GMES Service for Geospatial Reference Data Access (RDA) Covering Areas Outside Europe

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INSPIRE Conference 2011 Edinburgh 27 June - 1 July GMES Service for Geospatial Reference Data Access (RDA) Covering Areas Outside Europe Andrea Ajmar, Simone Balbo, Piero Boccardo, Simone Dalmasso, Anna Facello, Paola Fassino, Fabio Giulio Tonolo, Paolo Pasquali, Francesca Perez, Sara Steffenino ITHACA

Summary 1. The Framework 2. The Data Inventory (core and thematic) 3. The Data Quality 4. The Data Model

ITHACA Information Technology for Humanitarian Assistance, Cooperation and Action Co-Founded by Politecnico di Torino in 2006 MoU with UN World Food Programme Collaboration with several international entities (UNDP, JRC, World Bank)

The GMES Programme Global Monitoring for Environment and Security is the European Programme for the establishment of a European capacity for Earth Observation Information 6 Thematic Areas marine land atmosphere climate change emergency security 2 Services emergency response (e.g. floods, fires, technological accidents, humanitarian aid) security-related aspects (e.g. maritime surveillance, border control)

Geospatial Reference Data Access Updated, reliable and easily accessible reference base datasets are a key factor for the success of emergency operations; vital elements in order to provide: the basic geographic framework on top of which additional spatial information can be produced and disclosed (e.g. land use/land cover maps, asset maps and damage assessment maps in response to crisis); the set of relationships between the geographical components that will allow building the assessments, analyses and monitoring from combinations of datasets.

Major Tasks Analysis of non-european reference data availability; Analysis of non-european reference data quality and consistency; Analysis of the UN-SDI initiative; Identify reference data information gaps; Demonstrator and validation.

Data Availability Suitable in particular for Emergency Preparedness and Response, Food Security and Poverty Mapping issues; Core Data: the minimum geographic data baseline that is necessary for optimal use of all the different considered applications and activities; Thematic Data: considering in details each specific activity concerning GMES related projects and applications that will take advantage from the planned geospatial RDA service, additional specific geographic data can be identified.

Core Data TOPIC SUB-TOPIC Analyzed datasets Coastline and Maritime Boundaries 7 (100%) Country Political Level 0 and Area of Dispute Boundaries 6 (100%) Boundaries: coastal, administrative and Sub-national Boundary Data 6 (100%) areas of special interest Areas of conflict 1 (50%) 90% Parks, conservancies, and Protected areas 1 (50%) Drainage and Flow Routing Databases 0 Surface hydrology: surface water bodies, Surface water bodies (SWB) databases 8 (70%) water points, drainage and watersheds Watersheds and River Basin Databases 0 50% Water points and Limnological Databases 5 (70%) Human Population: population centers and Population Center 5 (100%) distributions Urban and Rural Population Density and Distribution database 7 (100%) 100% Roads databases 8 Transportation: roads, railways, airports, harbors and navigation routes Bathymetry and terrestrial elevation Railway line, station, and Marshaling Yard databases 8 Airport databases 6 100% Harbor databases 5 Navigation/routes 3 Bathymetric databases 0% Terrestrial elevation 12 (100%) 50%

Thematic Data TOPIC SUB-TOPIC Analyzed datasets Geology and mineral databases Geo-morphology and Physiocraphic databases Geophysical: geology, geomorphology, seismic, hydrogeology, and soils Earthquake, Tsunamigenic and Volcanic Databases 4 (50%) 10% Hydro-geological / aquifer databases Soils and soil properties databases Satellite imagery, orthorectified mosaics, Satellite Imagery and Mosaics land cover and vegetation data Satellite derivative Land Classification and Vegetation databases Climatic data Global Networks databases Satellite derivative databases Agro-ecological assessment and potential Land Productivity Potential Agricultural and economic assessment National and Subnational Agricoltural Productivity data UN sponsored global AEZ (agro-ecological zones) Food Insecurity, Poverty and Vulnerability databases Human Health Infrastructures and statistical databases 2 (30%) Human Health Socio-Economic and Nutrition Indicators databases 1 (30%) 20% Poverty Monitoring Indicators databases

The Inventory Process globally available; up-to-date; stand-alone or contained in databases; covering each sub-topic; through a review of web sites, geospatial data servers, and on-line searchable metadata databases.

