Methodical basis for landscape structure analysis and monitoring: inclusion of ecotones and small landscape elements

Volume 12 of the series "Remote Sensing and Applied Geoinformatics"

Wei Hou
ISBN: 978-3-944101-21-7
Veröffentlicht: Juni 2017, 1. Auflage, Einband: Broschur, Abbildung und Tabellen: numerous illustrations, many of them colored, Seiten 134, Format DIN B5, Gewicht 0.3 kg
Lieferzeit: 2-3 Tage
Verfügbarkeit: Auf Lager
32,80 €

Methodical basis for landscape structure analysis and monitoring: inclusion of ecotones and small landscape elements

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Wei Hou

Methodical basis for landscape structure analysis and monitoring: inclusion of ecotones and small landscape elements

 

Volume 12 of the series "Remote Sensing and Applied Geoinformatics"

Edited by Univ. Prof. Dr. habil. Elmar Csaplovics, Chair of Remote Sensing, FR Geosciences, TU Dresden

134 pages, DIN B5 format, numerous illustrations, many of them colored. Language: English. Price: 32.80 Euro. ISBN 978-3-944101-21-7. Publisher: Rhombos Verlag, Berlin 2017

Also: A thesis submitted in partial fulfilment of the requirements of the Faculty of Forest, Geo and Hydro Sciences of  Technische Universität Dresden  for the degree of Doctor of Natural Sciences (Dr.rer.nat.) in 2014

About this book

Effective methods for measuring habitat pattern at landscape level are crucial for understanding the ecological processes. The widely used patch-corridor-matrix model in landscape structure analysis may be oversimplified by losing valuable information, such as the terrain characteristics of landscape, ecotones, and small biotopes. The present work originates from the integration of the third spatial dimension in land-cover classification and landscape structure analysis. The focus is on the extraction of ecotones and small landscape elements based on high-resolution images and DEMs, and the integration of these elements in 3D landscape metrics. This work is meant to supply a possible way to enhance the model of landscape structure analysis. It may be interested to both scientists and practitioners in this field.

The Author

Wei Hou (born in 1984) studied Geo-information Science at the China University of Mining and Technology from 2002 to 2009. He has been working as a guest researcher at the Leibniz Institute of Ecological Urban and Regional development in the field of landscape ecology and GIS from 2009 to 2014. Since 2015, he works at the Chinese Academy of Surveying and Mapping (CASM) as research associate. This book was part of his PhD degree of Geoinformatics from the Dresden University of Technology in 2014.

Contact:

Dr.rer.nat. Wei Hou
Chinese Academy of Surveying and Mapping Lianhuachi West Road 28, Haidian District, 100830 Beijing
Email: houwei@casm.ac.cn


Academic Supervisors

Prof. Dr.habil. Elmar Csaplovics
Institute of Photogrammetry and Remote Sensing, TU Dresden

PD Dr.habil. Ulrich Walz
Leibniz Institute of Ecological Urban and Regional Development, Dresden

Prof. Dr. Xianfeng Song
University of Chinese Academy of Sciences, Beijing

The Editor

Prof. Dr. techn. habil. Elmar Csaplovics, Chair of Remote Sensing at the Institute of Photogrammetry and Remote Sensing at the Technische Universität Dresden.

Contact:

Department of Geosciences, Institute of Photogrammetry and Remote Sensing, Research Group Remote Sensing, Technische Universität Dresden, Helmholtzstraße 10, D-01062 Dresden

Tel. +49 351 463-33372, Fax +49 351 463-37266

Homepage: https://tu-dresden.de/bu/umwelt/geo/ipf/fern

Editorial

When the term landscape emerged in the 16th century it was coined by the perception of nature in its holistic appearance, i.e. of the wholeness of the visible nature more or less shaped by a location- and time-dependent mixture of anthropozoogenic impact. The “scenery” comprising all the visible elements of a landscape was understood as an aesthetic impression of ostensibly harmonious patterns of a composition of organic and anorganic objects. Accordingly, it was through the fine arts, that by the painting of landscapes the term per se was invented during the late Renaissance (Gombrich 1966). Only during the late 18th and early 19th century the term was scientified by natural scientists such as Alexander von Humboldt, who nevertheless still relied to the (aesthetic) holistic concept of landscape, but at the same time tried to set up a categorisation of the types of elements which “construct” it (Humboldt 1849). Efforts were made to define landscape as a quantifiable multi-layer and multi-scale structure which is solely characterised by specific landscape elements which form ecotopes (“landscape cells”). The mosaic-like concinnity of ecotopes creates the landscape which is experienced as a consistent entity (Troll 1939).

