Project (GLW) (на английском языке)
As a contribution to redressing the shortfall of informed decision-making on the challenges facing the livestock sector, and in collaboration with the Environmental Research Group Oxford (ERGO), FAO has developed the “Gridded livestock of the world” peer reviewed spatial database: the first standardized global, subnational resolution maps of the major agricultural livestock species. These data find applications in the fields of food and nutrition security; livelihoods and economic growth; human and animal health and welfare; and natural resources and environment.
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Integrated Food Security Phase Classification (IPC) (на английском языке)
The Integrated Food Security Phase Classification (IPC) is an innovative multi-partner initiative for improving food security and nutrition analysis and decision-making. By using the IPC classification and analytical approach, Governments, UN Agencies, NGOs, civil society and other relevant actors, work together to determine the severity and magnitude of acute and chronic food insecurity, and acute malnutrition situations in a country, according to internationally-recognised scientific standards.
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