Metadata and Catalogue FIELD FIELD CONTENT GENERAL INFORMATION TECHNICAL INFORMATION Database ID Database title Database alternate title Database producer Database sources Online resource Notes Database content Datasets type Datasets format Datasets scale Database geographic extent Database spatial reference system Notes Database internal identifier Name by which the cited resource is known Short name or other language by which the cited resource is known Identification of the institution, organization or company that is responsible for the production and maintenance of the resource Information about the source data used in creating the resource or, at least, about the provider of source data Online sources from which any other descriptive information about the database can be obtained Additional information Description of the content of the database and list of the different datasets contained Information about grid or the vector spatial objects in the datasets Name of the transfer format(s) for the datasets Level of detail of data, expressed as a scale factor or a ground sample distance Geographic coverage of the database (global, continental, national, or sub-national) Information about the spatial reference system (name of reference system, projection, ellipsoid and datum used) Additional information

Metadata and Catalogue FIELD Database reference date FIELD CONTENT Reference date (creation or publication or revision) for the cited database Database last edition Last edition of the cited databse MAINTENANCE INFORMATION Last edition date Maintenance Notes Date of the last edition of cited database Information about the frequency of updating and revision (e.g. changes, additions) of database Additional information Access instructions Information about the distributor of and option for obtaining the resource Access constraints Any restrictions or limitations on accessing and obtaining the resource DISTRIBUTION INFORMATION Use constraints Any restrictions or limitations or warnings on using the resource; moreover limitations affecting the fitness for use of the resource Notes Additional information

Metadata and Catalogue A metadata catalog service is a mechanism for storing and accessing descriptive metadata and allow users to query for data items based on desired attributes

GeoNetwork OpenSource The INSPIRE directive requires the capability to create metadata on spatial datasets or series or metadata on services using ISO19115 and ISO19119 GeoNetwork provide support for both standards with sample templates by default.

Data Quality Process internal quality corresponds to the level of similarity that exists between the data produced and the perfect data (Universe of Discourse) that should have been produced, that are also called nominal ground (greater accuracy); external quality corresponds to the level of concordance that exists between a product and user needs, or expectations, in a given context.

Internal Quality 11 Quality Indicators have been defined on the basis of the ISO specifications (ISO 19113, ISO 19115), which have been modified and adapted in relation to the aim of the GMES project; some confidence intervals have been set for each indicator, in order to define up to 5 levels of quality; for all candidate datasets selected for each sub-topic, comparisons, measurements and statistics are produced, in order to obtain a value for each indicator; for each indicator, a score between 1 and 5 is assigned to the current dataset, on the basis of the value obtained and the confidence intervals previously defined. RESULT: quality matrix

Internal Quality Geographic extent Licensing and constraints Scale Denominator Update Fitness for use in cartographic representation (I) and (II) Integration Data integrity Positional accuracy Thematic accuracy Completeness 11 indicators

Internal Quality Geographic extent Licensing and constraints Scale Denominator Update Fitness for use in cartographic representation (I) and (II) Integration Data integrity Positional accuracy Thematic accuracy Completeness 1.Local 2.Sub national 3.National 4.Continental 5.Global 1.Coarse 2.Low 3.Intermediate 4.High 5.File 11 indicators 5 levels of quality

Internal Quality Geographic extent Licensing and constraints Scale Denominator Update Fitness for use in cartographic representation (I) and (II) Integration Data integrity Positional accuracy Thematic accuracy Completeness 1.Local 2.Sub national 3.National 4.Continental 5.Global 1.Coarse 2.Low 3.Intermediate 4.High 5.File 11 indicators 5 levels of quality comparison, measures and statistics