Modern landscape ecology understands landscape as a heterogeneous area, which is coined by an aggregate of land forms or an association of habitats and which may comprise an area from some hectares up to hundreds of square kilometres (Turner et Gardner 1991). Three characteristics describing the typology of landscape are generally stressed, explicitly structure, function and change. Structure refers to relations of ecosystems in terms of shape, extent, abundance and configuration of components. Function relies to interactions of elements in space and time, i.e. flows of energy, material or organisms. Change describes the dynamics of structures and functions in a spatio-temporal context (Forman et Godron 1986).

Referring to structural characteristics it is obvious that the well-introduced patch-corridor-matrix-model is of limited reliability when extending the approach towards relief information, i.e. the third dimension in terrain description (digital surface/terrain models) as well as when integrating transition zones or gradients between patches. These ecotones have a significant temporal dimension in terms of dynamics of change and have thus a strong influence on parameters describing interrelated ecosystems. Improved approaches to a three-dimensional assessment and analysis of ecological gradients have to take into account that transition between ecological, geographical and environmental entities is generally non-discrete, often fuzzy. This aspect does not only concern relations between landscape elements and land use and land cover categories (describable by fuzzy logics) but also variations of approaches of analysis at multi-scale levels up to the dispersion of populations in respective areas of distribution. An ecological gradient can be described statistically by the fact that the variance of the relevant parameter increases with growing distance from the reference area (landscape element, habitat). It has nonetheless to be asked what would happen if that proportion were affected by diffuse impacts, which cannot be expressed by discontinuities in relief (e.g. in terms of canopy surface gradients from forest edges to adjacent copses and to grassland or agricultural land), such as environmental (human) impact varying locally both in time as well as in space, e.g. imission via air pollution or disturbances by tourism. Advanced technologies of 3D-topographic data acquisition such as Airborne Laser Scanning (ALS) as well as object-oriented approaches of remotely sensed image analysis (OBIA) allow for detection and mapping at very high geometric (spatial) accuracies. Thus, both relief gradients related to ecotones and also to small landscape elements (biotopes inside habitats) can be described in much more detailedness (e.g. Stumberg et al. 2014). It is worthwhile to take advantage of these data qualities and to focus on research into the integration of 3D-structural characteristics of ecotones via enhancing indices such as landscape diversity, fragmentation/connectivity and contrast.

One of the core problems in quantitative landscape ecology refers to the question to what extent landscape metrics are capable to assess information which supports the description of species richness (biodiversity?). Obviously, the integration of fine-scale landscape elements (small biotopes) and of ecotones into enhanced landscape metrics paves a way towards a better understanding and a more reliable interpretability and assessability of diversity, connectivity and contrast in landscapes. Gradient analysis along vegetation boundaries (edges) carries a load of further potential of information which needs to be integrated with more sophisticated landscape models to be developed. The extended potential of integration of any kind of gradient-type spatio-temporal information of environmental variables such as temperature, humidity and similar can be investigated.

Wei Hou has provided a very important contribution to pushing forward efforts of enhancing the real-world validity of landscape metrics by considering multi-scale characteristics of extent and distribution as well as of (canopy surface) gradients of small biotopes and (small) ecotones - smallness being a variable strongly depending on the scale of observation - based on the capability of spatial data to extract fine-scale elements of the landscape.

