Feldmeyer-Christe, E. (Ed.). (2003). State of the art in vegetation monitoring approaches. International Symposium. Swiss Federal Research Institute.

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State of the Art in

Vegetation Monitoring Approaches

International Symposium: March 24-26, 2003

Swiss Federal Research Institute WSL Birmensdorf, Switzerland

Abstracts

Editor: Elizabeth Feldmeyer-Christe

Published by

Swiss Federal Research Institute WSL, CH-Birmensdorf 2003

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The International Symposium "State of the Art in Vegetation Monitoring Approaches" was held from March 24 to 26, 2003 in Birmensdorf, Switzerland.

This book of abstracts contains 47 papers presented at this symposium. The contributions include methodological aspects of short- to long-term vegetation monitoring, descriptive analyses,

environmental modeling as well as the management (developing and updating) aspects of large data bases.

The symposium addressed the following topics in the field of vegetation monitoring: GIS, remote sensing and spatial modeling approaches; design and strategies for short- and long-term

monitoring; statistical methods and their applications.

Symposium organizers:

Dr. Elizabeth Feldmeyer-Christe, Associated Researcher, WSL Margrit von Euw, Secretary, WSL

Symposium Scientific Committee:

Dr. Elizabeth Feldmeyer-Christe Dr. Sucharita Ghosh

Dr. Niklaus Zimmermann

All Associated Researchers at the WSL

A proposal for short and long term monitoring strategies:

hierarchical landscape classification and Vegetation Series Map of Italy

Carlo Blasi1, Maria L. Carranza², Romeo Di Pietro 1, Leonardo Filesi³, Goffredo Filibeck¹and Leonardo Rosati¹

1 Department of Plant Biology, University of Rome "La Sapienza", Piazzale Aldo Moro 5, 1-00185 Rome, Italy.

carlo.blasi@uniroma1.it, romeo.dipietro@uniroma1.it, g.filibeck@libero.it, leo.ros@libero.it

2 Di.S.T.A.T., Faculty of Mathematics, Physics and Natural Sciences, University of Molise, Via Mazzini 8, 1- 86170 lsernia, Italy. laura.carranza@uniroma1.it

3 University of Venice, Ca' Tron, Santa Croce 19571-30135 Venice, Italy.leonardo.filesi@unive.it

The national programme "Completamento delle Conoscenze Naturalistiche di Base in Italia"

(Ecological Information in Italy), funded by the Nature Conservation Department of the Italian Ministry of Environment, includes a wide range of projects covering the main topics of ecological research, such as Fauna, Flora, Vegetation, Wetlands, Marine Biology, Land Cover Mapping, Bioclimate. One of the aim of this project is the development of a 1 :250,000 map of the major Vegetation Series of Italy.

The method for mapping Vegetation Series (Potential Vegetation) is based on a hierarchical land classification, obtained by integrating litho-morphological and phytoclimatical GIS layers.

Geological and bioclimatical maps were produced for this project. Land classification generated a 1 :250,000 map of land units, defined by the combination of litho-morphological and bioclimatical types. Each land unit was then assigned to a Vegetation Series identified on phytosociological basis using the association or the alliance level.

Vegetation Series result from the deductive and inductive processes: land units are defined through a hierarchical land classification (deductive or descending approach), whereas their vegetation attributes, that is the Potential Vegetation, are obtained from phytosociological data (inductive or ascending approach).

The Vegetation Series Map of Italy will be an extremely important tool for environmental monitoring, planning and assessment. Besides their high information content, land units are also easily comprehensible by local public administrators and policy-makers. Furthermore, the

correspondence between land units and Vegetation Series allows to evaluate the distance between the actual and potential vegetation, crucial element for assessing environmental quality.

Keywords: hierarchical landscape classification, land units, vegetation series map.

In: Feldmeyer-Christe, E. (ed) 2003: State of the Art in Vegetation Monitoring Approaches. Abstracts.

International Symposium, March 24-26, 2003. Birmensdorf, Swiss Federal Research Institute WSL.

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Evaluation of Gabor filters for natural scene analysis

Ruedi Boesch

WSL Swiss Federal Research Institute, ZOrcherstrasse 111, CH-8903 Birmensdorf, Switzerland.

ruedi.boesch@wsl.ch

Although many classifier models can be used for vegetation classification, landscape patterns have to be detected by crucial feature extraction methods. Therefore special attention is given to feature extraction methods, which focus on the varying characteristic of landscape pattern data. Texture analysis continues to be a bottleneck for natural scene interpretation. Texture is one of the basic characteristics of vegetation scenes and of similar importance as color.

The Gabor representation has been shown optimal in the sense of minimizing the joint two- dimensional uncertainty in space and frequency. Bovik et al. (1990) further emphasized that 2-0 Gabor filters have been shown to be particularly useful for analyzing texture images containing highly specific frequency or orientation characteristics. There are still many open research

questions which scales of natural features in landscape data (e.g. forests) contain such frequency- and orientation-specific patterns (Manjunath 1996, Shao 1994).

Many different implementations of Gabor texture filters can be found in literature. Therefore the following work focuses on an objective comparison of texture detection performance. Adaptive object recognition (Draper 1999) provides a suitable approach to dynamically select vision procedures based on a Markov decision process and allows a systematic evaluation either by heuristic or back-propagation search methods.

Keywords: pattern recognition, vegetation classification, evaluation References:

Bovik, A. C., Clark, M. and Geisler, W.S. "Multichannel Texture Analysis Using Localized Spatial Filters", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 12, No. 1, pp. 55-73, 1990.

Draper B., J. Bins, and K. Baek, "ADORE: Adaptive object recognition," in Proc. International Conference on Vision Systems, pp. 522-537, (Las Palmas de Gran Canaria, Spain), Jan. 1999.

