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Found 14 result(s)
<<<!!!<<< This repository is no longer available. The Environmental Dataset Gateway (EDG) has provided access to EPA's Open Data resources. Metadata records contributed by EPA Regions, Program Offices, and Research Laboratories that link to geospatial and non-geospatial resources (e.g., data, Web services, or applications) are now discoverable through Data.gov. https://www.re3data.org/repository/r3d100010078 >>>!!!>>>
EarthWorks is a discovery tool for geospatial (a.k.a. GIS) data. It allows users to search and browse the GIS collections owned by Stanford University Libraries, as well as data collections from many other institutions. Data can be searched spatially, by manipulating a map; by keyword search; by selecting search limiting facets (e.g., limit to a given format type); or by combining these options.
Content type(s)
Results from time-series analysis of Landsat images in characterizing global forest extent and change from 2000 through 2016.
In keeping with the open data policies of the U.S. Agency for International Development (USAID) and Bill & Melinda Gates Foundation, the Cereal Systems Initiative for South Asia (CSISA) has launched the CSISA Data Repository to ensure public accessibility to key data sets, including crop cut data- directly observed, crop yield estimates, on-station and on-farm research trial data and socioeconomic surveys. CSISA is a science-driven and impact-oriented regional initiative for increasing the productivity of cereal-based cropping systems in Bangladesh, India and Nepal, thus improving food security and farmers’ livelihoods. CSISA generates data that is of value and interest to a diverse audience of researchers, policymakers and the public. CSISA’s data repository is hosted on Dataverse, an open source web application developed at Harvard University to share, preserve, cite, explore and analyze research data. CSISA’s repository contains rich datasets, including on-station trial data from 2009–17 about crop and resource management practices for sustainable future cereal-based cropping systems. Collection of this data occurred during the long-term, on-station research trials conducted at the Indian Council of Agricultural Research – Research Complex for the Eastern Region in Bihar, India. The data include information on agronomic management for the sustainable intensification of cropping systems, mechanization, diversification, futuristic approaches to sustainable intensification, long-term effects of conservation agriculture practices on soil health and the pest spectrum. Additional trial data in the repository includes nutrient omission plot technique trials from Bihar, eastern Uttar Pradesh and Odisha, India, covering 2012–15, which help determine the indigenous nutrient supplying ability of the soil. This data helps develop precision nutrient management approaches that would be most effective in different types of soils. CSISA’s most popular dataset thus far includes crop cut data on maize in Odisha, India and rice in Nepal. Crop cut datasets provide ground-truthed yield estimates, as well as valuable information on relevant agronomic and socioeconomic practices affecting production practices and yield. A variety of research data on wheat systems are also available from Bangladesh and India. Additional crop cut data will also be coming online soon. Cropping system-related data and socioeconomic data are in the repository, some of which are cross-listed with a Dataverse run by the International Food Policy Research Institute. The socioeconomic datasets contain baseline information that is crucial for technology targeting, as well as to assess the adoption and performance of CSISA-supported technologies under smallholder farmers’ constrained conditions, representing the ultimate litmus test of their potential for change at scale. Other highly interesting datasets include farm composition and productive trajectory information, based on a 20-year panel dataset, and numerous wheat crop cut and maize nutrient omission trial data from across Bangladesh.
The NSF-supported Program serves the international scientific community through research, infrastructure, data, and models. We focus on how components of the Critical Zone interact, shape Earth's surface, and support life. ARCHIVED CONTENT: In December 2020, the CZO program was succeeded by the Critical Zone Collaborative Network (CZ Net) https://criticalzone.org/
A planetary-scale platform for Earth science data & analysis. Google Earth Engine combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. Scientists, researchers, and developers use Earth Engine to detect changes, map trends, and quantify differences on the Earth's surface.
AgBase is a curated, open-source, Web-accessible resource for functional analysis of agricultural plant and animal gene products. Our long-term goal is to serve the needs of the agricultural research communities by facilitating post-genome biology for agriculture researchers and for those researchers primarily using agricultural species as biomedical models.
International Research Institute for Climate and Society (IRI) research focuses on climate, environmental monitoring, agriculture, health, water, and economic sectors in Africa, Asia and Pacific, and Latin America and Caribbean. The IRI data library is a freely accessible data repository and analysis tool. IRI allows users to view, manipulate, and download climate-related data sets through a standard web browser.
Web Soil Survey (WSS) provides soil data and information produced by the National Cooperative Soil Survey. It is operated by the USDA Natural Resources Conservation Service (NRCS) and provides access to the largest natural resource information system in the world. NRCS has soil maps and data available online for more than 95 percent of the nation’s counties and anticipates having 100 percent in the near future. The site is updated and maintained online as the single authoritative source of soil survey information.
CottonGen is a new cotton community genomics, genetics and breeding database being developed to enable basic, translational and applied research in cotton. It is being built using the open-source Tripal database infrastructure. CottonGen consolidates and expands the data from CottonDB and the Cotton Marker Database, providing enhanced tools for easy querying, visualizing and downloading research data.
UNAVCO promotes research by providing access to data that our community of geodetic scientists uses for quantifying the motions of rock, ice and water that are monitored by a variety of sensor types at or near the Earth's surface. After processing, these data enable millimeter-scale surface motion detection and monitoring at discrete points, and high-resolution strain imagery over areas of tens of square meters to hundreds of square kilometers. The data types include GPS/GNSS, imaging data such as from SAR and TLS, strain and seismic borehole data, and meteorological data. Most of these can be accessed via web services. In addition, GPS/GNSS datasets, TLS datasets, and InSAR products are assigned digital object identifiers.