Elmar Csaplovics

References not appearing in the thesis

Gombrich EH (1966) The Renaissance theory of art and the rise of landscape, in: Gombrich EH (ed) Norm and form - studies in the art of the Renaissance, Phaidon, London, pp 107-121

Humboldt A v (1849) Ansichten der Natur mit wissenschaftlichen Erläuterungen, dritte verbesserte und vermehrte Auflage, 2 Bde. Cotta, Stuttgart Tübingen

Stumberg N, Hauglin M, Bollandsås OM, Gobakken T, Næsset E (2014) Improving classification of airborne laser scanning echoes in the forest-tundra ecotone using geostatistical and statistical measures. Remote Sensing 6(5): 4582-4599

Turner M, Gardner RH (1991) Quantitative methods in landscape ecology - an introduction, in: Turner MG, Gardner RH (eds) Quantitative methods in landscape ecology, Springer, New York Berlin

 

References appearing in the thesis

Forman RT, Godron M (1986) Landscape ecology. Wiley, New York

Troll C (1939) Luftbildplan und ökologische Bodenforschung, in: Zeitschrift der Gesellschaft für Erdkunde, Berlin 1939, Heft 7/8: 241-298

 

Foreword

The now printed thesis of Mr. Wei Hou, which originated in the period of his stay at the Leibniz Institute of Ecological and Regional Development, deals with advanced methods of landscape structure analysis and remote sensing for landscape monitoring. Background is a widespread approach in landscape ecology, according to which the landscape structure or, in other words, the "pattern" or "mosaic" of a landscape arises from the composition and arrangement of discrete patches, e.g. Individual land use units.

These spatial patterns can be quantified using "landscape metrics". The goal is to capture the structure of a landscape, to document it for the purpose of monitoring, or to provide it as input parameters for landscape ecological simulation models. Up to now, however, landscape metrics have mostly deviated from concrete landscape elements. Ecologically important transitional areas between such elements, e.g. height differences, have so far been not or hardly included. In addition, small-scale elements such as individual trees, shrubs, hedges, etc. are also important for a landscape monitoring, but these often do not show up in existing data. The work begins on these two points. The objectives of the work were:

* Development of a model and corresponding methods for the detection of small

landscape elements or biotopes as well as transitional areas between different land uses (ecotones) from remote sensing data and a high-resolution digital surface model.

* Integration of the small-scale landscape elements and ecotones into the methods of landscape structure analysis by adapting or extending existing methods and indices of landscape structure analysis.

For his work, he used data from the satellite “RapidEye” and high-resolution elevation

data from airborne laser scanning. He subsequently developed a multi-level approach in which small-scale landscape elements can be detected using common image processing and GIS software. Furthermore, transitional areas between different land use classes, here mainly between forest and open land, can be characterized. Afterwards, methods for analyzing the landscape structure are presented on this basis. Specially developed indices allow the analysis of landscape diversity, fragmentation, landscape contrasts and biotope networks. Both for complex methods for the detection of small- scale elements and ecotones, as well as for the methods of landscape structure analysis, own algorithms and indices were developed. The developed methods were tested in study areas in Germany and China and their behavior in different landscapes and with different data bases were examined.

Mr. Hou has made a significant contribution to the progress of this research area - even in the international context - with the doctoral thesis he has presented. The innovative approaches, which he developed and exemplarily prepared, testify to this. Beyond that, the work also shows the necessity and also possibilities for application in landscape monitoring. We are confident, that the methods developed by him will find interest and application in science and practice.

 

Ulrich Walz

 

