Landscape Analysis and Visualisation

by Pettit, Christopher; Cartwright, William; Bishop, Ian; Lowell, Kim; Pullar, David

• ISBN13: 9783540691679
• ISBN10: 3540691677
• eBook ISBN(s): 9783540691686
• Format: Hardcover
• Copyright: 2008-08-03
• Publisher: Springer Verlag
• More Book Details
• Purchase Benefits

Summary

This book showcases a wide range of innovative landscape analysis and visualization techniques as used in a number of applied natural resource management and central planning problems. It includes papers ranging from a number of areas including: (i) natural resource knowledge management, (ii) ecological modelling, (iii) landscape visualization, (iv) NRM policy and investment, (v) land use change and scenario modelling, (vi) farm to catchment tools, and (vii) social, economic, environmental indicators and landscapes. It aims to provide readers with a better understanding of available frameworks spatial models and tools currently applied when addressing critical land use issues such as urban sprawl, climate change, salinity, biodiverstiy, and changing landscapes, from both the socio-economic and the biophysical angle.

Table of Contents

Contributors	p. XXI
Abbreviations	p. XXXI
Introduction	p. 1
Understanding Landscapes through Knowledge Management Frameworks, Spatial Models, Decision Support Tools and Visualisation	p. 3
Introduction	p. 3
Part 1: Natural Resource Knowledge Management Frameworks and Tools	p. 5
Part 2: Integrating the Ecology of Landscapes into Landscape Analysis and Visualisation	p. 7
Part 3: Socioeconomic Dimensions to Landscapes	p. 9
Part 4: Land Use Change and Scenario Modelling	p. 11
Part 5: Landscape Visualisation	p. 13
Future Challenges	p. 15
Natural Resource Knowledge Management Frameworks and Tools	p. 17
Reading between the Lines: Knowledge for Natural Resource Management	p. 19
Introduction	p. 19
Knowledge Hierarchy	p. 20
Timelag between Question and Answer	p. 23
Organising the Questions	p. 24
Integrating Disciplines	p. 26
Conclusion	p. 27
Improving the Use of Science in Evidence-based Policy: Some Victorian Experiences in Natural Resource Management	p. 29
Context	p. 29
Historical Perspective	p. 30
The Policy Process: Towards Evidence-based Policy	p. 31
Use of Science as Evidence in Policy	p. 32
Some Victorian Experiences in Natural Resource Management	p. 35
Survey of Policy Analysts	p. 37
Market Research	p. 38
Improving the Utility of Project Outputs	p. 40
Observation of How Policy Decisions Are Made	p. 40
Case Studies of Successful Science-Policy Influence	p. 41
Sawlogs for Salinity	p. 42
Salinity Investment Framework 3	p. 42
Soil Health	p. 43
Greenhouse in Agriculture	p. 43
Discussion	p. 44
Toward Better Use of Science in Evidence-based Policy	p. 44
Conclusion	p. 46
The Catchment Analysis Tool: Demonstrating the Benefits of Interconnected Biophysical Models	p. 49
Introduction	p. 50
Catchment Analysis Tool: Background and Description	p. 51
The CAT Interface	p. 54
CAT Input Data	p. 56
The CAT Model Components	p. 59
Model Calibration and Conceptualisation	p. 61
Case Study	p. 61
Hypothetical Case Study	p. 61
Results and analysis	p. 66
Validation and Model Improvement	p. 68
Conclusion	p. 69
The Application of a Simple Spatial Multi-Criteria Analysis Shell to Natural Resource Management Decision Making	p. 73
Introduction	p. 74
Multi-criteria Analysis	p. 74
Spatial Applications	p. 75
The Decision-making Process	p. 77
The MCAS-S Approach	p. 79
Design Principles	p. 79
Key Functions	p. 80
Applications	p. 82
Prioritising Revegetation Investment	p. 82
Assessing the Sustainability of Extensive Grazing	p. 85
Future Trends	p. 89
Conclusion	p. 90
Future Research Directions	p. 91
Platform for Environmental Modelling Support: a Grid Cell Data Infrastructure for Modellers	p. 97
Introduction	p. 98
Background	p. 100
Methodology	p. 102
Progress and Discussions	p. 103
The PEMS Demonstrator Project	p. 105
National Seasonal Crop Monitoring and Forecasting105
Develop and Demonstrate a Market-based Approach to Environmental Policy on Private Land	p. 108
Wildfire Planning: Consequence of Loss Modelling	p. 109
Land Use Data, Modelling and Reporting	p. 111
