AIP-6 Agriculture/Disaster Management SBA Eugene Yu and Joan Mas Outline Scenarios & Use Cases Agricultural Drought Monitoring and Forecasting Agricultural Flooding Crop Loss Assessment Quality of Web Service Products Agriculture Scenario in GeoViQua Results Global Agricultural Drought Monitoring and Forecasting System Remote Sensing based Crop Loss Assessment Service System Quality of Web Service Products through GeoViQua Message The use of Open Geospatial Web Services improves agricultural disaster decision support tools.
CSW DAB-Q (quality indicators) & S&T (user feedback) RFCLASS Remote Sensing based Flood Crop Loss Assessment Service Systems Online system supported with Open Geospatial Web services OGC WCS, WMS, WFS are the backbone components Crop loss assessment using crop condition profiles Flood time series analyses
GADMFS - Global Agricultural Drought Monitoring and Forecasting System Low latency information production with Open Geospatial Web services OGC WCS, WMS, WFS supports data access Global coverage Interactive query, visualization and data retrieval Activity Integration of the GeoViQua GEO label User Feedback interface Into the
George Mason University Global Agricultural Drought Monitoring and Forecasting System By means of simple links Integrating GeoViQua GEO label in GADMFS portal: GEO label was created by linking to GeoViQua for Quality Service Base on both ISO19115 Metadata description and User feedback reports Visualization and discovery of metadata Connected to the GCI http://gis.csiss.gmu.edu/GADMFS
GeoViQua user feedback Feedback is managed with GeoViQua User Feedback service and API Facilitate users to provide feedback on data quality By clicking on the dynamic GEO label users can read metadata fragments including feedback updates Very easy to integrade. Link for the 2 icons This static icon has to be linked to https://geoviqua.stcorp.nl/submit_feedback.html?
target_code=GlobalAgriculturalDrought&target_codespace=www.gmu.ed u This icon is generated automatically using a link in the GEO label API. To ensure maximum compatibility, you should use this html code: Agriculture flooding practices control Scenario The EU agri-environmental measures (Regulation CEE 1257/1999) consist of a subsidy that farmers receive to
support agricultural practices that favour the conservation of affected ecosystems. In Catalonia, the local government monitors the farmers practices by means of a fair decision support system based on remote sensing imagery and flooding practices detection, replacing time-consuming and expensive field surveys. 1 Farmers flooding practices are extracted by combining Landsat image classification procedures with rigorous statistical quality assessments. Both the Landsat imagery and sample of the classified maps are available through the GEOSS Portal. GEOSS PORTAL http://geoportal.geoviqua.org
This enhanced GEOSS Portal includes: discovery and access of quality indicators and traceability embedded in metadata a GEO Label and referencing scientific reports smart quality visualization at pixel level (quality enriched Web Map services [WMS-Q] visualized in Greenland) at feature level (Quality enriched [KML-Q] visualized in Google Earth). 2 A sudden failure of the Landsat TM/ ETM+ sensor occurs during a monitoring critical period. Time is critical to find a suitable alternative dataset. A discovered issue is found. ADDITIONS IN THE METADATA QUALITY MODEL The Producer Quality Model extends ISO 19115-1, 19115-2 and 19157 standards to include information such as discovered issues, new and better formalized quality indicators (reference datasets for quality evaluation,
traceability, and statistical summaries of uncertainty), citations to publications, pixel level quality and more. 3 The government technicians can search for these alternative datasets through the GEOSS Portal thanks to the quality-aware component (DAB-Q) QUERY BY QUALITY INDICATOR The Quality-enabled Discovery and Access Broker (DAB-Q) is an extension of the GEO-DAB that implements the Producer Quality Model (and also the User Quality Model) as a quality extensions of the OGC Catalogue Service for the Web (CSW-ISO-Q) interface. 4 The metadata of the possible alternative datasets can be
compared to facilitate the choice of the right product. The most fitfor-purpose dataset is identified through metadata comparison METADATA COMPARISON The metadata comparison tool. presents datasets in columns, with attributes and metadata parameters aligned in rows. 5 At the end of the campaign, the local government releases KML-Q with a summary of the season KML-Q AND WMS-Q http://www.ogc.uab.es/geoviqua/wmsq
Quality can be described at dataset level (overall indicator in the metadata) or at pixel level and feature level (a quality value for each pixel or feature). GeoViQua has incorporated into the ncWMS and in the KML-Q innovative symbolization. Contributors GMU (USA) USDA NASS (USA)
Zhengwei Yang CU-Boulder (USA) Joan Mas Pau Eva Sevillano Marco G. Robert Brakenridge CAAS (China)
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