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Found 11 result(s)
>>> the repository is offline <<< The Detection of Archaeological Residues using Remote-sensing Techniques (DART) project was initiated in 2010 in order to investigate the ability of various sensors to detect archaeological features in ‘difficult’ circumstances. Concluding in September 2013, DART had the overall aim of developing analytical methods for identifying and quantifying gradual changes and dynamics in sensor responses associated with surface and near-surface archaeological features under different environmental and land-management conditions.
Country
The GeoPortal.rlp allows the central search and visualization of geo data. Inside the geo data infrastructure of Rhineland-Palatinate the GeoPortal.rlp inherit the central duty a service orientated branch exchange between user and offerer of geo data. The GeoPortal.rlp establishes the access to geo data over the electronic network. The GeoPortal.rlp was brought on line on January, 8th 2007 for the first time, on February, 2nd 2011 it occured a site-relaunch.
Climate Data Record (CDR) is a time series of measurements of sufficient length, consistency and continuity to determine climate variability and change. The fundamental CDRs include sensor data, such as calibrated radiances and brightness temperatures, that scientists have improved and quality-controlled along with the data used to calibrate them. The thematic CDRs include geophysical variables derived from the fundamental CDRs, such as sea surface temperature and sea ice concentration, and they are specific to various disciplines.
The JPL Tropical Cyclone Information System (TCIS) was developed to support hurricane research. There are three components to TCIS; a global archive of multi-satellite hurricane observations 1999-2010 (Tropical Cyclone Data Archive), North Atlantic Hurricane Watch and ASA Convective Processes Experiment (CPEX) aircraft campaign. Together, data and visualizations from the real time system and data archive can be used to study hurricane process, validate and improve models, and assist in developing new algorithms and data assimilation techniques.
GRID-Geneva is a unique platform providing analyses and solutions for a wide range of environmental issues. GRID-Geneva serves primarily the needs of its three institutional partners - UNEP, the Swiss Federal Office for the Environment (FOEN) and the University of Geneva (UniGe) - which are linked by an ongoing, multi-year “Partnership Agreement”, along with other local-to-global stakeholders. GRID-Geneva is also a bilingual English and French centre and the key francophone link within the global GRID network of centres. GRID-Geneva is a key centre of geo-spatial know-how, with strengths in GIS, IP/remote sensing and statistical analyses, integrated through modern spatial data infrastructures and web applications. Working at the interface between scientific information and policy/decision-making, GRID-Geneva also helps to develop capacities in these fields of expertise among target audiences, countries and other groups.
EartH2Observe brings together the findings from European FP projects DEWFORA, GLOWASIS, WATCH, GEOWOW and others. It will integrate available global earth observations (EO), in-situ datasets and models and will construct a global water resources re-analysis dataset of significant length (several decades). The resulting data will allow for improved insights on the full extent of available water and existing pressures on global water resources in all parts of the water cycle. The project will support efficient and globally consistent water management and decision making by providing comprehensive multi-scale (regional, continental and global) water resources observations. It will test new EO data sources, extend existing processing algorithms and combine data from multiple satellite missions in order to improve the overall resolution and reliability of EO data included in the re-analysis dataset. The resulting datasets will be made available through an open Water Cycle Integrator data portal https://wci.earth2observe.eu/ : the European contribution to the GEOSS/WCI approach. The datasets will be downscaled for application in case-studies at regional and local levels, and optimized based on identified European and local needs supporting water management and decision making . Actual data access: https://wci.earth2observe.eu/data/group/earth2observe
Country
China Meteorological Data Service Center, an upgraded system of the meteorological data sharing network, is an important component of the underlying national science and technology platform and a main portal application system of meteorological cloud. It is an authoritative and unified shared service platform for China Meteorological Administration to open its meteorological data resources to domestic and global users, and a data supporting platform for China to open its meteorological service market and promote the sharing and efficient application of meteorological information resources as a new meteorological service system. The comprehensive meteorological database provide online and offline shared services, the existing data types including global upper-air sounding data, surface observations, ocean observations, numerical forecast products, agro-meteorological data of ground observation data encryption, aircraft soundings, numerical weather prediction analysis field data, GPS-Met, Storm 2 No, GOES-9 satellite data, soil moisture, aircraft reported sandstorm monitoring, TOVS, ATOVS, wind profilers, satellite detection information.
The LINZ Data Service provides free online access to New Zealand’s most up-to-date land and seabed data. The data can be searched, browsed and downloaded. The LINZ web services can be also integrated into other applications.
The NASA/GEWEX SRB project is a major component of the GEWEX radiation research. The objective of the NASA/GEWEX SRB project is to determine surface, top-of-atmosphere (TOA), and atmospheric shortwave (SW) and longwave (LW) radiative fluxes with the precision needed to predict transient climate variations and decadal-to-centennial climate trends.