Manjunath B.S., W.Y. Ma, "Browsing large satellite and aerial photographs", Proc. third IEEE international conference on Image Processing ( ICIP '96), Vol. II, pp. 765-768, Lausanne, Switzerland, April1996.

Shao J., Forstner W, Gabor Wavelets for Texture Edge Extraction. ISPRS Commission Ill Symposium on Spatial Information from Digital Photogrammetry and Computer Vision, September 5-9, Munich, Germany, 1994.

8 In: Feldmeyer-Christe, E. (ed) 2003: State of the Art in Vegetation Monitoring Approaches. Abstracts.

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Spatial classification uncertainty in the historical landscape of Wisconsin (USA}

Janine Bolliger¹·2

1 WSL Swiss Federal Research Institute, Zurcherstrasse 111, CH-8903 Birmensdorf, Switzerland.

2 Department of Forest Ecology and Management, University of Wisconsin-Madison, Madison WI 53706, USA janine.bolliger@wsl.ch

Enviromental policy makers require spatial baseline data to develop management, conservation, or restoration goals. Visualization of areas of interest requires reduction of the data into a comprehensive format and recognition of natural groupings. The process of generalization and aggregation of landscape properties usually involves various classification methods. Geographical phenomena, however, are usually not distinct or discrete; rather they spread along spatial continua and exist as class intergrades, featuring classification error and uncertainty. As there is a growing need to use spatial data for providing ecological application and policies, it is thus relevant to quantify classification errors and uncertainties, and to assess implications for the relationship between spatial uncertainty and the decision-making process.

In this paper, two landscape classification methods originating from a discrete and continuous classification approach are presented for the historical landscape of Wisconsin (USA). The classifications rely on the U.S. Public Land Office Surveys, conducted during the 19^thcentury for selling the land to Euro-American settlers.

The discrete classification method involves a probabilistic hierarchical cluster analysis. The continuous classification is represented by fuzzy classification. Conceptually, discrete cluster analysis relies on the assumption that each location has a specific, crisp property. Fuzzy classification, however, accounts for the continuous nature of geographical phenomena in a landscape.

Classification accuracies between the methods are reported using global statistics (pixel-by- pixel comparisons: confusion matrices, Kappa statistics; pattern comparisons using landscape metrics). Although these metrics give an overall measure of the overall classification accuracy, no information is given about the spatial variation of the classification accuracy, and the global classification accuracy may not be applicable to subregions of the landscape. Classification errors (membership exaggeration, membership ignorance) due to the mixed grade, intergrade, and extragrade nature of geographic phenomena may not be known, but may be approximated by classification uncertainty. Local uncertainty maps can be derived from fuzzy classification using two kinds of uncertainties (Zhu 1997): (1) extent of an entity to belong to a prescribed set of classes, (2) deviation from the class to which the entity is assigned. Both uncertainties are calculated for every spatial location to derive uncertainty maps. Implications and challenges are discussed for

classification application such as vegetation monitoring, and conservation success controls.

Keywords: historical landscape, Wisconsin, United States General Land Office Surveys, classification, fuzzy clustering, cluster analysis, spatial uncertainty, entropy

References:

Zhu, A.-X. 1997. Measuring uncertainty in class assignment for natural resource maps under fuzzy logic.

Photogrammetric Engineering & Remote Sensing 63: 1195-1202.

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An integrated system for vegetation and landscape monitoring in Europe

Bob Bunce 1, Rob. Jongman1, Berien Elbersen1, Marc Metzgef, Sander Mucher¹and Marta Perez- Soba ¹

1 Alterra Green World Research, Post-box 47, NL-6700 AA Wageningen, The Netherlands.

r.g.h.bunce@alterra.wag-ur.nl

2 Wageningen University, Plant Production Systems Group, Haarweg 333, NL-6709 AZ Wageningen, The Netherlands

The richness and diversity of the landscapes in Europe are unique in the world. The complexity of factors that contribute to the shaping of Europe's landscapes is reflected in the values attached to them. In order to assess the changes in European landscapes and related changes in biological functioning, cultural and aesthetic values an integrated monitoring approach is a prerequisite. One of the major preconditions for a European wide monitoring system is a good sampling strategy.

However, not only sampling strategies are important, there are also many projects and initiatives dealing with assessment of the European environment and landscapes, which need to be mentioned.

Environmental classification of Europe is a way forward to develop a stratified random sampling strategy as well as a basis for interpretation of both vegetation and landscape data. Field data sampling should be unified, for instance using the EEA-EUNIS classification and agreed methods for vegetation sampling.

Classifications have already been available for about ten years. The first classifications were simple, because of data restrictions and lack of sufficient computer power. Nowadays classifications can be made almost without restrictions at the European level, bearing in mind the limitations of the scale of the data. At present a spine classification of about 70 classes for Europe is under development. This classification can be merged into larger units for different purposes. Potential uses are merging into biogeographic zones for biodiversity assessment and merging the spine classes into 32 classes for ecosystem vulnerability assessment.

Procedures have been developed for linking vegetation records, habitat and landscape features using the framework of the environmental classification. This paper will describe this procedure which has been developed in conjunction with a working group of the international Association for Landscape Ecology.

Keywords: environmental classification, Europe, stratified random samples, consistent data, surveillance, monitoring

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Monitoring British woodland vegetation 1971-2002

R.G.H. Bunce¹•2

, S.M. Smart', H. Black' and K. Kirby\

1 CEH Merlewood, Grange-over-Sands, Cumbria UK

2 Alterra PO Box47 6700AA, Wageningen, The Netherlands

3 English Nature, Peterborough, UK

In 1971 a subset of about 2400 broadleaved woodland sites, defined as cartographic units, in Great Britain were classified using multivariate analysis into 103 classes. For each class a representative site was drawn using a statistical procedure. 16 random 200m²plots were placed in each woodland and a field survey carried out between June and September in 1971. A pilot survey was carried out in 2000. This repeated 16 of the original sites using exactly the same field procedures. Data were recorded for vascular plants and bryophytes, DBH of trees and shrubs and habitat features. In addition soil samples were collected at both dates.