Contents

1             Introduction      1

1.1          Starting point of this work: biodiversity on landscape level         1

1.2          Modern landscape ecology and its shortcomings            2

1.3          Research objectives and key questions               3

1.3.1      Research objectives      3

1.3.2      Key questions   4

2             Theoretical basis and background           5

2.1          Small biotopes and ecotones as components of landscape pattern        5

2.1.1      Landscape fragmentation as a result of disappearing small biotopes     5

2.1.2      A “soft” boundary: ecotones as transitional area between habitats       6

2.1.2.1  The model of patch boundary   7

2.1.2.2  The ecotone concept    8

2.1.3      Ecological functions of small biotopes and ecotones      9

2.1.3.1  Ecological functions of small biotopes   9

2.1.3.2  Ecological functions of ecotones              11

2.2          Landscape monitoring in Germany and China    14

2.2.1      Landscape monitoring in Germany         14

2.2.1.1  Current situation of biological diversity in Germany       15

2.2.1.2  Data used for landscape monitoring      16

2.2.1.3  Landscape indicators for biodiversity conservation         17

2.2.2      Landscape monitoring in China 20

2.2.2.1  Current situation of biological diversity in China               20

2.2.2.2  Data used for landscape monitoring      20

2.2.2.3  Landscape indicators for biodiversity conservation         21

2.3          Summary            23

3             An enhanced approach for landscape structure analysis              25

3.1          Data basis           25

3.1.1      RapidEye images             25

3.1.2      High resolution elevation data  27

3.1.3      Other data         29

3.2          Mapping landscape pattern by integration of an object- and pixel-based classification approach            29

3.2.1      Object-based image analysis (OBIA): land-use classification based on multi-temporal RapidEye images              29

3.2.1.1  Spectral feature of RapidEye image       30

3.2.1.2  Class hierarchy 34

3.2.1.3  The concept of image segmentation     35

3.2.1.4  Segmentation and classification strategy             36

3.2.2      Pixel-based image analysis: detection of ecotones and small biotopes using high resolution NDSM data            37

3.2.2.1  Ecotone model and definition of small biotopes              38

3.2.2.2  Applied features and algorithms             39

3.2.2.3  Detailed landscape structure detection based on NDSM             41

3.3          Landscape structures analysis   43

3.3.1      Metrics for describing landscape structure         43

3.3.1.1  Landscape diversity       44

3.3.1.2  Landscape fragmentation           45

3.3.1.3  Landscape contrast        46

3.3.2      Habitat connectivity analysis considering small biotopes as stepping stones      48

3.3.2.1  Mapping ecological network      49

3.3.2.2  Indicators for assessing ecological networks      51

3.4          Summary            52

4             Examples of use and results: application of the proposed methodology in test sites of Germany and China      53

4.1          Study areas and data basis         53

4.2          Object-based image classification           55

4.2.1      Classification of main classes     55

4.2.1.1  Settlement and traffic extraction            55

4.2.1.2  Assessing scale parameter for segmentation    56

4.2.1.3  Classification process    58

4.2.2      Further classification of detailed land-cover classes       59

4.2.2.1  Detailed classification within settlements           59

4.2.2.2  Farmland plots delineation         60

4.2.2.3  Detailed classification within forests      61

4.2.3      Accuracy assessment    63

4.2.3.1  Classification accuracy in test site Rathen            63

4.2.3.2  Classification accuracy in test site Jiawang           65

4.3          Fine-scale landscape structure detection            66

4.3.1      Detection results            66

4.3.2      Accuracy assessment    68

4.4          Landscape structure analysis     69

4.4.1      Comparing “2D” and “3D” metrics in practice     70

4.4.1.1  Basic patch geometry    70

4.4.1.2  Diversity metrics             71

4.4.1.3  Effective mesh size (MESH)       71

4.4.2      Landscape contrast analysis       72

4.4.3      Ecological network analysis using small biotopes as stepping stones      75

4.4.3.1  Selection of buffer ranges          75

4.4.3.2  Mapping ecological networks    75

4.4.3.3  Analysis of connectivity for the test sites            77

4.5          Summary            78

5             Discussion and evaluation           79

5.1          Evaluation of the proposed methods for image processing        79

5.1.1      Applying Object-Based Image Analysis (OBIA) on RapidEye data             79

5.1.2      Applying pixel-based object detection on high resolution NDSM            82

5.2          Evaluation of the metrics for landscape structure analysis          85

5.2.1      The application of landscape diversity metrics  85

5.2.2      The application of the metrics for describing landscape fragmentation/connectivity     85

5.2.2.1  Unification of landscape fragmentation and connectivity            86

5.2.2.2  Functional roles of ecotones and small biotopes in econets       86

5.2.2.3  General applicability in econets analysis              87

5.2.3      The application of the metrics for describing landscape contrast             89

5.3          Possible fields of application      90

6             Conclusion and outlook               93

7             References        99

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