Internal Quality Geographic extent Licensing and constraints Scale Denominator Update Fitness for use in cartographic representation (I) and (II) Integration Data integrity Positional accuracy Thematic accuracy Completeness 1.Local 2.Sub national 3.National 4.Continental 5.Global 1.Coarse 2.Low 3.Intermediate 4.High 5.File Geographic extent 5 Licensing and constraints 5 Scale Denominator 2 Update 3 Fitness for use in cartographic representation (I) and (II) 4-5 Integration 5 Data integrity 5 Positional accuracy 3 Thematic accuracy 5 Completeness 5 11 indicators 5 levels of quality comparison, measures and statistics 11 scores

Internal Quality Geographic extent Licensing and constraints Scale Denominator Update Fitness for use in cartographic representation (I) and (II) Integration Data integrity Positional accuracy Thematic accuracy Completeness 1.Local 2.Sub national 3.National 4.Continental 5.Global 1.Coarse 2.Low 3.Intermediate 4.High 5.File Geographic extent 5 Licensing and constraints 5 Scale Denominator 2 Update 3 Fitness for use in cartographic representation (I) and (II) 4-5 Integration 5 Data integrity 5 Positional accuracy 3 Thematic accuracy 5 Completeness 5 Quality Matrix 11 indicators 5 levels of quality comparison, measures and statistics 11 scores

Internal Quality Geographic Dataset Extent 1.Coarse Geographic extent 2.Low Licensing and 3.Intermediate constraints 4.High Scale 5.File Denominator Update Fitness for use in cartographic representation (I) and (II) Integration Data integrity Positional accuracy Licensing and Constraint Scale Denom. 1.Local 2.Sub national 3.National 4.Continental 5.Global Update Fitness for Use I Fitness for Use II Integration Data Integrity Geographic extent 5 Licensing and constraints 5 VMAP1 5 4 4 3 4 3 Scale Denominator 5 5 2 5 5 5 Update 3 Fitness for use in cartographic representation (I) and (II) GAUL 5 4 2 4 5 4 Integration 1 4 5 3 5 5 Global Thematic Map 4 4 3 3 4 4 Thematic 5accuracy 5 5 5 5 5 accuracy Completeness 5 Completeness 4-5 Data integrity 5 Positional accuracy 3 Positional Accuracy Thematic Accuracy VMAP0 5 5 2 3 4 5 5 5 3 5 5 GADM 5 4 3 5 3 5 1 5 4 5 5 WVS+ 5 2 4 1 4 5 3 5 5 5 5 Compl. Quality Matrix 11 indicators 5 levels of quality comparison, measures and statistics 11 scores

External Quality Parameter Weight (0 to 1) Geographic Extent 1 Licensing and Constraint 1 Scale Denominator 0,5 Update 1 Fitness for Use I 1 Fitness for Use II 1 Integration 1 Data Integrity 1 Positional Accuracy 0,5 Thematic Accuracy 1 Completness 1 a weight included in the range 0-1 has to be assigned to each indicator for the single sub-topic: this value represents the importance of any single quality indicator for the current sub-topic in respect to the final service;

External Quality Dataset Final Score a vector of the total VMAP0 44,5 VMAP1 43,5 Global Map 43,5 GADM 41,5 GAUL 39,5 WVS+ 39,5 scores for each considered dataset is calculated as the result of an ordinary matrix product between the quality matrix and the vector of weights.

Data Model Design

Data Model Design

Data Model Design

Demonstrators

Conclusions Complete and comprehensive inventory of globally consistent core and thematic data, available through a catalog application; Quality evaluation and ranking of the candidates through user driven criteria; Data model and ETL procedures definition and implementation.

Thank You GMES Service for Geospatial Reference Data Access (RDA) Covering Areas Outside Europe Andrea Ajmar, Simone Balbo, Piero Boccardo, Simone Dalmasso, Anna Facello, Paola Fassino, Fabio Giulio Tonolo, Paolo Pasquali, Francesca Perez, Sara Steffenino ITHACA