The paper will present the results of this pilot re-survey, which demonstrated the validity of the approach. These showed that increased canopy closure was the primary determinant of changes in species composition and richness. Evidence of eutrophication was also detected however individual site events, such as the great storm of 1987 and extensive felling, can deflect individual woods away from the cross-site trend.

The wider significance of the results will be discussed since the changes are much greater than those indicated by many other monitoring programs for woodlands in GB. This is probably because most woodland monitoring is in nature reserves which are protected from the influences present in the wider landscape. These results demonstrate that a statistically robust approach to sampling can achieve results with even relatively few samples.

Keywords: native woodlands, Great Britain, stratified random samples, Indicator Species Analysis (TWINSPAN), monitoring

International Symposium, March 24-26, 2003. Bimiensdorf, Swiss Federal Research Institute WSL.

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The monitoring of non-equilibrium dynamics and assembly rules of vegetation: sampling scale dependence and relative coenostate descriptors by using information theory

Giandiego Campetella, Roberto Canullo and Sandor Bartha

Department of Botany and Ecology, University of Camerino, via Pontoni, 5, 1-62032 Camerino (MC), Italy

Long term vegetation monitoring provide numerous informations on spatio-temporal patterns in plant communities, which could be analysed to yield correlated changes in spatial relationship among the species and to interpret dynamical tendencies and assembly rules on non-equilibrium phytocoenosis. In this kind of studies one should take into account recent ecological theories emphasizing the scale dependence of vegetation; in particular fine-scale spatial patterns of vegetation are important constraints in the genesis and maintenance of diversity. However, few contributions have analysed explicitly the relationship between diversity and multispecies spatial dependence in vegetation. The information theory models of Juahsz-Nagy offers an appropriate tool to describe these patterns.

Diversity (florula diversity) and spatial dependence (associatum) are calculated at a series of increasing plot size (spatial scaling). The plot size at which the two coenostate descriptors reach the maximum informations (bits) represent characteristic scales that should be considered as optimal plot size in monitoring data collection. Moreover, this methodology enable us to study non-equilibrium dynamics and assembly rules in a more operational way. Diversity and spatial dependence are related but the power and direction of these relationship change by environmental characteristics, vegetation type and successional context. The demonstrated correspondence of dominant pattern generating mechanisms and the relative trajectories in abstract coenostate spaces, obtained by exploratory simulation studies, spanned by coenostate descriptors (florula diversity and associatum maximum values), can help the interpretation of dynamical state and tendencies of vegetation and offers a better inference about the relative role of different background mechanisms. We present some results obtained by this methodology with field data from the forest of Bialowieza National Park (Poland). In particular we compared the spatial patterns of herb layer of different regeneration phases of the forest. Sampling was performed by recording the presence of plant species in 1Ox10cm contagious microquadrats arranged in 150 m long circular transects. Field data were analysed with the same information theory methods as the ones applied to simulated data. Results show that assemblages of plant individuals are less diverse and more associated in primary than in secondary stands, suggesting, in both situations, competitive dominance and disturbance as main ecological mechanisms.

Keywords: dynamical tendencies, diversity, forest herb layer, competitive dominance, disturbance

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Expectations vs. reality: results and sampling design in forest monitoring programmes in Europe

Alessandro Chiarucci1, Marco Ferretti², Simona Maccherini1

1 Dipartimento di Scienze Ambientali, Universita di Siena, Via PA Mattioli 4, 1-53100 Siena, Italy.

chiarucci@unisi.it

2 LINN.LEA ambiente Sri, Firenze, Italy

International monitoring programmes are expected to provide estimates of spatial and temporal variation for a number of forest ecosystems' attributes, ranging from tree health to species diversity, to deposition of pollutants. Given the existing concern about biodiversity and the effects of trans- boundary air pollution on forest ecosystems, the policy relevance of such estimates is obvious. To meet expectations, monitoring programmes need to consider several issues, from the value of the indicators adopted to various error sources, including measurement and classification errors, sampling errors, non-statistical errors. Recently, some progress was made to improve the quality of the measurements carried out at the monitoring sites; however, the statistical requirements needed to obtain unbiased estimates of population parameters (e.g., mean and totals) as well as to allow spatial and temporal comparisons are yet to be fully considered. While this is true for both stages of sampling - selection of sites and locations of measurements within the site - here we concentrate on the second stage. Actually, many of the investigations carried out at the monitoring plots are not designed within a statistical framework and cannot be used for statistical inference, nor for spatial and temporal comparisons unless a proper model is developed. In some cases, also the use of the data in multiple regression models can be questioned, as assumptions are needed about the reliability of the obtained statistics as valid, unbiased estimates of population parameters.

Keywords: long-term, monitoring, forests, air pollution, biodiversity, sampling design

International Symposium, March 24--26, 2003. Birmensdorf, Swiss Federal Research Institute WSL.

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From plot data to spatial models: example applications from Colorado, USA

Geneva W. Chong and Thomas J. Stohlgren

The Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523-1499, geneva_chong@usqs.qov

Resource managers and scientists are continuously challenged to accurately measure and describe vegetation characteristics (e.g., biodiversity) for large, heterogeneous areas. Although existing methods and technologies may be adequate given unlimited resources, the pervasive lack of resources requires that research programs address the need for incorporating and altering existing methods and technologies into a useful process from the initial stages of defining objec- tives and sampling strategies to later stages of analyses, communication and long-term monitoring.

