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 Its content includes unique grey literature such as unpublished scientific and technical reports, theses, conference papers, government publications, and more.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 3841 - 3845 of 9579Models for assessment of actual evapotranspiration from remote sensing: theoretical basis
In the evaluation of the onset, severity and duration of situations of water stress and droughts, indicators based on processes with intensive use of remote sensing can be used. In the monitoring of agricultural activities as well as the management of water and forest resources, spatio-temporal distributions of information of actual evapotranspiration (ETact) are crucial. This work presents the theoretical aspects of spatio- temporal assessment of ETact process, from remote sensing and meteorological data.
Mapping impervious surface expansion using medium-resolution satellite image time series: a case study in the Yangtze River Delta, China
Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades.
Winter wheat mapping using temporal signatures of MODIS vegetation index data
Because most land-cover types have distinct seasonal changes and corresponding reflectance characteristics in remotely sensed images, the signatures in time-series data are useful for discriminating different land covers. Although temporal signatures have been used to classify different land-cover types, they have not been fully exploited to classify specific crops, and the influence of low resolution should be evaluated.
Using multiscale texture information from ALOS PALSAR to map tropical forest
This research investigated the ability of the Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) to map tropical forest in central Sumatra, Indonesia. The study used PALSAR 50 m resolution orthorectified HH and HV data. As land-cover discrimination is difficult with only two bands (HH and HV), we added textures as additional information for classification. We calculated both first- and second-order texture features and studied the effects of texture window size, quantization scale and displacement length on discrimination capability.