BIOSOS
Biodiversity Multi-Source Monitoring System: From Space TO Species

ABSTRACT

The main objective of BIO_SOS is the development of a knowledge-based pre-operational ecological modelling system suitable for effective and timely multi-annual monitoring of NATURA 2000 sites and their surrounding areas particularly exposed to different and combined type of pressures.
Study areas located in three Mediterranean and two Western Europe Countries have been considered.
To extrapolate from European test cases additional areas are being considered in two tropical countries (i.e., Brazil and India) allowing the methods to be more generally applied.

PRINCIPAL INVESTIGATOR AND PROJECT COORDINATOR
PALMA BLONDA

DATA SHEET

   TYPE AND DATE
   FP7 / CP
   STARTING DATE – Oct 1, 2010
   ENDING DATE – Nov 30, 2013

COST
TOTAL COST €: 3.102.083,77
TOTAL FUNDING € 2.476.363,71

CNR ISSIA
COST € 583.395,46
FUNDING € 480.500,00

SUMMARY

Based on the expert knowledge of botanists, ecologists and end local site managers, BIO_SOS has developed the Earth Observation Data for Habitat Monitoring (EODHaM) classification system, that is able to integrate remotely sensed data from a satellite sensor and ground reference data. Land Cover/ Land Use (LCLU) and habitat classes are described by the experts in terms of their temporal characteristics and spatial relationships and this information is used in the classification. Consequently, the EODHaM products will be more familiar to the End Users since they are built on their expertise and can be improved as they further engage with the process. Once land cover classes and habitats are described through a semantic language in an appropriate scale, any site can theoretically be mapped and subsequently monitored over time. Wherever it is difficult to provide expert rules for describing classes of interest, specific ground data can be collected.  This is only necessary in specific attentive (homogenous) areas identified by remote sensed data, with this resulting in a reduced requirement for in-situ campaigns. BIO_SOS has also developed a habitat and landscape modeling framework to assess relationships between both spectral feature/landscape structure indices and biodiversity surrogates, and community structure indicators relevant to the “Essential Biodiversity Process”.

Across a range of scales, NATURA 2000 sites, which have been designated for protecting biodiversity and ecosystems are still threatened by human activities, such as logging, mining, poaching, agricultural intensification, contamination, infrastructure development for tourism and spillage of wastes. Whilst such events and processes may occur within the boundary of protected sites, often they take place in the surrounding landscape, and particularly, where urban areas agriculture or touristic sites are in close proximity. The cumulative effect of such activities through time can eventually lead to habitat loss, degradation and fragmentation. In the past, such changes have rarely been monitored effectively or routinely.

In the European Union (EU), the Habitats Directive (92/43/EEC) and the Birds Directive (79/409/EEC) oblige Member States to report on the conservation status of species and habitats of European importance every six years and trends in status during the intervening period. However, as reported by the European Topic Centre on Biodiversity, data on species, and especially habitats, are collected in different ways, are unavailable or are insufficient in their spatial coverage. For these reasons, the development of a uniform observation system, which  can be easily used by all Member States for reporting obligations and defining management strategies (either strategic or operational) is very important. This is particularly the case in Mediterranean
countries, which typically lack long-term baseline data for assessing changes and evaluating biodiversity indicator trends. Common requirements expressed by the end-users:

  • Long-term baseline data (e.g., thematic maps at 1:5000 scale or finer) of land covers types and habitats, as well as new automatic, standardised, rapid and cost-effective monitoring techniques. These are  needed to meet commitments, define management policies and assess the impacts of existing policy;
  • A means of reducing costs, mainly related to in-field campaigns;
  • Methods for assessing the significance of measured land cover changes and evaluating trends;
  • Modelling techniques for evaluating the combined impact that different drivers affecting soils and/or vegetation may have on biodiversity over time.

The BIO_SOS project is providing local and regional authorities the following services:

  • Very detailed LCLU maps, based on the integrated analysis of (as a minimum) two high or mainly very high spatial resolution satellite images.
  • Specific layers from the LCLU map, such as:
    •  Permanent grasslands
    •  Deciduous forest
    • Coniferous forest
  • General Habitat Categories (GHCs) maps derived from land cover/use maps, based on a set of expert knowledge rules and ancillary data. The set of rules can also be applied to pre-existing validated land cover/use maps or to historical satellite images.
  • Annex 1 Habitat maps derived from LCLU maps and ancillary data, based on a set of expert knowledge rules.
  • Annex 1 Habitat maps derived from GHC maps and ancillary data, based on a set of expert knowledge rules.
  • Specific layers from the Annex I map, depending on the site such as: 7210; 1310; 2110; 2250; 1150; 62A0
  • Intermediate produced information layers, such as the spectral indices derived ones to be used for landscape modelling: NDVI; WBI; PSRI
  • Land cover/use and habitat change maps, which are obtained by comparing maps from different years.

In addition, the project is also providing:

  • Biodiversity indicators from remotely sensed data, such as PLAND, CA, MESH, PD, SHAPE and MPS
  • Biodiversity indicator trends tackling biodiversity pressure scenarios through the assessment of indicators evolution over time.
  • A dedicated geoportal for metadata

The EODHaM system is implemented as open source software written in python.

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SOURCE OF FOUNDING

PARTNERSHIP

National Research Council of Italy (CNR)
University of Ioannina (UOI), Greece
Centre for Research and Technology Hellas (CE.R.T.H.) Greece
Alterra, Wageningen UR, The Netherlands
Ashoka trust for Research in Ecology and the Environment (ATREE), India
Planetek Italia SRL (PKI), Italy
Altamira Information SL (ALTAMIRA), Spain
Università degli Studi di Bari “ALDO MORO” (UNIBA), Italy
ICETA – Instituto de Ciências e Tecnologias Agrárias e Agro-Alimentares (CIBIO), Portugal
Università degli Studi di Milano-Bicocca (UNIMIB), Italy
Aberystwyth University (ABER), United Kingdom
Institut de Recherche pour le Developpement (IRD), France
Planetek Hellas (PKH), Greece
Baraldi Consultancy in Remote Sensing, Italy
University Paul Sabatier (UPS-CESBIO), France