We introduce the history and ongoing results from a pilot vegetation sampling project in Colorado - from the development of a sampling plot and strategy to the current uses of the methods developed to implement the project. The Landscape-scale Gap Analysis research program was piloted in Rocky Mountain National Park, Colorado, USA from 1994 to 2000. Starting with the objective of an improved vegetation map to serve as a base for resource management, the program began by developing and testing multiple-scale vegetation sampling plots and continues with development of database management and analysis tools and applications of spatial and non-spatial models to extrapolate vegetation data (native and non-native species) from sampled to unsampled areas in an 80,000 ha portion of the Park. Ongoing modeling efforts to describe patterns of native and non- native vegetation find that combining trend surface and regression tree models provides the greatest explanations of variance and the lowest mean squared errors for this heterogeneous area that ranges from 2,300 m to 4,200 m above sea level. The number of native plant species in a 30 m x 30 m cell was modeled with 59% of the variance explained (N = 175 0.1 ha plots in 20 vegetation types identified from color air photos. Independent variables were Landsat TM bands 1, 3, 5, 6, and 7 and slope, aspect, and elevation derived from a digital elevation model). The design and

outcomes from this pilot project are currently leading to greater advances in the use of dispersed plot data to develop databases and models of non-native species patterns for much larger areas such as the state of Colorado.

Keywords: multi-scale vegetation sampling, spatial modeling, non-native plant species, biodiversity, Rocky Mountain National Park, Colorado

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Controlling of a biodiversity conservation program by a wide process monitoring approach

Thomas Dalang

WSL Swiss Federal Research Institute, Zurcherstrasse 111, CH-8903 Birmensdorf, Switzerland.

Thomas.dalang@wsl.ch

The subject of my talk is the planning of a long-time monitoring framework for a big-size nature conservation inventory in Switzerland. The project includes around 25'000 ha of dry grassland sites (DGS) in agricultural landscapes. The first of three parts of the DGS inventory will be enforced by law in 2004. The inventorisation process will be in progress until 2008.

A monitoring framework has to find a strategy to overcome three characteristic problems:

- The monitoring results should be usable for the improvement of the conservation methods. For this purpose, additional, not easily available data about the political and administrative environment of the project is needed.

- The upscaling from a small-size controlling system to a large-size system implies the shift from a complete census to a sampling survey. From the viewpoint of controlling, the most important fact is, that it is no longer possible to focus and make statements about each individual site.

- The consequence of the two mentioned problems is an economic problem: the absolute cost is high because reproducible biodiversity assessment methods are expensive and the additional data needed for the diagnosis are manifold.

The main line of the approach developed by a small group of experts is to base monitoring not on a static, strong deterministic causal model but on a more flexible system description. In this model the administration processes and the farmers are more important than exhaustive monitoring programs for the vegetation. Such control models have properties which are a challenge for the decision makers.

An important task of such a control system is to permanently improve and adapt the under- standing of the fuzzy causal model. Thus, critical aspects of the inventory process should be analyzed. The most important task is to identify those processes which change the quality of the conservation sites rapidly and irreversibly.

The biodiversity quality of dry grassland sites existentially depends on agricultural cultivation. So the agricultural land use is the most critical process of this conservation program. The management depends on economic factors, which are controlled by the agricultural and biodiversity policy and by the market. Psychological factors play an important role as well. So the main subject of monitoring is the socioeconomic situation of the farmers and the policies concerning them. On the research side the main questions are: How can the socioeconomic situation of the farmers be developed in a sustainable way? And how do the agricultural cultivation methods influence biodiversity?

Keywords: monitoring framework, biodiversity conservation, dry grassland, mesobrometum, planning, fuzzy system, agricultural cultivation

International Symposium, March 24--26, 2003. Birmensdori, Swiss Federal Research Institute WSL.

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Swiss Mire Monitoring: High resolution digital surface models (DSM) completing common spectral classification of color infrared images for statistical sampling

Klaus Ecker

klaus.ecker@wsl.ch

Remote sensing has long been used as a tool for environmental monitoring. Developments in digital photogrammetry now open new possibilities. In the research outlined here digital surface models of diverse resolution and different data sources are computed for various analyses.

To reduce the amount of field work a stratification of mire vegetation is performed on the basis of spectral classification of color infrared images and surface structure data. Aspect-data are generated from the DSM 25 m of the Swiss Federal Office of Topography. In addition to this, high-resolution DSMs with grid spacings of 1 m and 0.5 m are computed from aerial images to obtain fine-coarse slope-data: A smoothed DSM is calculated for the orthorectification of CIR-images. Using adapted parameters, the DSM reveals details such as tree height and small bushes.

Analysing slope-data, the occurrence of single trees and forest in given polygons can be detected and computed in terms of shape, texture and cover proportions. The surface-derived features are integrated with spectral indices obtained from spectral classification to a linear model of the mire vegetation properties. The precise discrimination and differentiation of woody vegetation is expected to further improve its high quality results.

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Swiss Mire Monitoring: How to detect shifts in vegetation

Elizabeth Feldmeyer-Christe and Ulrich Graf

elizabeth.feldmeyer@wsl.ch, ulrich.graf@wsl.ch

The Swiss mires of national importance have been protected by law since the beginning of the nineties. According to federal decrees of protection, the areas to be protected are to be maintained in their present size and quality. In mire areas where disturbance has already occurred, regeneration operations should be implemented wherever feasible.

A programme to monitor the efficiency of the protection measures was initiated in 1996 at the WSL in partnership with the Swiss Agency for the Environment, Forests and Landscape. The programme is based on aerial photographs and vegetation records. Aerial infrared photographs are delineated under the stereoscope to produce individual surfaces that are uniform in structure, texture and color. After interpretation and photogrammetric processing a mapping basis results in the form of a copy of the aerial photograph with the delineation of the surfaces. For large mires the number of recorded surfaces will be reduced by using image processing and statistics. A complete inventory of surfaces is made for small mires. The field work consists of the full record of plant species (including mosses) using a logarithmic scale for the cover. Complementary features like proportion of open water, proportion of bare peat, total cover of Sphagna, litter, etc, are recorded.

