Karel CharvatHelp Service

Remote Sensing

Social Validation of INSPIRE Annex III Data Structures in EU Habitats(27th of June 16:00 room Fintry)

Content Lessons learn from user communities Why harmonize data? For whom are metadata important From INSPIRE to Habitats Architecture Reference laboratory as prove of concept Pilots testbeds

Lessons learn from user communities

WILD SALMONMONITORING

LA PALMAMARINE

RESERVE

NATURAL RESOURCE MGMT

SHEEP & GOATHERD

MANAGEMENT

ECON ACTIVITYAT COASTAL

BENTHIC HAB.

ECONOMIC ACTIVITIES

HIKING TRIPPLANNER

SORIANATURALRESERVE

ECO-TOURISM

CZECH NAT’LFOREST

PROGRAMME

NAT’LPOLICY

Lessons learn from user communities Analysis of use cases Generalization How communities request could influence

architecture design, data models and metadata requirements

Analysis of use casesUse case 1 Sheep and Goat Herding Management

Actors Personnel at Madonie Park Authority Task This is mostly an internal but fundamental task at Madonie Park Authority the

requires the availability of geospatial data inside the whole Office and for external consultants (mainly researchers) that must help internal staff in managing the areas of the park. All this people access data by their GIS software or the WEBGIS platform, through geospatial web services INSPIRE compliant.

Assumptions The proprietary databases can be made INSPIRE-compliant using the HABITATS Metadata profile in order to be accessed through the Sicily Region Portal using GIS or WEBGIS software compliant to OGC web services.

Description People at Madonie Park Authority deal with the management of grazing areas in a sustainable way allowing shepherds to access to areas, assigned to each of them, for grazing of sheep and goats. The control of the impact of grazing on assigned areas is carried out by Park Authority Personnel and external experts. This requires also the production of new layers on the state of areas the must be in a format compliant to ISPIRE directive in order to be used in an appropriate way.

Comments Data used for this task are:

- Grazing plan; - Animals position distributed over the whole period of grazing; - State of conservation of areas (this includes some information such as level

of pressure caused by animals).

Analysis of use casesUse case Wild Salmon Monitoring and Management Internationally

Actors Researchers, and Decision Makers Task The International SALSEA Group through collaboration in the FP7 SALSEA-Merge

project is investigating and recording in 2 major databases, the migration and distribution of salmon in the North-East Atlantic. The Use Case is to make their extensive data open and accessible using INSPIRE principles. Based on their existing best-practice, this group is likely to impact on the proposed salmon-related data, metadata and services that will be input to the INSPIRE TWGs.

Assumptions As the SALSEA Group wish to focus all of their efforts on their scientific work until the end of the SALSEA Merge project, it will be late 2011 before they will allow their data to be made available to a HABITATS pilot. They also wish to see how the Irish National pilot gets on and reuse its learning and approach.

Description This group uses the widely used best-practice ICES WGNAPES database structure. WGNAPES is a permanent Group that will continue after the SALSEA-Merge project ends in 2011. ICES/WGNAPES is an Internal database composed of National databases. With some fields added for SALSEA-Merge and the Genetic database. So it is good practice and a permanent working group which should lead to very useful inputs to the 4 HABITATS INSPIRE themes.

Comments This case with SALSEA-Merge is complex, and touches on the potentially high commercial value of the genetic databases, which is the reason for the reticence of the scientists involved in opening up their information to be INSPIRE compliant. On the other hand, interfacing INSPIRE-compliant databases with commercial services might be the most effective means for them to profit from their research. These issues will be further explored when MAC is able to more actively engage with the SALSEA-Merge stakeholders, after their current project work ends.

