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 Its content includes unique grey literature such as unpublished scientific and technical reports, theses, conference papers, government publications, and more.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 4096 - 4100 of 9579Testing the red edge channel for improving land-use classifications based on high-resolution multi-spectral satellite data
The incorporation of a red edge channel in multi-spectral satellite sensors has potential for improving land-use classification, as the related electromagnetic spectrum is specifically sensitive to vegetation chlorophyll content. RapidEye is the first high-resolution multi-spectral satellite system that operationally provides a red edge channel. The objective of this study is to test the potential of the RapidEye red edge channel for improving the classification of land use, investigated at a study site west of Berlin.
Unsupervised and supervised classification of hyperspectral imaging data using projection pursuit and Markov random field segmentation
This work presents a classification technique for hyperspectral image analysis when concurrent ground truth is either unavailable or available. The method adopts a principal component analysis (PCA)-based projection pursuit (PP) procedure with an entropy index for dimensionality reduction, followed by a Markov random field (MRF) model-based segmentation. An ordinal optimization approach to PP determines a set of ‘good enough projections’ with high probability, the best among which is chosen with the help of MRF model-based segmentation.
Towards a World Desertification Atlas. Relating and selecting indicators and data sets to represent complex issues
Mapping land degradation and desertification (LDD) at the global scale still is a conceptual and operational challenge. The present study has been performed in the frame of the WAD (new World Atlas of Desertification) initiative. The objective of the paper is to test a structured procedure to identify relevant indicators for an effective representation of complex global LDD issues, based on available data sets (both geo-spatial and statistical), and conform to the UNCCD (United Nations Convention to Combat Desertification) requirements.
Application of an evidential belief function model in landslide susceptibility mapping
The objective of this paper is to exploit the potential application of an evidential belief function model to landslide susceptibility mapping at Kuala Lumpur city and surrounding areas using geographic information system (GIS). At first, a landslide inventory map was prepared using aerial photographs, high resolution satellite images and field survey. A total 220 landslides were mapped and an inventory map was prepared. Then the landslide inventory was randomly split into a testing dataset 70% (153 landslides) and remaining 30% (67 landslides) data was used for validation purpose.
automated approach for updating land cover maps based on integrated change detection and classification methods
Updating land cover maps from remotely sensed data in a timely manner is important for many areas of scientific research. Unfortunately, traditional classification procedures are very labor intensive and subjective because of the required human interaction. Based on the strategy of updating land cover data only for the changed area, we proposed an integrated, automated approach to update land cover maps without human interaction.