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Community Organizations AGRIS
AGRIS
AGRIS
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What is AGRIS?

 

AGRIS (International System for Agricultural Science and Technology) is a global public database providing access to bibliographic information on agricultural science and technology. The database is maintained by CIARD, and its content is provided by participating institutions from all around the globe that form the network of AGRIS centers (find out more here).  One of the main objectives of AGRIS is to improve the access and exchange of information serving the information-related needs of developed and developing countries on a partnership basis.

 

AGRIS contains over 8 million bibliographic references on agricultural research and technology & links to related data resources on the Web, like DBPedia, World Bank, Nature, FAO Fisheries and FAO Country profiles.  

 

More specifically

 

AGRIS is at the same time:

 

A collaborative network of more than 150 institutions from 65 countries, maintained by FAO of the UN, promoting free access to agricultural information.

 

A multilingual bibliographic database for agricultural science, fuelled by the AGRIS network, containing records largely enhanced with AGROVOCFAO’s multilingual thesaurus covering all areas of interest to FAO, including food, nutrition, agriculture, fisheries, forestry, environment etc.

 

A mash-up Web application that links the AGRIS knowledge to related Web resources using the Linked Open Data methodology to provide as much information as possible about a topic within the agricultural domain.

 

Opening up & enriching information on agricultural research

 

AGRIS’ mission is to improve the accessibility of agricultural information available on the Web by:

 

 

 

 

  • Maintaining and enhancing AGRIS, a bibliographic repository for repositories related to agricultural research.
  • Promoting the exchange of common standards and methodologies for bibliographic information.
  • Enriching the AGRIS knowledge by linking it to other relevant resources on the Web.

AGRIS is also part of the CIARD initiative, in which CGIARGFAR and FAO collaborate in order to create a community for efficient knowledge sharing in agricultural research and development.

 

AGRIS covers the wide range of subjects related to agriculture, including forestry, animal husbandry, aquatic sciences and fisheries, human nutrition, and extension. Its content includes unique grey literature such as unpublished scientific and technical reports, theses, conference papers, government publications, and more. A growing number (around 20%) of bibliographical records have a corresponding full text document on the Web which can easily be retrieved by Google.

 

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Resources

Displaying 2716 - 2720 of 9579

new Likelihood Ratio for supervised classification of fully polarimetric SAR data: An application for sea ice type mapping

Journal Articles & Books
Dezembro, 2013

One of the potential applications of polarimetric Synthetic Aperture Radar (SAR) data is the classification of land cover, such as forest canopies, vegetation, sea ice types, and urban areas. In contrast to single or dual polarized SAR systems, full polarimetric SAR systems provide more information about the physical and geometrical properties of the imaged area. This paper proposes a new Bayes risk function which can be minimized to obtain a Likelihood Ratio (LR) for the supervised classification of polarimetric SAR data.

Validating the geometric accuracy of high spatial resolution multispectral satellite data

Journal Articles & Books
Dezembro, 2013
Estados Unidos

Uses of high spatial resolution data obtained from satellite-based sensors include creating land cover maps, deriving large-scale quantitative assessments such as vegetation indices, and visually assessing an area for qualitative information only assessable from large-scale digital data. One of the more popular uses of high spatial resolution data is to use the image as a base map for on-screen digitizing spatially dependent vector products.

Role-playing game developed from a modelling process: A relevant participatory tool for sustainable development? A co-construction experiment in an insular biosphere reserve

Journal Articles & Books
Dezembro, 2013
França

This contribution refers to a companion modelling approach applied to the study of interactions between social and environmental dynamics in a small protected island, part of a biosphere reserve. This approach leads to a role-playing game designed by a pluridisciplinary workgroup (researchers and reserve manager), used as management support and as a tool to help people regarding the stakes of sustainable development. For several years, Ushant Island (Brittany, France) was in the process of social and environmental restructuration due to land-use and land-cover changes.

Temporal logic and operation relations based knowledge representation for land cover change web services

Journal Articles & Books
Dezembro, 2013

Providing land cover spatio-temporal information and geo-computing through web service is a new challenge for supporting global change research, earth system simulation and many other societal benefit areas. This requires an integrated knowledge representation and web implementation of static land cover and change information, as well as the related operations for geo-computing. The temporal logic relations among land cover snapshots and increments were examined with a matrix-based three-step analysis.

Land cover and impervious surface extraction using parametric and non-parametric algorithms from the open-source software R: an application to sustainable urban planning in Sicily

Journal Articles & Books
Dezembro, 2013
Itália

Detailed urban land-cover maps are essential information for sustainable planning. Land-cover maps assist planners in designing strategies for the optimisation of urban ecosystem services and climate change adaptation. In this study, the statistical software R was applied to land cover analysis for the Catania metropolitan area in Sicily, Italy. Six land cover classes were extracted from high-resolution orthophotos. Five different classification algorithms were compared. Texture and contextual layers were tested in different combinations as ancillary data.