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 AGROVOC, FAO’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 CGIAR, GFAR 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 Its content includes unique grey literature such as unpublished scientific and technical reports, theses, conference papers, government publications, and more.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.
Members:
Resources
Displaying 2281 - 2285 of 9579Do Ponds on Golf Courses Provide Suitable Habitat for Wetland-Dependent Animals in Suburban Areas? An Assessment of Turtle Abundances
Golf courses represent a common type of anthropogenically modified habitat in suburban environments. Golf courses may provide suitable habitat for semi-aquatic animals in suburban areas, yet studies comparing animal abundances in golf course ponds with other pond types in suburban environments are somewhat limited. In this study, we compared turtle abundances in golf course ponds with ponds found in residential areas and ponds found in rural (farm) areas and examined the relationship between turtle abundance and residential land-cover within individual golf courses.
Estimating net surface longwave radiation from net surface shortwave radiation for cloudy skies
This work addresses the estimation of net surface longwave radiation (NSLR) from net surface shortwave radiation (NSSR) by analysing the Surface Radiation Budget Network (SURFRAD) radiation data under cloudy conditions. A general model is developed to estimate NSLR from the NSSR for cloudy skies with a root mean square error (RMSE) of 23.16 W m⁻² compared with in situ data. The model is applied to AmeriFlux data. The results show that the mean error and RMSE are –2.31 W m⁻² and 29.25 W m⁻², respectively, compared with the measurement of AmeriFlux.
Multiple SVM System for Classification of Hyperspectral Remote Sensing Data
With recent technological advances in remote sensing sensors and systems, very high-dimensional hyperspectral data are available for a better discrimination among different complex land-cover classes. However, the large number of spectral bands, but limited availability of training samples creates the problem of Hughes phenomenon or ‘curse of dimensionality’ in hyperspectral data sets. Moreover, these high numbers of bands are usually highly correlated.
RGB-NDVI color composites for monitoring the change in mangrove area at the Maubesi Nature Reserve, Indonesia
The Maubesi Nature Reserve (MNR) is a protected lowland area in eastern Indonesia that mainly consists of mangrove forest. The objective of this paper was to demonstrate a simple technique to visualize and quantify the change in mangrove area using a 3-year dataset of Landsat TM images acquired in 1989, 2003 and 2009. The normalized difference vegetation index (NDVI) was calculated to determine high and low vegetation biomass in each image.
Benefits of earth observation data for conservation planning in the case of European wetland biodiversity
To evaluate the status of biodiversity and to determine how current conservation efforts can be improved, biodiversity monitoring is crucial. An important aspect of data quality lies in its spatial resolution. It is unclear how finer scale land cover and land value information might further benefit biodiversity conservation. This paper aimed to assess the impacts of scale by modelling the conservation of endangered European wetland species and their corresponding habitats. Fine-scale datasets were derived by integrating existing geographical, biophysical and economic data.