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 Its content includes unique grey literature such as unpublished scientific and technical reports, theses, conference papers, government publications, and more.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 2296 - 2300 of 9579Carbon sequestration and water use of a young hybrid poplar plantation in north-central Alberta
Hybrid poplar (HP) is an important fast-growing crop with the potential to provide a reliable supply of biomass for the pulp and bioenergy industries while also sequestering carbon (C) in the soil. We used the eddy-covariance technique to measure CO₂, water vapor and sensible heat fluxes above a three-year-old HP plantation on high productivity land near St Albert, Alberta. Measurements showed that the annual C balance of the plantation shifted from a C source of about 1.54 Mg C ha⁻¹ y⁻¹ in the 2nd year (2010) to a C sink of 0.80 Mg C ha⁻¹ y⁻¹ in the 3rd year (2011).
Landscape functionality in protected and unprotected areas: Case studies from the Czech Republic
Landscape structure not only reflects the natural settings of the landscape but also its history and the impact of human activity. Information about the characteristics of the landscape elements in terms of their structural functionality plays a central role in assessing their ecological quality. Statutory designation of sites plays a key role in conserving and maintaining valuable parts of the landscape. In this study, we investigated whether protection status influences functionality in case studies from the Czech Republic, representing three different landscape types.
Improving change vector analysis by cross-correlogram spectral matching for accurate detection of land-cover conversion
Time series of vegetation index (VI) information derived from remote sensing is important for land-cover change detection. Although traditional change vector analysis (TCVA) is an effective method for extracting land-cover change information from a time series of VI data, it has the disadvantage of being too sensitive to temporal fluctuations in VI values. The method tends to overestimate the changes and confuse the actual land-cover conversion with the land covers that have not been converted but experience significant VI changes.
Land-use and land-cover change detection in a semi-arid area of Niger using multi-temporal analysis of Landsat images
Recent studies using low-resolution satellite time series show that the Sahelian belt of West Africa is witnessing an increase in vegetation cover/biomass, called re-greening. However, detailed information on local processing and changes is rare or lacking. A multi-temporal set of Landsat images was used to produce land-cover maps for the years 2000 and 2007 in a semi-arid region of Niger, where an anomalous vegetation trend was previously detected.
Feature extraction for high-resolution imagery based on human visual perception
Feature extraction is highly important for classification of remote-sensing (RS) images. However, extraction of comprehensive spatial features from high-resolution imagery is still challenging, leading to many misclassifications in various applications. To address the problem, a shape-adaptive neighbourhood (SAN) technique is presented based on human visual perception. The SAN technique is an adaptive feature-extraction method that not only considers spectral feature information but also the spatial neighbourhood as well as the shape of features.