Analysis of use casesUse case Subsidies in the forest management

Actors forest owners, state and regional forest administration, EU public

Task Every time the forest owner decides to apply for one, or more of the subsidy

programmes in forestry, he needs to prepare project of the desired action. The digital datasets of the Regional Plans of Forest Development (RPFD) can be used to plan the reforestation of the target tree species in respect with their natural conditions, to manage the decision process in case of windthrow event, to build the shelter, or the new biking trail, etc.

Assumptions RPFD digital forest maps: - Typological map 1:10 000 - Map of forest altitudinal zones 1:50 000 - Map of forest target management sets 1:25 000 - Map of long-term forest protection measures 1:25 000 - Map of declared functions 1:25000 - Map of function potential 1:25 000 - Transportation map 1:25 000

Description In the Czech forest law, there are several means of promotion the sustainable forest management. The government provides subsidies for reforestation and plantations of native forest species, to support the wood production after natural disasters (bark beetle, windthrow events) and gentle management practices. Further there are subsidies to promote rural development and recreational function of forests (afforestation of agricultural land, building of biking trails and other tourist infrastructure, and more.) The information from the Regional Plans of Forest Development (RPFD) datasets serve as a basis the decision-making, project preparation, and finally also controls of the subsidies usage.

Comments

Analysis of use cases – data usage Regional data used regionally Global data used regionally Regional data used cross regionally Regional data used globally Global data used globally

Regional data used regionally There is not direct requirement for INSPIRE

data models Local data models could be wider Local data models reflect regional needs and

also regional decision processes If data are not shared outside of region (but in

many cases it is necessary), in principle global standards are not needed

Standards are needed in case of more data suppliers, to guarantee data consistence

Regional data used regionally

Global data used regionally Global data are in some content something like

de facto standards In some cases it is necessary to be possible

transform data into such models, which is required by regional decision processes

The global model has to cover regional decision needs (GMES case for example)

Question is, if this transformation will be done on fly or offline

Language problem

Example FMI data used locally

Example FMI data used locally

Regional data used cross regionally There is already very visible problem of data

harmonization, this problem is higher, in the case of cross boarder regions

In many cases, like tourism we need deal not with one or more separate data theme, but with complex mixture of themes related to INSPIRE

In some application cases model could be broader then INSPIRE definition

Language problem

Tourist example

Regional data used globally Probably most relevant cases for INSPIRE data

model The idea is to combine local data sets into one

data set The regional data has to be transformed (in

many cases simplified) into global model Relevant cases are tourism, transport,

education, research, environment protection, risk management, strategic decision

Language problem

Regional data used globally

Regional data used globally

Global data used globally Global data are standard or de facto

standard. It is expected, that in the case of data of

public sector, this data will be already in INSPIRE models

It could happened, that this models has to be transformed on the base of needs of concrete application area. Transformation could be based also on Feature Encoding or SLD.

Global data used globally

Global data used globally

Sea Regions Species distributionHabitats and

biotopesBio-geographical

regions

TRAGSATEC IMCSHSRSTU Graz

D3.1 Conceptual Data Models

UML Class Diagrams

Feature Catalogues

INSPIRE testing

→ INSPIRE TWGs

→ methodology used for INSPIRE data specification,

→ international standards

→ analyses of data models for selected themes used in single countries participating on Habitats project

→ results of previous tasks of Habitats project

← As simple as possible

← Just common elements

and attributes

← To enable an extension of

models

← To interconnect Habitats

themes

← To re-use existing

componets

FMIdata

INSPIREData

Specifications 2.0

Harmonization

Testing of specifications(based on Habitats

data models and userrequirements)

Sea Regions

Species distribution

Habitats and biotopes

Bio-geographical regions

Source data

Vegetation tiers (altitudinal vegetation zones) layer

● Part of PFD (Regional Plans of Forest Development) produced by FMI● Spatial reference system - SJTSK (Czech national system)● FMI original classification system