On the basis of these raw data it is possible to answer a lot of questions about the state and the evolution of a mire. For example, we can discriminate the vegetation units, describe the habitat conditions by means of indicator values and create corresponding maps, compute new indicator values for specific questions, derive the dynamics of individual species, assess the diversity of the surfaces and types of mires. Additionally it is possible with the GIS to calculate surface balances as well as lengths of boundaries.

In this contribution we present our results from three reference mires for which we already have chronological data.

The Hagenmoos mire represents a case of a distinct and heavy human impact by building a dam for rewetting the site. The Gross Moos Schwandital mire represents a case of medium human impact with the abandonment of pasture and the Burgmoos mire represents the most frequent case of no clear human impact but with the usual influence of nearby agriculture. We show how our method allows to emphasize the changes at different levels of sensitivity.

Keywords: long-term monitoring, mires, aerial photographs, vegetation dynamic; indicator values

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Mapping precision of predictions based on multiple primary variables from joint co-simulation with LANDSAT TM image

George Gertner, Guangxing Wang, Shoufan Fang

Department of Natural Resources and Environmental Science, University of Illinois, Urbana, Illinois 61801, USA

In the management of natural resources, multiple variables correlated with each other usually need to be mapped jointly. However, joint mapping and spatial uncertainty analyses are very difficult mainly because of interactions among variables and imperfection of existing methods. There is abundant evidence that considering interactions among variables and spatial information from neighbors can result in improved maps. This paper presents a remote sensing-aided method for that purpose.

The method is based on the integration of joint sequential co-simulation with Landsat TM image for mapping and polynomial regression for spatial uncertainty analysis. This procedure utilizes information obtained from joint sequential simulation to establish the relationship between model uncertainty and variation of model inputs. Using this procedure, model variance can be spatially partitioned by model input parameters on a pixel by pixel basis. In the partitioning, the correlation of neighboring pixels is accounted for. The method was applied to a case study in which ground cover, canopy cover, and vegetation height were jointly mapped to derive a map of the vegetation cover factor for predicting soil loss. The variance contributions from the variables, their interactions, and the spatial information from neighbors leading to uncertainty of predicted vegetation cover factor were assessed. The results showed that in addition to unbiased maps, this method repro- duced the spatial variability of the variables and the spatial correlation among them, and successfully quantified the effect of variation from all the components on the prediction of the vegetation cover factor.

Keywords: accuracy assessment, error budgets, remotely sensed data, spatial simulation, vegetation cover mapping

International Symposium, March 24-26, 2003. Birrnensdorf, Swiss Federal Research Institute WSL.

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Development of protected and utilized forest-savanna mosaics in Ivory Coast since 1954: a monitoring project in the BIOTAAfrica program

Dethardt Goetze ¹, Bianca Horsch²and Stefan Porembski¹

1 Institute of Biodiversity Research, Department of Botany, Wismarsche Strasse 8, D-18051 Restock, Germany. dethardt.goetze@biologie.uni-rostock.de

2 German Aerospace Center, Linder Hohe, D-51147 Kain, Germany.bianca.hoersch@dlr.de

The West African transition zone between Congolian rain forest in the south and Sudanian woodland towards the north is characterized by a vegetation mosaic consisting of forest islands and savanna. Anthropogenic habitat fragmentation leads to a decline of natural forests, their increasing isolation, a growing influence of edge effects from the surrounding savanna, and an alteration in species composition. As a result, biodiversity, as the most important natural resource and basic foundation for the livelihood of the inhabitants, is declining. In a period of intensification of land use and climate change in West Africa, the consequences of habitat fragmentation on biodiversity are being studied with a focus on spatio-temporal dynamics of landscape diversity.

For this purpose, the Comae National Park region (NE Ivory Coast) was chosen as study area because it comprises numerous forest islands of different types and geometries in comparatively homogenous savanna. The forests vary in size between square meters (on ancient termitaries) to more than one square kilometer. For at least 75 years the only direct human impact have been annual savanna fires and poaching of savanna animals. This forest island mosaic can, thus, be considered as a comparatively primary system that originally was characteristic for many peripheral areas of the humid tropics in the world. In the utilized region directly neighboring the southern park border this landscape mosaic continues, but with traditional agriculture and small plantations penetrating many forests.

The development of landscape structure and diversity from 1954 to today is being directly compared between the utilized and the protected area by means of remote sensing data: In order to monitor the long-term changes at different spatial scales, a multi-resolution approach was chosen. For large-scale change analysis high-resolution b/w aerial photos and CORONA (1954,

1967, 1972, 1996) were employed.

By combining traditional supervised classification algorithms by thresholding with image segmentation and pattern recognition tools, the delineation and mapping of highly fragmented forest patches and their changes down to a size of several meters is achieved.

Transferring the results of these analyses to coarser resolution and multispectral LANDSAT and SPOT data reveals different types and intensities of forest dynamics in different parts of the study area. It also enables us to transfer the gained knowledge about large-scale landscape dynamics to a much larger area, especially by applying panchromatic satellite images and integrating their features, i.e. panchromatic spectral range and the high spatial resolution of 1 Sm. This allows for a more comprehensive reconstruction of dynamics of the entire vegetation cover and land surface.

Furthermore, continued satellite availability will allow for detailed monitoring during the next years.

The investigations are part of the interdisciplinary BIOTA Africa research network, funded by the German Federal Ministry of Education and Research, BMBF. It focuses on i) monitoring biodiversity changes and detecting their specific causes, and ii) developing a sustainable management of biodiversity in Africa.

