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 Its content includes unique grey literature such as unpublished scientific and technical reports, theses, conference papers, government publications, and more.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 4561 - 4565 of 9579multigradient algorithm using a mixture of experts architecture for land cover classification of multisensor images
An algorithm for supervised classification of multisensor images is proposed. The mixture of experts (ME) architecture with dynamic weight allocation is used for multiclass classification. Here the classification is treated as a maximum likelihood problem and the synaptic weights of the expert network and gating network are updated by a stochastic multigradient approach. Data from an optical sensor with four bands and a synthetic aperture radar (SAR) image of the same scene has been fused and classified.
Mapping fuel moisture codes using MODIS images and the Getis statistic over western Canada grasslands
In Canada, fire danger is predicted by the Canadian Forest Fire Danger Rating System (CFFDRS). One of its subsystems is the Canadian Fire Weather Index (FWI) system, which has two slow-drying fuel moisture codes: the drought code (DC) and the duff moisture code (DMC). Both codes are used in this study as a surrogate of dead fuel moisture. We evaluate the capability of Moderate Resolution Imaging Spectrometer (MODIS) observations to map DC and DMC.
Integrated Assessment Modelling of Complexity in the New Zealand Farming Industry
As New Zealand farming industry pursues more productivity this has implication for environment and makes land use and agricultural policy decision processes more complex for which integrated assessment modeling (IAM) can support. The purpose of this review paper is to propose means through which IAM can be improved specifically to minimize uncertainties and increase relevance, reliability, and utility of outputs of different models. Literature suggests that the general motivation for land use change is that farmers do consider the environment, but need to maintain profitability.
impacts of climate change on Australia and New Zealand: a Gross Cell Product analysis by land cover
This paper examines the newly constructed geographically scaled economic output measure, Gross Cell Product (GCP), of Australia and New Zealand to quantify the impacts of climate change in the region. The paper discusses advantages of using the GCP instead of the Gross Domestic Product. The paper reveals that the GCP falls sharply as temperature increases in the region. A 1°C increase in temperature would decrease the productivity with an elasticity of −2.4. A 1 per cent decrease in precipitation would decrease productivity with an elasticity of −2.3.
International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements
In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, longterm time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol.