ARCADIA SIT is a partner in a European consortium for the supply of services in the field of GIS and remote sensing, under the framework contract Desis. The project is developed by CCR – IES – Institute for Environment and Sustainability / Land Management and Natural Hazards Unit / DESERT.
The European Drought Observatory is designed by the European Commission to monitor and evaluate the phenomenon of drought in Europe and to provide forecasts on its impact.
The purpose of EDO is to use data from different fields (meteorology, hydrology, soil moisture, crop / vegetation) to provide real-time reports and forecasts of drought, both within specific areas, either by an overall assessment of the phenomenon.
With the results obtained by the different models used are then produced thematic maps of drought, made public through a web GIS implemented ad hoc. The functionality of the web GIS allow the user to view the cards drought together with other layers (geographical or thematic), in order to better locate the areas subject to the phenomenon. In addition, the functionality of querying and generating graphics based on time series allow a thorough analysis of the information provided.
Printed outputs and reports:
- DESERT Action deliverables: WP2008 Deliverable 1.2, WP2009 Deliverable 4.2, WP2010 Deliverables 2.4, 4.1, 4.2, WP2011 Deliverables 4.1, 4.2, 4.3, 6.1, 8.1, WP2012 Deliverables 2.5, 3.1, 3.4.
- Contribution to the deliverables of EuroGEOSS project, WP5 “Drought”.
- The poster “Methodologies to enhance complex geometry analysis and display using a dynamic object-oriented DBMS”, D.Magni and A.de Jager, FOSS4G 2010, Barcelona, 6-9 September 2010.
- The geographical area covered is EU countries.
The purpose of EDO is not only to present the results of the models used within the JRC of drought, but also to act as a coordinating body for research centers and European bodies that deal with drought, managing a network of relationships and organizing the sharing and presentation of data and maps produced by the different parties.
The input data used are:
- Vector data from Oracle tables;
- ESRI shapefiles;
- WFS (Web Feature Service);
- Gridded data from Oracle tables;
- Raster images in many formats, from files with world files for geo-referencing and from WMS (Web Map Service) and WCS (Web Coverage Service);
- Alphanumerical data from Oracle tables and XML documents.
Type of data processing and implementations:
- Generation of maps by means of UMN MapServer;
- Configuration and implementation of UMN MapServer projects;
- Editing and maintenance of Oracle tables;
- Test on OWS services;
Maintenance and tuning of web tools to generate maps and charts of drought indicators and to manage webpages and their translations in different languages.
Crossing the input data through, GIS, Data mining and ad-hoc routines in the appropriate IT language, to analyze data and produce in output:
- Procedures in DOS and BASH to manage data transfer and publication;
- Set-up of OWS (OGC Web Services);
- On-line documentation on implemented software;
- Implementation of web tools to generate maps and charts of drought indicatorsand to manage webpages and their translations in different languages.
During the project were implemented scripts for testing and validation of the alphanumerical and geographical information.
Were prepared scripts in Python for systematic verification of the information, fields are populated according to encoded information, also correlation keys between the different elements are builded.
Other scripts have been produced for the statistical analysis of the information and classification of areas subject to desertification.
The EDO pages contain drought-relevant information such as maps of indicators derived from different data sources (e.g., precipitation measurements, satellite measurements, modelled soil moisture content).
Different tools allow for displaying and analyzing the information and irregularly published “Drought News” give an overview of the situation in case of imminent droughts.
Generally the drought assessment is done using individual indices, based or in meteorological data or in remote sensing images. The development of a combined index integrating meteorological and remote sensing indicators can help to reduce false alarms, for example in the case of the vegetation indices where a biomass reduction can be generated by another reasons different than water stress. The combined indicator proposed is based in the three main indices of EDO: the SPI, the soil moisture and the fAPAR.
Soil moisture is one of the important variables in hydrologic, climatologic, biologic, and ecological processes because it plays a crucial role in the interactions between the atmosphere and land surface. In fact, soil moisture content affects surface evaporation, runoff, albedo, emissivity, and portioning of sensible and latent heat fluxes. Moreover, it represents a vital water reservoir for all the plants buffering their water consumptions in period with rain water supplies are lesser than their requests. In addition, drought in not only a temporary lack of rain but also occurs when the soil moisture decreases considerably, and crops and natural plant communities suffer due to insufficient water availability. Therefore, great efforts have been made to estimate soil moisture using soil water balance model forced with realistic precipitation and other atmospheric data (ground observation, numerical weather prediction, etc.) to be used as direct indicator to assess the drought onset, duration and severity.
One of the most important parts in the web is a browser. Browser is the window, through which web users interact with web applications and other users. Users are always talking with web applications through browsers. So, in order to test, that our web application behaves correctly, we need a way to simulate this interaction between browser and web application in our tests. In fact, different browsers have different behaviors and you need to ensure maximum transparency to make the product independent of the browser. For the testing of individual functions we defined programs that are able to perform self-tests, both to verify the functionality is to stress the system.
We create tests by modeling the purpose of a test from the user’s perspective: send a message, Load a maps, connect a web service, etc. Each test is decomposed into individual actions, very granular.
The automated test program create a skeleton in the programming language and create a method name that reflects each action, that is increased step by step.
However, it remains necessary to conduct tests on the overall web product that reflects the use of the product and its effectiveness. For web surfing regards products webgis a number of specific problems have been addressed in the development phase and consequently of the test.
Droughts are caused by a lack of precipitation over a prolonged period of time. Since the average amount of precipitation varies spatially, the definition of drought periods needs to take local characteristics into account.
Drought monitoring is based on the evaluation of various indices. The standardized precipitation index (SPI) shows the deviation from average precipitation and is therefore directly related to drought risk. Additional indices monitor the status of soil moisture, vegetation, groundwater levels, etc. to determine the impacts of droughts. The various indices are collected by different means, ranging from precipitation measurements of weather stations to remote sensing images for vegetation states. The JRC collects series of drought indices on a continental level. This drought monitoring data is complemented by additional drought indices, that are prepared by national, regional or local organizations. Drought experts analyse the quantitative measures of drought impacts by. Based on this analysis they can make an informed statement regarding the current drought situation. The continuous observation of the drought conditions in Europe shall therefore facilitates the detection of the onset, duration and drought periods.
EDO analyze dataset to produce data analysis and statistics like:
- Combined Drought Indicator
- Daily Soil Moisture average per Region
- Daily Soil Moisture Anomaly Average per Region
- Forecasted Soil Moisture Anomaly
- SPI at SYNOP stations from the MARS database
- SPI at SYNOP stations interpolated to 0.25dd grid
- Snowpack Indicator
- Spatial average of SPI at SYNOP stations / interpolated SPI for Eurostat NUTS3 regions
- Vegetation Productivity (fAPAR)
- Vegetation Productivity Anomaly (fAPAR Anomaly)
- Vegetation Water Content (NDWI)
- Vegetation Water Content (NDWI) Anomaly
CustomerJoint Research Centre ISPRA - EU COMMISSION
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