Keywords: habitat fragmentation, forest island, global change, biodiversity, landscape diversity, landscape dynamics, rain forest, Comae, remote sensing

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Multi-scale vegetation monitoring for conservation practice on military ranges in the Netherlands

Rense Haveman and Raymond van der Wijngaart

Ministry of Defence, P.O. Box 30, 6700 AA Wageningen, The Netherlands.r.haveman@eclnv.agro.nl,

van.der.wijngaart@eclnv.agro.nl

Permanent plots (pq's) are widely used for the monitoring of vegetation. However, the use of pq's has two big disadvantages when used for conservation practice: it measures only relatively small- scale 'at the spot' vegetation processes. The measurement of the overall quality of large areas is only possible with an extensive network of pq's, and therefore time consuming and expensive. The second disadvantage of permanent plots is the inflexibility, due to the fixed position of pq's and the limited scale of measurement.

Therefore, pq's are not the most adequate method for the monitoring of the effects of use and management for the sake of nature conservation. Qualitative and quantitative changes of the vegetation on military ranges in the Netherlands are measured by using a set of monitoring methods, which integrates different organisation levels (from species to landscape). This set of methods comprises:

- qualitative species-lists;

population structure of important species;

semi-quantitative species-lists per ecotope;

before-after comparison of vegetation types;

permanent plots;

permanent plots of vegetation complexes;

vegetation maps.

For every individual area, a number of methods are selected which effectively monitor the most important values of the area. For example, the monitoring of a large heathland area on the northern 'Veluwe' called 'Oldebroekse Heide' (4,500 hectares), which was mapped in 1999, consists of three of the above mentioned methods. First, a before-after comparison of the floristic composition of vegetation types will be made. This method consists of a analysis of a sequence of vegetation tables of one vegetation type, to examine possible floristic changes over a longer time. Secondly, permanent plots of vegetation complexes will be used for the monitoring of small-scale shifts in vegetation type inventory. Due to the scale of the former vegetation mapping (1 :10,000), small- scale shifts can not be shown in a sequence of vegetation maps. Therefore, permanent plots of vegetation complexes, in which the abundance of all vegetation types is estimated, are the obvious method to measure these changes. Moreover, these vegetation complexes will be correlated with population dynamics of the endangered grasshopper Gampsocleis glabra. A third method that will be used, is the survey of the population structure of Gentiana pneumonanthe, one of the keystone species of the area. Changes in population structure can indicate the necessity of management intervention.

Keywords: vegetation monitoring, conservation, multi-scale approach, military ranges, species list, population structure, permanent plot, vegetation complex, vegetation map

References:

Haveman, R & Hornman, M. (2002). Meten op maat. Methode monitoring van natuurwaarden op defensieterreinen. Internal report Ministry of Defence, DGW& T, Wageningen.

International Symposium, March 24-26, 2003. Binnensdorf, Swiss Federal Research Institute WSL.

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BIOTA: Strategies for short- and long-term Monitoring of Vegetation Dynamics and Human Impact for Biodiversity Research in Africa

Bianca Horsch

Deutsches Zentrum fur Luft- und Raumfahrt DLR; Deutsches Fernerkundungsdatenzentrum DFD-UG, Linder Hohe, D-51147 Koln, Deutschland.bianca.hoersch@dlr.de

Biodiversity is one of the most important resources for mankind on earth. It is the essential basis for the functioning of natural ecosystems and of great relevance and potential not only for the livelihood of the people but also for various technical and agricultural aspects of economy (Linsenmair, 2001 ). Today however biodiversity is dramatically diminished by profound anthropogenic modifi- cations of the environment. This entails a direct loss of specific ecological and economical poten- tials which might lead to a progressive loss of biodiversity itself. There is an increasing need to develop adequate protection and management schemes, where vegetation monitoring will play a key role (Jurgens, 2001 ).

BIOTA AFRICA aims to create a significant contribution to the UNCBD. The project comprises 35 interdisciplinary sub-projects, which - in close co-operation with African research institutions - aim at monitoring the changes of biodiversity along the most important biomes of Africa. The overall goal of the project is to achieve knowledge for a sustainable management of biodiversity, taking into account the ecosystem and the socio-economic framework.

The remote sensing based monitoring of biodiversity is aiming at assessing the spatial and temporal patterns and dynamics of vegetation along a 2000km transect from the Angolan-Namibian border to the Cape Peninsula.

Recent monitoring design and sample strategies have been set up to compare sites with different land use intensities, thus influencing biodiversity in a different way. The transect idea is following a multi-scale hierarchical approach: within each biome along the major climatic gradients each of the 20 research sites is made up by two 'biodiversity observatories' of standardised size.

They are covered with remote sensing data using either very high resolution satellite data or aerial photos. On these sites habitat types and vegetation types are delineated on the basis of botanical relevee data. The stratification results are used by the other project partners for designing their sampling strategy, e.g. by pedologists for soil profile or by zoologists for trap design planning.

On a larger scale entire farming systems, which are analysed towards socio-economic relevance, are being covered by high resolution multi-temporal satellite imagery (e.g. LANDSAT). Short and long-term fluctuations in vegetation type and characteristics are being monitored on selected farms.

Coherences between farm practices and vegetation characteristics are investigated in order to find out about thresholds of land use intensities and possible future changes under human impact scenarios. For the large-scale approach a coverage of the whole transect with long-term moderate resolution remote sensing data (e.g. NOAA, MODIS) is compiled in order to evaluate changes within the system between vegetation, climate and land use.

Keywords: vegetation dynamics, monitoring, biodiversity, sampling strategies, southern Atria References:

Jurgens, N. (2001 ): Biodiversity, the living resource: Challenges and research strategies. Contributions to global change research. Report published by The German National Committee on Global Change Research, Bonn, pp. 122-130.

