European Topic Centre for Spatial information and Analysis

Tuesday, July 10th, Background Literature

Michael Bock (DLR):

Monitoring and modeling of habitats with Earth observation

Birgen Haest (VITO), Jeroen Vanden Borre, Toon Spanhove (INBO):

Remote sensing for Natura 2000 monitoring - A methodological concept to consolidate what we can measure and what we need to measure

The habitats protected by the Habitats Directive are listed in its Annex 1. It currently lists 231 habitat types in nine major habitat formations. The list of habitats is very heterogeneous; the majority are defined by vegetation, but some are defined by physiographic features that may contain vegetated and unvegetated parts of different kinds. They may occur at a high variety of scales (from point locations up to complete landscapes), and also differ greatly in their inherent variability. Furthermore, local habitat quality assessment, i.e. specific structures and functions, encompassing typical species and various indicators, again differ for each of the habitat types, and vary in spatial scales. Several member states have elaborated a framework to assess the local quality of habitat locations, using indicators and threshold values that are adapted to the country-specific variability of the habitats. Direct measurement or mapping using remote sensing of both habitat types and their quality is in most cases hampered exactly by this large scale-variability and inherent composition variability. Habitat types consist of various ‘land cover and vegetation types’, which can occur in numerous other habitat types, and moreover can be have wide ranges of composition of these specific covers.

In this presentation, we will provide a methodological framework and examples to overcome these difficulties, both in the context of habitat type mapping and local habitat quality assessment. The framework shows how to: (1) use ‘land and vegetation cover’ as spatial building blocks to construct habitat type maps; and (2) extract local habitat quality information that is not directly measurable due to its inherent small-scale occurrence. Or, in short, how to consolidate what we can measure and what we need to measure.

References:

Haest, B.et al. (2010): An object-based approach to quantity and quality assessment of heathland habitats in the framework of natura 2000 using hyperspectral airborne ahs images. Third international conference on all aspects of GEOGRAPHIC OBJECT-BASED IMAGE ANALYSIS, Ghent, Belgium, 29 June — 2 July. - Ghent, Belgium : 2010 (paper 211 )

Martínez. S. & Mollicone, D. (2012): From Land Cover to Land Use: A Methodology to Assess Land Use from Remote Sensing Data. Remote Sensing 4, no. 4: 1024-1045. 10.3390/rs4041024

Spanhove, T., Vanden Borre, J., Delalieux,S., Haest, B. & Paelinckx, D. (2012): Can remote sensing estimate fine-scale quality indicators of natural habitats? Ecological Indicators 18: 403-412. 10.1016/j.ecolind.2012.01.025.

Vanden Borre, J., Paelinckx, D., Mücher, C.A, Kooistra, L., Haest, B., De Blust, G. & Schmidt, A.M. (2011): Integrating remote sensing in Natura 2000 habitat monitoring: Prospects on the way forward. Journal for Nature Conservation 19 (2): 116-125. 10.1016/j.jnc.2010.07.003.

Doug Evans (ETC/BD):

The EUNIS habitats classification

References:

Evans, D (2012) The  EUNIS habitats classification - past, present & future. Revista de Investigación Marina 19(2): 28-29.

Stefan Lang (PLUS):

The MS.MONINA approach: Multi- scale services for habitat monitoring

References:

Vanden Borre, J., Haest, B., Lang, S.,  Spanhove, T.,  Forster, M. & Sifakis, N.I. (2011): Towards a Wider Uptake of Remote Sensing in Natura 2000 Monitoring: Streamlining Remote Sensing Products with Users’ Needs and Expectations. 2^nd International Conference on Space Technology. 1-4.

Francisco Javier Bonet (UGR):

Sierra Nevada Global Change Observatory.

References:

Bonet, F.J.; Aspizua, R.; Zamora, R.; Sánchez, J.F., Cano Manuel, F.J & Henares, I. (2011): Sierra Nevada Observatory for Monitoring Global Change: Towards the Adaptive Management of Natural Resources. In: Austrian MAB Committee (ed.): Biosphere Reserves on the Mountains of the World. Excellence in the Clouds? 48-52.

Bonet, F.J.; Pérez-Luque, A.J.; Moreno, R. & Zamora, R. (2010). Sierra Nevada Global Change Observatory. Structure and Basic Data. Environment Department (Andalusian Regional Government)

Monday, July 9th, Background Literature

Allan Watt:

The Biodiversity concept at the science-policy interface: How to improve the conservation and sustainable use of biodiversity?

Desiré Paelinckx:

From EU Biodiversity Strategy to local conservation status

References:

Louettea, G, et al. (2011): Bridging the gap between the Natura 2000 regional conservation status and local conservation objectives. Journal for Nature Conservation 19: 224-235. doi:10.1016/j.jnc.2011.02.001

Roger Milego:

Biodiversity OLAP Cube in the framework of the INBALUD project

References:

Kleeschulte, S. et al (2011): Integrating nature & biodiversity and land use data – Final Report. Output of the project: INBALUD - Integrating Nature & biodiversity and land use data. GeoVille Environmental Services, Luxembourg.

Lena Pernkopf:

Structural indicators - The concept of landscape metrics

Landscapes exhibit specific patterns or mosaics of constituting elements (e.g. habitat patches), and this heterogeneity is measurable and can be quantified. The quantitative assessment of landscape structure gains importance for a wide range of landscape ecological applications. Landscape ecology investigates the relationships between pattern and process, i.e. how ecological processes are influenced or even driven by the spatial configuration of ecological units (patches). Analysis of the landscape pattern gives insight into processes and functions, and above that, into potentials or services provided. Originating from the quantitative branch of North American landscape ecology, these ideas have meanwhile settled in European landscape applications and spatial ecological research. A broad set of quantitative measures, called landscape metrics, has been elaborated. Structural indicators, based on landscape metrics, describe habitats in terms of size, shape, and neighbourhood relations. They express in mathematical terms the arrangement and configuration of habitat patches in a specific area of interest. They characterize different spatial properties of landscape units by specific measures or in an aggregated manner using basic statistical values (mean, standard deviation, etc.). The session will provide an overview on different aspects of quantitative landscape structure assessment and will provide the theoretical background for a related lab session.

Doug Evans:

Monitoring & reporting under the Habitats Directive: Lessons learnt at European and national level.

References:

Evans, D. (2005). Natura 2000 – completing the EU’s network of sites to conserve flora & fauna. Plant Talk 39: 22 –27.

Evans, D. (2012). Building the European Union’s Natura 2000 network. Nature Conservation 1: 11 – 26. 10.3897/natureconservation.1.1808

Sipkova, Z., Balzer, S., Evans D. & Ssymank, A. (2010). Assessing the conservation status of European Union habitats – results of the community report with a case study of the German national report. Annali di Botanica 1: 19-37.

Vasiliki Hrisopolitou (EKBY):

Reporting requirements according to Article 17 of the Habitats Directive: Lessons learnt from the second Greek national report.