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FRAMEWORK CONTRACT DESIS – EDO (European Drought Observatory)

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Project details

Summary

ARCADIA SIT is a partner in a European consortium for the provision of services in the GIS and remote sensing field, within the framework of the Desis framework contract. The project is developed by CCR – IES – Institute for the Environment and Sustainability / Land Management and Natural Hazards Unit / DESERT.
The European Drought Observatory was set up by the European Commission to monitor and evaluate the phenomenon of desertification in Europe and provide forecasts on its impact. The data used comes from different fields (meteorology, hydrology, soil moisture, crop and vegetation) and is analyzed in such a way as to provide real-time reports and drought forecasts, both within specific and restricted areas and more large. With the resulting information, models are developed and thematic maps are drawn up and then made public through an ad hoc implemented Webgis. The functionality of the webgis is to allow the user to view the various maps produced together with other geographic data and to query the different layers.

Description

The project produced several outputs:

  • 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 deliveries of the EuroGEOSS project, WP5 “Drought”.
  • 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.
  • Geographical coverage of the EU area.

The purpose of the EDO is not only to present the results of the models used within the JRC on drought, but also to act as a coordinating body for European research centers and bodies dealing 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 of the project are:

  • Vector and grid data from Oracle DB
  • Alphanumeric data from Oracle DB and XML tables
  • ESRI shapefiles
  • WFS (Web Feature Service)
  • Raster images in various formats, georeferenced files from WMS (Web Map Service) and WCS (Web Coverage Service)

Type of data processing and implementation:

  • Generation of maps using UMN MapServer
  • Configuration and implementation of UMN MapServer projects
  • Modification and maintenance of Oracle tables
  • Test on OWS services

Maintenance and development of web tools to generate maps and graphs of drought indicators and to manage web pages and their translations in different languages.
Passing of input data, GIS, data mining and ad-hoc routines to analyze the data and produce in output:

  • Websites implemented with HTML, PHP, JavaScript, XML, AJAX and related libraries and frameworks such as Map of PHP MapScript, FPDF, jQuery, jqPlot, OpenLayers and in the past ExtJS and Highcharts
  • Procedures in DOS and BASH to manage the transfer and publication of data
  • Configuring OWS (OGC Web Services)
  • Online documentation on the implemented software
  • Implementation of web tools to generate maps and graphs of drought indicators and to manage web pages and their translations in different languages

During the project, scripts were implemented to test and validate the alphanumeric and geographic information, for the systematic verification of the information. Other scripts have been produced for the statistical analysis of information and the classification of areas subject to desertification.

The EDO pages contain information relevant to drought, such as maps of indicators derived from different data sources (e.g. rainfall measurements, satellite measurements, soil moisture content). Several tools allow viewing and analysis of information and the publication of “Drought News” provides an overview of the situation in case of impending drought.

One of the most important parts of the system is the browser. The browser is the window through which users interact with each other and with web applications. To verify the correct functioning of the system, we need a way to simulate the interaction between browser and web application. In fact, different browsers have different behaviors and maximum transparency must be ensured to make the product browser independent. For the test of the single functions we have defined programs capable of carrying out self-tests to verify the functionality of the system.

Tests have been developed by modeling the behavior of the user in his actions of sending a message, loading maps, connecting a web service, etc. Each test is broken down into individual actions. It is necessary to conduct tests on the product in its entirety, the tests must measure the effectiveness of the system and the performance of web browsing, as regards the individual functions offered by the webgis.

Tests have been developed by modeling the behavior of the user in his actions of sending a message, loading maps, connecting a web service, etc. Each test is broken down into individual actions. It is necessary to conduct tests on the product in its entirety, the tests must measure the effectiveness of the system and the performance of web browsing, as regards the individual functions offered by the webgis.

Drought assessment is done using individual indices, based on meteorological data or remote sensing images. The development of a combined index integrating meteorological and remote sensing indicators can help reduce false alarms, for example in the event that vegetation indices indicate a reduction in biomass that can be generated for reasons other than water stress. The proposed combined indicator is based on the three main EDO indices: SPI, soil moisture and FAPAR.

Soil humidity is one of the fundamental variables in the analysis of hydrological, climatological, biological and ecological processes because it plays a crucial role in the interactions between the atmosphere and the earth’s surface, in fact, the soil’s moisture content influences evaporation surface, the runoff, albedo, emissivity and portioning of sensitive and latent heat flows also represent a useful water reservoir for plants, in the period in which rainwater supplies are lower than their demands.

Drought is not only a temporary lack of rain, but also occurs when the soil moisture decreases considerably, in this scenario, crops and natural vegetation suffers due to scarce water availability, therefore, great efforts have been made to estimate soil moisture using the soil water balance model and other atmospheric data (soil observation, numerical weather forecast, etc.).

Drought is a phenomenon caused by a lack of rainfall for a prolonged period of time, since the average amount of rainfall varies spatially, the definition of drought periods must take into account local characteristics, and its monitoring is based on the evaluation of various indices.

The standardized precipitation index (SPI) shows the deviation from the average precipitation and is therefore directly related to the risk of drought. Other indices are used to monitor the state of soil moisture, vegetation, groundwater levels, etc.
The indices are collected by various means, ranging from precipitation measurements via meteorological stations to deriving from images by remote sensing.

The JRC collects a series of continental-level drought indices, these drought monitoring data are complemented by additional drought indices, provided by national, regional or local organizations. Drought experts analyze the indices and based on this analysis they can make an informed statement about the current drought situation. Continuous observation of drought conditions in Europe will therefore facilitate the identification of periods of onset and duration of the same.

EDO analyzes datasets to produce analytics and statistics such as:

  • Combined drought indicator
  • Average daily soil moisture per region
  • Daily soil moisture, Average anomaly by region
  • Predicted soil moisture anomaly
  • SPI to SYNOP stations from the MARS database
  • SPI at SYNOP stations interpolated to the 0.25dd grid
  • Snowpack indicator
  • Spatial average of the SPI at the SYNOP / SPI stations interpolated for the Eurostat NUTS3 regions
  • Vegetation Productivity (fAPAR)
  • Vegetation productivity anomaly (fAPAR anomaly)
  • Water content of vegetation (NDWI)
  • Water Composition Abnormality (NDWI)

Customer

Joint Research Centre ISPRA - EU COMMISSION

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