Linsenmair, K.-E. und C.A. Bruh! (2001 ): Luxury or necessity: On some aspects of the functional significance of biodiversity. Contributions to global change research. Report published by The German National Committee on Global Change Research, Bonn, pp. 67-79.

International Symposium, March 24-26, 2003. Birmensdori, Swiss Federal Research Institute WSL.

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Object-Oriented Vegetation Monitoring: Correlation of Remote Sensing with Field Samples of Plants

Eva lvits ¹, Barbara Koch ¹and Lars Waser2

' Freiburg University, Dep. of Remote Sensing and US, Tennenbacherstr. 4, D-70106, Freiburg, Germany.

eva. ivits@felis.uni-freiburg.de, barbara. koch@felis.uni-freiburg.de

2 WSL Swiss Federal Research Institute, Zurcherstrasse 111, CH-8903 Birmensdorf, Switzerland.

lars.waser@wsl.ch,

Up to date several studies have indicated (but mostly assumed), that species react on landscape properties such as connectivity or fragmentation. In fact, landscape fragmentation has been identified as one of the most sever cause of biodiversity loss. However, up to now most studies failed to support and validate results of landscape ecological analysis with biological field data. This paper attempts to overcome this lack of information by correlating several RS data (and its deriva- tives) with field samples of plant biodiversity.

The study is focussed on six test sites in Switzerland representing different degrees of land use gradient - from forest to intensively managed agricultural areas. Plants sampling data of the six test sites are correlated a) with landscape indices, and b) with other RS-indices derived from Landsat ETM, SPOT, IRS, and Quickbird satellite data. For landscape ecological analysis of habitats, land use types, or forest stands, well-defined objects and object edges are needed. These parameters serve as input for the calculation of landscape indices that describe phenomena e.g. like fragmentation. On the other hand the four RS sensors provide a spatial gradient of perception for vegetation and landscape monitoring that ranges from low to very high resolution. High resolution RS data, specially the very high-resolution Quickbird satellite (2.Bm multispectral and 0.7m pan, respectively), offer strongly varying spatial information. Although they enable differentiation of many landscape objects - which are the working units of landscape ecology- their processing has become more and more difficult and therefore requires new techniques.

Both visual-, and automatic image processing techniques are evaluated for their contribution of operational vegetation monitoring. Hierarchical image segmentation, based on semantic networks, and visual image interpretation have been implemented and compared based on the above mentioned sensor types. Segmentation enables the user to process high and very high resolution RS data in a way that produces optimal input for further landscape ecological analysis. The hierarchy of the image segmentation enables the assessment of habitats on different scales with clear object edges that can be defined according to the user's needs. Additionally, automatic methods have the advantage of standardisation when compared to visual interpretation. Objects that appear too small for a human eye cannot be detected with visual methods - while automatic approaches enable a much easier and repeatable interpretation of these objects

Landscape indices have on one hand been used to describe diversity of the different habitats and on the other hand correlated with species diversity of plant field data. On the other hand, RS- derived indicators (e.g. NOVI or texture images) have also been correlated with the species data.

For the correlation of the spatial and biological data several multivariable methods, e.g. canonical correspondence analysis, have been tested. This study was completed in the framework of the European Union Project BioAssessto prove that RS and its derived indicators serve as promising tool in the assessment of species diversity on the landscape scale.

Keywords: object-based assessment, landscape index, biodiversity, multivariate date analysis

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The use of sequential vegetation maps for monitoring

John A.M. Janssen

Alterra, P.O. Box 47, 6700 AA Wageningen, The Netherlands.j.a.m.janssen@alterra.wag-ur.nl

For nature management, vegetation maps are an important source of information. They provide a synoptic view of the area and vegetation is a good indicator for other aspects of the landscape.

Vegetation maps are used for inventories, monitoring and evaluation of the effects of natural processes and human activities upon vegetation.

By comparing sequential maps and analyse changes, vegetation maps can be used for monitoring. One of the main problems in this application is that the maps contain uncertainties, which affect the reliability of the change analysis. A comparison of two maps of an area during different years shows both real vegetation changes and changes caused by methodological differences and uncertainties in the compared maps. It is important to distinguish between these two sources of 'change' in order to provide users with reliable information.

The paper discusses how operational methods for vegetation mapping can be used for monitoring in order to provide nature managers with relevant and reliable information on an ecological management problem. In a coastal salt-marsh area in the Netherlands it was studied which uncertainties arise in vegetation mapping (based on interpretation of aerial photographs) and change analysis. An overview of the main uncertainties in vegetation mapping and their consequences for change analysis is given. Uncertainties in the boundaries of map units (chorological uncertainties) are discussed in detail. It is shown how the chorological uncertainties may be reduced significantly by using the 'Previous Boundary Method'.

Keywords: vegetation, mapping, monitoring, photo-interpretation, change analysis, uncertainty References:

Janssen, J.A.M. (2001 ). Monitoring of salt-marsh vegetation by sequential mapping. PhD Thesis, University of Amsterdam.

International Symposium, March 24-26, 2003. Bimiensdorf, Swiss Federal Research Institute WSL.

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Sampling methods in the Swiss NFI

Edgar Kaufmann

edgar.kaufmann@wsl.ch

The Swiss National Forest Inventory (NFI) is gathering information that is relevant for the analysis of the state of the Swiss forests and of changes in the forests on systematic sample grids covering the whole country. In the paper, both the sampling methods applied in the NFI and some sampling alternatives are explained and discussed. Alternate sampling methods are demonstrated by means of case studies that have been performed in the NFI context.

The estimation of standing volume, cut and growth is one of the most important goals in the NFI.

Consequently, the sample system has been optimized for the assessment of these characteristics.

