BIO diversity multi-source monitoring S ystem: from S pace T O S pecie

BIOdiversity multi-source monitoring System: from Space TO Specie.

on behalf of BIO_SOS consortium

Palma Blonda

and the Management Team:

B. Biagi, G. Bono, C. Marangi, F. Lovergine, D. Torri

BIO-SOSFP7-SPACE-2001-1, GA n. 263435

KICK-OFF: BARI 17/12/2010

Outline

• History

• BIO_SOS concept and objectives

• The Consortium

• Work Plan

• Test sites

• Management Structure

The concept

• Biodiversity and ecosystems integrity are threatened by human activities resulting in pressures and negative impacts (abuses) on the environment.

• These type of ecosystem disturbances are often conducted in the period between when an area is selected to become a protected site, and when it is actually so, whatever the protection level applied:– a Site of Community Importance – (SCI)– or a Special Protection Area – (SPA)

– :

SCI Murgia Alta IT9120007

• CAP transformation from grassland pasture into agricultural area: soil erosion

• Illegal waste and toxic mud causing heavy metal contamination of soil and aquifer system

• Legal and illegal mining activities• Wind farms infrastructure• Logging, hunting• Tourism • Fires

Outline

• History

• BIO_SOS concept and objectives

• The Consortium

• Work Plan

• Test sites

• Management Structure

Call description: topic SPACE.2010.1.1.-04Stimulating the development of GMES services in

specific area: Biodiversisy

Pilot projects could be considered, which focus on a series of multi-annual surveys of 'sampling' sites under 'pressure' and should foresee the option of delivering Natura 2000 site satellite images 'on demand' for EU policy makers.

….. In particular, effective and timely monitoring of changes in the land cover within and along the borders of protected areas is needed to judge the effectiveness in protecting and conserving the regions from human impacts such as poaching, hunting, logging, urbanization, agriculture, mining, and road construction.

Important Dates

• Submission: 8-12-2009• Negotiation phase: 5-5-2010• Grant Signature: 11-11-2010• Starting date of the project: 1-12-2010• Pre-financing to CNR: 1-12-2010• First authorized set of payments: 14-Dec-2010• Kick-Off: 17-12-2010

BIO_SOS Objective

The development of an operational ecological modelling system suitable for effective and

timely multi-annual monitoring of NATURA 2000 sites and their surrounding.

• To adopt and develop novel operational automatic HR and VHR EO image processing and understanding techniques for:

– Land Cover (LC) map and Land Cover Change (LCC) map generation eligible for habitat mapping

• To develop a modelling framework (scenario-analysis) to combine EO and on-site in-situ data for:

–The automatic provision of biodiversity indicators and their trend

–The prediction that human impacts and combined drivers may have on biodiversity

Research groups

SMEs

Automatic EO Image interpretation

Ecological & landscape modelling

CIBIO-P9

CNR-IGV-P1

UOI-P2

UNIBA-P8

ATREE-P5CERTH-P3ALTERRA-P4

IRD-P12

ABERY-P11

CNR-ISSIA-P1

ASI-P14BACRES-P15

PKI-P6

PKH-P13

ALTAMIRA-P7

UNIMIB-P10

CNR-IAC-P1

CNR-IRPI-P1

Partners’ broad characterization and complementarities

one-man company

End Users who signed the Service Level Agreement (SLA)

– Portugual, ICNB

–Brazil, INPE

–Italy, Regione Puglia

BIO_SOS main outcome:

EO Data for Habitat Monitoring (EODHaM) system

Land Cover (LC) maps and LC Change (LCC) maps

(3-D) World model(site specific)

Single-date single-sensor

Land Cover (LC) map at Ti, i=1….n Habitat map at

Ti, i=1….n

Indicators trends

2. Habitat modelling

Indicators at Ti, i=1….n

3. Landscape modelling

In situ, ground truth

and ancillary data

Prior knowledge

In situ, ground truth and ancillary data

1. Automatic hierarchical single-date single-sensor

spaceborne image classification system

4. Semantic nets• Single-date single-sensor

• Multi-date• Multi-sensor

Legenda -Yellow: available in part- Red: to be developed

Land Cover (LC) maps and LC Change (LCC) maps




Ti, i=1….n

Indicators trends





and ancillary data

Prior knowledge










Ti, i=1….n

Indicators trends





and ancillary data

Prior knowledge







RS_IUS

Habitat change map (HaC)

EODHaM: Module 1

RS-IUS: Remote Sensing Image Understanding System

1.2 RS-IUS first stage: SRC

Spectral Rule-based Classifier (SRC)

• Input: multi-spectral image radiometrically calibrated into top-of-atmosphere reflectance (TOARF) values. No ground truth is required.

• Output: a preliminary spectral (primal sketch) map of the input image into a finite set of spectral sub-categories belonging to six super-categories (strata):

1) water or shadow,

2) snow or ice,

3) clouds,

4) vegetation,

5) bare soil or built-up,

6) outliers.

– Each input pixel belongs to a symbolic segment: a connected sets of labeled pixels featuring the same semantic label (patch)

– Each segment belongs to a symbolic strata defined as image-wide set of labeled pixels featuring the same semantic label (vegetation).

EODHaM: Module 1, RS-IUS

• First stage:– Input:

Calibrated EO images – Outputs:

Preliminary Spectral Map of the input image Continuous physical variables: (e.g., biomass, leaf area index,

etc.)

