Geoffrey H. Griffiths

Landscape pattern and species richness; regional scale analysis from remote sensing

Concern about the future of biodiversity in the wider countryside is stimulating the development of methods for species and ecosystem monitoring over large areas. The objective of this paper is to explore the potential of remotely sensed data for measuring landscape structure as an important determinant of species diversity. Data from the satellite Land Cover Map of Great Britain, a land cover classification of Landsat Thematic Mapper scenes, were used to derive a set of simple measures of landscape structure within 2km x 2km tetrads for three vascular plant families. Results from a model to predict plant diversity from landscape structure alone proved difficult to interpret ecologically and highlighted the need to obtain data on both landscape quality and landscape structure.

The mapping of hydrothermal alteration zones on the island of Lesvos, Greece using an integrated remote sensing dataset

The mapping of hydrothermal alteration zones associated with epithermal gold deposits on the island of Lesvos in Greece has been carried out using Landsat Thematic Mapper (TM) satellite and ground remote sensing data. The initial analysis of the satellite data using the minimum noise fraction, matched filter and spectral unmixing techniques identified the altered rock outcrops clearly. The identified pixels were almost completely contained within the highest grade alteration zones mapped by the field geologists. The analysis of the field spectroscopy data using two quantitative techniques, spectral angle mapper and cross-correlogram spectral matching, identified clearly the presence of high grade kaolinite and alunite outcrops. The further application of the matched filter and spectral unmixing techniques using the additional information from the field spectroscopy survey identified the outcrop of alunite and kaolinite quite clearly. This study indicates the ability of existing satellite data combined with atmospheric correction and novel image processing techniques to locate the regions of highest mineral prospectivity. The addition of a limited amount of field spectroscopy data into the processing of the satellite data suggests that two of the most diagnostic clay minerals can be differentiated.

Landscape Characterisation: The Living Landscapes Approach in the UK

Abstract This paper describes refinements to the process of landscape characterisation that have been developed by the Living Landscapes Project (LLP) within the context of the now widely adopted approach to Landscape Character Assessment (LCA) in England. The Living Landscapes project was developed in an attempt to improve the consistency of LCA at different spatial scales within the UK. This was achieved by the introduction of the Land Description Unit (LDU) into the process of LCA, enabling users to develop a consistent spatial framework based upon relatively homogeneous landscape units that reflect differences in the natural and cultural dimensions of landscapes at different scales. The paper describes the method and demonstrates its potential for improved mapping within the Peak District National Park, in the UK.

A GIS-based empirical model for vegetation prediction in Lefka Ori, Crete

The aim of the study was to establish and verify a predictive vegetation model for plant community distribution in the alti-Mediterranean zone of the Lefka Ori massif, western Crete. Based on previous work three variables were identified as significant determinants of plant community distribution, namely altitude, slope angle and geomorphic landform. The response of four community types against these variables was tested using classification trees analysis in order to model community type occurrence. V-fold cross-validation plots were used to determine the length of the best fitting tree. The final 9node tree selected, classified correctly 92.5% of the samples. The results were used to provide decision rules for the construction of a spatial model for each community type. The model was implemented within a Geographical Information System (GIS) to predict the distribution of each community type in the study site. The evaluation of the model in the field using an error matrix gave an overall accuracy of 71%. The user’s accuracy was higher for the Crepis–Cirsium (100%) and Telephium–Herniaria community type (66.7%) and relatively lower for the Peucedanum–Alyssum and Dianthus–Lomelosia community types (63.2% and 62.5%, respectively). Misclassification and field validation points to the need for improved geomorphological mapping and suggests the presence of transitional communities between existing community types.

Historic Landscape Reconstruction and Visualisation, West Oxfordshire, England

As part of the Wychwood Project in West Oxfordshire, England, aerial photography and historic maps are being used to reconstruct landscape change in the former medieval Royal Hunting Forest of Wychwood. An important objective of the project is to stimulate local interest in Wychwood and promote understanding of its evolution, thereby encouraging the support of stakeholders in the design of future landscapes. The parish of Leafield was selected to develop and test a method for reconstructing and visualising past and present landscapes to present to the public for evaluation and comparison. Leafield contains fine examples of both early and late enclosure landscapes and underwent large-scale disafforestation following the Enclosure Act of 1856. Ordnance Survey (O.S.) 1:10000 Landform Panorama contour data were used to create a digital elevation model (DEM) of the parish using ArcView 3D Analyst, enabling the user to create perspective views of the landscape from any height and viewing angle. Contemporary aerial photography was scanned and geo-rectified to create an overlay for ‘draping’ onto the DEM. Historical maps provided the reference for modifying the aerial photography using the PaintShop Pro graphics package. This paper presents and reviews the results and compares the method with other techniques, including VRML.