The main principles of the approaches that were considered when developing the system and main results of the methodical studies are explained. This comprises simple random sampling and double sampling for stratification or double sampling with regression analysis. As the plot structure and the selection probabilities of sample trees play an important role, it is shown how sample trees are selected.

The method of the regeneration survey applied in the NFI is the second example that is demonstrated. Regeneration has an enormous spatial variability even on a small scale. Recording seed- lings and saplings is time consuming, but the time is limited. Problems that arise with the regeneration assessment are suitable to discuss some methodical aspects such as the advantages of cluster sampling or sampling with unequal probabilities. Until now, the sampling system has not been satisfying. Further investigations are therefore ongoing.

The main purpose of the paper is on one hand to give an overview of important statistical

methods with which one has to deal in the framework of a NFI, on the other hand to show how these methods are applied in the Swiss NFI and to depict valuable alternatives.

Keywords: National Forest Inventory, sampling design

24 In: Feldrneyer-Christe, E. (ed) 2003: State of the Art in Vegetation Monitoring Approaches. Abstracts.

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A cell-grid method for short-term and fine-scale monitoring of vegetation dynamics in pastures

Florian Kohler¹•2

, Marie-Aude Progin², Jean-Michel Gobat², Alexandre Buttler¹•3 and Fran9ois Gillet¹•2 1 WSL Swiss Federal Research Institute, Antenne romande, 1015 Lausanne, Switzerland

2 Laboratoire d'ecologie vegetale et de phytosociologie, lnstitut de Botanique, Universite de Neuchatel, Rue Emile-Argand 11, CH-2007 Neuchatel, Switzerland. florian.kohler@unine.ch

3 Laboratoire de Chrono-ecologie, UMR CNRS 6565, UFA Sciences et Techniques, Universite de Franche- Comte, 25030 Besanc;:on, France

In sylvopastoral ecosystems, the herb layer is strongly dependent on cattle activity. Dunging, grazing, trampling and gaps induce short-term vegetation dynamics at fine scale. To survey seasonal change in herbaceous communities and gap colonization in wooded pastures, a cell-grid method was chosen. A grid of 1 m²subdivided into 100 cells of 1 dm²was used as a permanent plot. In each cell of each plot and at each season (twice or five times a year), we estimated dominance, height and a grazing index of each species.

This heavy method {5-8 hours for one releve) permitted to detect phenomena, in particular spatial patterns, which were not perceptible with other classical methods, such as point-intercept or Braun-Blanquet releves. At community level, seasonal changes in vegetation texture and structure at different scales (1 dm²to 1 m²) can be described by similarity indices. At population level, the spatial distribution of each species can be surveyed through time, in particular after natural or artificial gap creation.

As an example, stability of permanents plots in four different plant communities representative of typical vegetation of wooded pasture (grazed meadow, lawn, fallow, and underwood) are presented. Results of this observational study showed that at cell scale there was a high turn-over in species composition, not detected at plot scale. Species used different strategies, depending on context (cattle activities, community type), responsible for fluctuations in vegetation texture and structure. Seasonal selectivity patterns were described by comparing grazing effects in the different communities through time.

For gap colonization, examples of results obtained from observational and experimental studies are presented. The experiment was conducted in a fenced area simulating cattle activities by repeated mowing, fertilizing and trampling. Plots were artificially disturbed by creating gaps of different sizes. 8 plots were surveyed twice a year during two years. Gap colonization was recog- nized to have a strong effect on vegetation texture, favoring essentially clonal reproduction.

Keywords: scale, seasonal change, spatial monitoring, vegetation dynamics

International Symposium, March 24--26, 2003. Bimiensdorf, Swiss Federal Research Institute WSL.

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Swiss Mire Monitoring: Improved modelling of vegetation properties from aerial photographs and field data

Meinrad Kuchler

mein rad.kuechler@wsl.ch

According to federal decrees of protection, the Swiss mires of national importance are to be maintaned in their present size and quality. Mires already suffering from disturbance have to be regenerated whenever feasible.

To control the efficiency of protection, a monitoring program was initiated in 1996 at the WSL in partnership with the Swiss Agency for the Environment, Forest and Landscape. The vegetation was chosen as the main criterion because many different interpretations can be derived from. To describe the Swiss mires, a pair of infrared aerial photographs and a sample of field data is taken from 103 mire objects. After 5 years the same 103 mires will be visited again to detect changes if present.

The treatment of the aerial pictures and of the field data are the subjects of other contributions to the symposium (KE and FE+ UG respectively). The present lecture deals with modelling of vegetational information by means of the information derived from the aerial photographs.

Vegetational information is treated as response variables. They include cardinal, ordinal and categorial data like habitat indicator values, counts or cover proportions of plants, vegetation units, etc.

The data derived from aerial pictures (used as predicor variables) include cardinal, ordinal and categorial data as well: color and structure parameters, slope and exposition.

In a first stage, when our research activities focused on the treatment of the aerial pictures and the vegetation data, we fitted linear and logistic models. Just for describing the mire objects, the results were quite satisfactory. But for detecting changes, the method had to be improved. The problems to resolve were the following:

- inaccurate values in the response variables (it's an usual situation with vegetation data);

- contaminated data (e.g. shadows of trees) in the predictor variables;

- many zero values in the predictor variables;

- inhomogeneous data types;

- outliers.

We present the effects of data transformation, robust, nonlinear and multivariate models on the correlation between fitted and observed values. The data we use are from three mires of which we already have chronological data.

Keywords: mire monitoring, Switzerland, aerial photographs, vegetation dynamics, indicator values, vegetation units, linear models, nonlinear models, generalized linear models, robust statistics, multivariate statistics

26 In: Feldmeyer-Christe, E. (ed) 2003: State of the Art in Vegetation Monitoring Approaches. Abstracts.