• Second stage– Output:

– Single-date HR and VHR land cover (LC) maps

Remote Sensing Image Understanding

hierachical two-stage stratified System (RS-IUS)

1.3 RS-IUS second stage

It includes a battery of class specific image proc. modules:

• Context-sensitive image feature extraction modules:

– Stratified multi-scale texture features

– Segment-based geometric attributes, e.g. area, perimeter, compactness rectangularity, number of vertices, etc.

– Stratified morphological attributes.

– Spatial non-topological relationships between segments, e.g. distance, angle/orientation, etc.

– Spatial topological relationships between segments, e.g., adjacency, inclusion, etc. • Class-specific fuzzy rule-based classification modules (semantic nets) exploiting constructive reasoning by evidence accumulation.

EODHaM: Modeling Modules 2 and 3

• Habitat modelling: land cover habitat map • Landscape modeling: for pressure scenario analysis

– Context modelling for landscape changes at different spatial/temporal scale based on land management strategies.

– Site specific models for ecosystem state assessment (soil/vegetation interactions).

– Species specific ecological model for threat identification and impact quantification trend evaluation.

• Single-date Habitat maps (Ha) • Biodiversity Indicators

EODHaM: Module 4

• Automatic change detection techniques development• Semantic net development for pressures evaluation,

impacts detection and warning.

• Land cover change maps (LCC)• Habitat change maps (HaC) • Biodiversity Indicator trends• Warning maps to management authorities

Ecologically sensitive Test Sites• In Italy :

– SCI-IT9120007 Murgia Alta (1258 km2)– SPA-SCI Valloni e steppe pedegarganiche (312 km2)– SCA-IT9150014 and SCI IT9150032 Le Cesine (3.5 km2 )– SPA Saline di Margherita di Savoia IT911006 (SCI IT9110005) (1488 km2 )

• In Greece (120km2 )– SCI-GR2120001 Kalamas delta– SCI-GR2120002 Kalodiki lake – SCI- GR2120004 Kalamas gorge

• In Portugal:– SPA-SCI Rios Sabor e Maçãs (334.76 km2 ) – SPA-SCI Peneda-Gerês (888.45 km2 )

• In Brazil:– 2 sites in Western part of Brazilian Amazon (tropical forest)

• Western Europe sites:– Wales: Borth Bog– Netherlands: Ginkelse and Ederheide

BIO_SOS: impacts

• EODHaM proposed monitoring will examine locally recognizable pressures and their impact on habitats trough the automatic processing of VHR EO data. It will support :

– The management of Natura 2000 sites according to National and EU obligations.

– The evaluation of the effectiveness in protecting and conserving regions from human impacts

– The development of Environmental Planning policies.

Impacts

• Within GMES:– The improvement of operational core service

products (LC and LCC) at VHR.

– The development of new downstream services production (e.g. Habitat maps, Habitat change maps, threats and trend indicators).

– Identifying and promoting new utilisations of satellite imagery.

Project description: 8 WPs

Management structure of the BIO_SOS project

Project Coordinator

Project Coordination Committee: WP Leaders

Project Management Team

Coordination Team

European Commission / Project Officer

Advisory BoardScientific Partners

Consortium Partners

Coordination Committee: WP Leaders

• Work Package leaders, who will be responsible for the realisation of the tasks and deliverables of each Work Package, will report the results at each CC meeting.

• CC is responsible for reporting Partner’s contribution to the project trough the half year reports.

• CC decides on all significant WP modifications and use of finances. The partners consults CC in case of disagreement trough the Coordinator and decide jointly

• CC will assess the performance of the Coordinator, the Contractors and Project management Team.

• General assembly is the ultimate decision body

Project Management Team

The team will be located at CNR: • C. Marangi and. D. Torri to audit the R&D performance of

the project and ensure accomplishment of the technical and scientific objectives as well as project management.

• B. Biagi and F. Lovergine will support the coordinator in data handling as well as for dissemination activities.

• G. Bono will carry out administration of financial matters

• Tools for communication between the coordinator and the project members.

BIO_SOS Consortium

CNR Italy

UOI Greece

CE.R.T.H. Greece

AlterraNetherlands

ATREE India

PKI Italy

ALTAMIRA Spain

UNIBA Italy

CIBIO Portugal

UNIMIB Italy

ABERY UK

IRD France

PKH Greece

ASI Italy

BACRES Italy

[email protected]

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Third Party making their Resources available to a beneficiary.

• University of Porto will make available resources, i.e. contribution in kind via the contribution of Dr. João Pradinho Honrado to beneficiary Partner 9, ICETA/CIBIO, within WPs

– In Portugal, scientific research is mostly performed in research centers, usually connected to the universities and funded by the Ministry of Science and Higher Education (through FCT - Fundação para a Ciência e a Tecnologia).

– Many faculty members of Portuguese universities do most of their research in such centers.

– ICETA is a private, non-profit institution for research, of which the University of Porto is one of the founder members. ICETA has lot of researchers who are scientifically grouped into centres according to their research expertise. CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, is one of those ICETA centers. CIBIO is not a legal entity.

– As a faculty member of the University of Porto, Dr. Honrado is employed and paid by the University of Porto, which is a public university under the Ministry of Science and Higher Education.

– As a faculty member of the University of Porto, Dr. Honrado is allowed to perform research (and coordinate projects, WPs or tasks) in ICETA-CIBIO, but he does not have any contract or other legal relation with ICETA (other than that resulting from the statute of the University of Porto as founder associate of ICETA).

Documents

BIO diversity multi-source monitoring S ystem: from S pace T O S pecie