Pattern Analysis And The Ecological Interpretation Of Satellite Imagery

Simple descriptions of the area and distribution of different land cover types is only the first stage in deriving ecological information from satellite imagery. This paper describes a number of measures of landscape pattern that have been developed to assist in defining the ecological characteristics of a sample of lowland and upland areas in the United Kingdom. The results suggest that raster-based image analysis techniques can be used effectively to measure various parameters of landscape pattern from Landsat Thematic Mapper imagery.

Habitat associations of the Small Red Damselfly (Ceriagrion tenellum) (De Villiers) in heathland in southern England (Zygoptera: Coenagrionidae)

The Small Red Damselfly (Ceriagrion tenellum) (De Villiers) (Odonata: Coenagrionidae: Ceriagrion) is classed as vulnerable (Shirt, British Red Data Book, Nature Conservancy Council, Peterborough, UK, 1987) throughout the UK, and is included in certain Local Biodiversity Action Plans (LBAPs) in the south. A large proportion of any Biodiversity Action Plan is concerned with the requirement of conservation and management programmes. In order to guide them, information about the habitat preferences of the species concerned is vital. Detailed habitat information was collected to include a variety of physical parameters particularly vegetation, both in-channel and bankside. The species was found to be primarily associated with in-channel emergent broad-leaved plants, bankside grasses and rushes, and shallow, narrow channels with dark organic substrate. The consequences of these findings are discussed in relation to the conservation and management of C. tenellum.

Species distribution model transferability and model grain size – finer may not always be better

Species distribution models have been used to predict the distribution of invasive species for conservation planning. Understanding spatial transferability of niche predictions is critical to promote species-habitat conservation and forecasting areas vulnerable to invasion. Grain size of predictor variables is an important factor affecting the accuracy and transferability of species distribution models. Choice of grain size is often dependent on the type of predictor variables used and the selection of predictors sometimes rely on data availability. This study employed the MAXENT species distribution model to investigate the effect of the grain size on model transferability for an invasive plant species. We modelled the distribution of Rhododendron ponticum in Wales, U.K. and tested model performance and transferability by varying grain size (50 m, 300 m, and 1 km). MAXENT-based models are sensitive to grain size and selection of variables. We found that over-reliance on the commonly used bioclimatic variables may lead to less accurate models as it often compromises the finer grain size of biophysical variables which may be more important determinants of species distribution at small spatial scales. Model accuracy is likely to increase with decreasing grain size. However, successful model transferability may require optimization of model grain size.

Geospatial tools for landscape character assessment in Cyprus

The development of Landscape Typologies in Europe relies upon advances in geospatial tools and increasing availability of digital datasets. Landscape Character Assessment (LCA) is a technique used to classify, describe and understand the combined physical, ecological and cultural characteristics of a landscape. LCA uses a range of data sources to identify and describe areas of common character and can operate at a range of scales i.e.national and regional and local. The paper describes the steps taken to develop an island wide landscape typology for Cyprus, based on the use of GIS and remote sensing tools. The methodology involved integrating physiographical, ecological and cultural information about the Cypriot landscape. Datasets on the cultural attributes (e.g. settlement and field patterns) were not available, so they were created de novo based on information from topographical maps (for settlement dispersion and density) and medium resolution satellite imagery from Google Earth, from which a number of distinctive field patterns could be distinguished. The mapping work is carried out on two levels using a hierarchical approach. The first level at a 1:100, 000 scale has been completed resulting in a map with 17 distinct landscape types. The second level is under way with the view of producing a more detailed landscape typology at 1:50, 000 scale which will incorporate the cultural aspects of the island. This is the first time that such a typology has been produced for Cyprus and it is expected to provide an invaluable tool for landscape planning and management.

Predictive Vegetation Mapping in the Mediterranean Context: Considerations and Methodological Issues

The need to map vegetation communities over large areas for nature conservation and to predict the impact of environmental change on vegetation distributions, has stimulated the development of techniques for predictive vegetation mapping. Predictive vegetation studies start with the development of a model relating vegetation units and mapped physical data, followed by the application of that model to a geographic database and over a wide range of spatial scales. This field is particularly important for identifying sites for rare and endangered species and locations of high biodiversity such as many areas of the Mediterranean Basin. The potential of the approach is illustrated with a mapping exercise in the alti-meditterranean zone of Lefka Ori in Crete. The study established the nature of the relationship between vegetation communities and physical data including altitude, slope and geomorphology. In this way the knowledge of community distribution was improved enabling a GIS-based model capable of predicting community distribution to be constructed. The paper describes the development of the spatial model and the methodological problems of predictive mapping for monitoring Mediterranean ecosystems. The paper concludes with a discussion of the role of predictive vegetation mapping and other spatial techniques, such as fuzzy mapping and geostatistics, for improving our understanding of the dynamics of Mediterranean ecosystems and for practical management in a region that is under increasing pressure from human impact.