Translating land cover/land use classifications to habitat taxonomies for landscape monitoring: a Mediterranean assessment

Valeria Tomaselli,Caspar A Mücher,Richard Lucas,Francesco Lovergine,Paola Mairota,Carmela Marangi,Maria Adamo,Athanasios S Kallimanis,Panayotis Dimopoulos,Giuseppe Veronico,Maria Panitsa,Massimo Terzi,Cristina Tarantino,Harini Nagendra,Palma Blonda

doi:10.1007/s10980-013-9863-3

Abstract

Periodic monitoring of biodiversity changes at a landscape scale constitutes a key issue for conservation managers. Earth observation (EO) data offer a potential solution, through direct or indirect mapping of species or habitats. Most national and international programs rely on the use of land cover (LC) and/or land use (LU) classification systems. Yet, these are not as clearly relatable to biodiversity in comparison to habitat classifications, and provide less scope for monitoring. While a conversion from LC/LU classification to habitat classification can be of great utility, differences in definitions and criteria have so far limited the establishment of a unified approach for such translation between these two classification systems. Focusing on five Mediterranean NATURA 2000 sites, this paper considers the scope for three of the most commonly used global LC/LU taxonomies—CORINE Land Cover, the Food and Agricultural Organisation (FAO) land cover classification system (LCCS) and the International Geosphere-Biosphere Programme to be translated to habitat taxonomies. Through both quantitative and expert knowledge based qualitative analysis of selected taxonomies, FAO-LCCS turns out to be the best candidate to cope with the complexity of habitat description and provides a framework for EO and in situ data integration for habitat mapping, reducing uncertainties and class overlaps and bridging the gap between LC/LU and habitats domains for landscape monitoring—a major issue for conservation. This study also highlights the need to modify the FAO-LCCS hierarchical class description process to permit the addition of attributes based on class-specific expert knowledge to select multi-temporal (seasonal) EO data and improve classification. An application of LC/LU to habitat mapping is provided for a coastal Natura 2000 site with high classification accuracy as a result.

Highlights

Effective and timely multi-annual biodiversity monitoring of protected sites and other endangered and biologically important landscapes is critical for detecting changes which might impact on a site’s conservation status, quality and resources (Townsend et al 2009)
Focusing on five Mediterranean NATURA 2000 sites, this paper considers the scope for three of the most commonly used global LC/land use (LU) taxonomies—CORINE Land Cover, the Food and Agricultural Organisation (FAO) land cover classification system (LCCS) and the International Geosphere-Biosphere Programme to be translated to habitat taxonomies
The comparison of the different habitat legends highlighted several omissions in the Annex I scheme with respect to European Nature Information System (EUNIS), for the sites considered (Table 2), namely: (a) different shrub vegetation types of high conservation value; (b) nitrophilous and subnitrophilous grasslands that are often functionally linked to Annex I habitat types; (c) reeds and sedges communities, as already highlighted by Petermann and Ssymank (2007)

Summary

Introduction

Effective and timely multi-annual biodiversity monitoring of protected sites and other endangered and biologically important landscapes is critical for detecting changes which might impact on a site’s conservation status, quality and resources (Townsend et al 2009). Such monitoring is essential to evaluate the effectiveness of conservation policies in protecting biodiversity and ecosystems from human activities The advent of very high resolution (VHR) satellites (i.e., spatial resolution: \3 m) has provided opportunities for more detailed mapping and studies of changes in habitat coverage, landscape fragmentation, and human pressure, albeit over smaller areas through comparison with pre-existing validated fine-grain (1:5,000 or better) maps obtained by orthophoto visual interpretation and in-field campaigns. Habitats offer greater scope for linking EO data to biodiversity

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