New Data Model

Existing data model +

referenceHabitatTypeId: CharacterStringreferenceHabitatTypeScheme: ReferenceHabitatTypeSchemeValuelocalSchemeURI: URIlocalNameValue: CharacterString

geometry: polygonreferenceHabitatTypeId: eunis_valuereferenceHabitatTypeScheme: eunislocalSchemeURI: link_to_FMI_classificationlocalNameValue: FMI_classification_value

Harmonization process

Open SHP fileand its scheme

Save finalSHP file

ReclassificationFMI → EUNIS

New datamodel

Taxonomy – reclassification (FMI → Eunis)

● 0 Pine → G3.42,"4","Middle European [Pinus sylvestris] forests"

● 1 Oak → G1.87,"4","Medio-European acidophilous [Quercus] forests"

● 2 Beech-oak → G1.82,"4","Atlantic acidophilous [Fagus] - [Quercus] forests"

● 3 Oak-beech → G1.82,"4","Atlantic acidophilous [Fagus] - [Quercus] forests"

● 4 Beech → G1.6,"3","[Fagus] woodland"

● 5 Fir-beech → G4.6,"3","Mixed [Abies] - [Picea] - [Fagus] woodland"

● 6 Spruce-beech → G4.6,"3","Mixed [Abies] - [Picea] - [Fagus] woodland"

● 7 Beech-spruce → G4.6,"3","Mixed [Abies] - [Picea] - [Fagus] woodland"

● 8 Spruce → G3.1D,"4","Hercynian subalpine [Picea] forests"

● 9 Dwarp pine → F2.45,"4","Hercynian [Pinus mugo] scrub"

Source data(simplified)

Target data

Metadata profiles and cataloging Requirements on metadata information are

growing with professionalism of users. Simply we can say, that for example tourist

requirements will be done usually by theme of information and spatial or eventually time extend

Requirements of specialist could lead to extension of current INSPIRE standards (done as part of Habitats work)

Simple metadata inside of viewer

Habitats multi search

INSPIRE versus Habitats architecture

What is missing from Habitats view INSPIRE architecture doesn’t reflect needs of

regions about data collection and updating INSPIRE architecture doesn’t reflect needs of

regions about metadata collection and updating

In single Habitats pilot cases you don’t need necessary full architecture

Components of Habitats architecture could be localized on more places.

Example Metadata Habitats metadata management has to be

divided into single components, guarantee communication using CSW standards.

So metadata management system could run on different server, than single clients

Metadata management system is divided from metadata edition and also from discovery services.

Example Metadata Catalogue system is now composed from

independent components: Metadata catalogue Metadata editor client Metadata import client Metadata harvesting client Metadata valuator client Light discovery services client Full discovery services client

Example Metadata Currently solved problem is about metadata

management, if to use metadata harvesting or provide multi search to multiple catalogue

Second option could be combined with some methods of metadata caching

The problems are with different usage of standards in INSPIRE and ISO, for example some GEOSS catalogues are not compatible with INSPIRE based catalogues

View services Current most popular technologies are based

on clients technologies. It give us some advantage, but also could

bring problems with browsers and some operations like coordinate transformation or printing

Server part of client is necessary

View services

View services

Additional services required Sensor Observation Services Data uploading Data composition forming Vectorisation of data Data download Support for mobile online and offline data

collection Support for iframe or portlets to be possible

integrate components with Web pages

Usage of iframe

Reference laboratory  Habitats RL is designed and implemented as

a virtual database. It integrates different technologies like GIS, multimedia, and virtual reality. Important part is integration of social networking tools supporting social assessment. These services are not implemented on the Habitats  portal directly, but they are implemented as virtual services on different places in Europe.

Reference laboratory

Pilot implementation Not all pilots need to implement full

architecture, subset of architecture is given by pilot needs

Pilot implementation are based on common generic architecture principles, but they are free to use different components and platforms, this give possibilities for good testing of interoperability

Pilot applications are validate by users, but also against RL

Thank you for your attention

Karel CharvatHelp Service

Remote Sensing