Conclusion	p. 115
Integrating the Ecology of Landscapes into Landscape Analysis and Visualisation	p. 119
Looking at Landscapes for Biodiversity: Whose View Will Do?	p. 121
Introduction	p. 122
To be Human is to Err	p. 122
What's Good for the Goose?	p. 124
Consider the Lilies	p. 127
Best is Bunkum	p. 128
Varied Perspectives	p. 129
Mapping and Modelling Terrain, Hydrological, Pedological and Geological Features and Climate	p. 129
Vegetation Mapping Using Remotely Sensed Data, Including Vegetation Condition and Temporal Variability	p. 130
Mapping and Modelling Movement	p. 131
Integrating Multiple Perspectives	p. 133
Conclusion	p. 135
Native Vegetation Condition: Site to Regional Assessments	p. 139
Introduction	p. 140
Measuring Vegetation Condition at Sites	p. 141
Measuring Vegetation Condition across Regions	p. 142
Case Study: Vegetation Condition in the Murray Catchment, New South Wales	p. 143
Study Area	p. 143
Site Data Collection	p. 144
Modelling from the Site to the Region	p. 146
Results and Discussion for the Murray Catchment Case Study	p. 149
Conclusion	p. 152
Future Research Directions	p. 153
Towards Adaptive Management of Native Vegetation in Regional Landscapes	p. 159
Introduction	p. 159
What Adaptive Management is and is not	p. 161
Step i: Statement of Objectives, Constraints and Performance Measures	p. 163
Step ii: Specification of Management Options	p. 164
Step iii: System Modelling and Model Credibility	p. 165
Step iv: Allocation, implementation and Monitoring - Closing the Loop	p. 165
Managing and Monitoring Native Vegetation	p. 167
An Example of a Formal Approach to Adaptive Management of Vegetation Condition	p. 169
Research	p. 175
Conclusion	p. 176
Future Directions	p. 177
Appendix	p. 181
Revegetation and the Significance of Timelags in Provision of Habitat Resources for Birds	p. 183
Introduction	p. 184
Methodology	p. 186
Model Description	p. 186
Case Study	p. 191
Results	p. 192
Discussion	p. 197
Caveats and Extensions	p. 199
Appendices	p. 204
The Application of Genetic Markers to Landscape Management	p. 211
Introduction	p. 212
The Need for Information on How Biota Occupies and Moves through Landscapes	p. 212
A Spectrum of `Genetics' in Landscape Management and Planning	p. 213
Molecular Population Biology Supplies Information Essential for Landscape Planning and Management	p. 213
Background	p. 215
Three Levels of Analysis Assess Three Levels in Time and Space	p. 215
Main Molecular Tools in Landscape Molecular Population Biology	p. 217
Case Studies	p. 220
Impacts of Habitat Fragmentation on Cunningham's Skinks	p. 220
Dispersal and Gene Flow of Greater Gliders through Forest Fragmented by Pine Plantation	p. 221
Catchments Catch All: Congruent Patterns in Diverse Invertebrate Fauna in Decaying Wood at a Landscape Scale	p. 222
Future Trends	p. 223
Conclusion	p. 225
Future Research Directions	p. 225
Appendix	p. 231
Scenario Analysis with Performance Indicators: a Case Study for Forest Linkage Restoration	p. 235
Introduction	p. 236
Background	p. 237
Linkage restoration	p. 239
Indicator Rule 1: Site Recovery Capacity	p. 240
Indicator Rule 2: Site Biodiversity Value	p. 241
Indicator Rule 3: Landscape Linkage Qualities	p. 242
Indicator Rule 4: Landscape Connectivity	p. 242
Atherton Tablelands Case Study	p. 243
Restoration scenarios	p. 245
Scenario Evaluation	p. 246
Conclusion	p. 247
Socioeconomic Dimensions to Landscapes	p. 251
Strategic Spatial Governance: Deriving Social-Ecological Frameworks for Managing Landscapes and Regions	p. 253
Introduction	p. 254
A Potted History of Catchments for Resource Governance	p. 254
Defining Regions for Resource Governance	p. 256
Principle 1	p. 256
Principle 2	p. 257
Principle 3	p. 259
Application of Principles to Spatial Analysis	p. 259
Delineating Civic Regions from a Social Surface	p. 260
Deriving a Hierarchy of Civic Regions	p. 262
Deriving Ecoregions	p. 264
Integrating Ecoregions and Civic Regions through Boundary Optimisation	p. 265
Comparing the Performance of Regions	p. 266
Conclusion: Past, Present and Future Resource Governance	p. 269
Future Directions	p. 270
Placing People at the Centre of Landscape Assessment	p. 277
Introduction	p. 277
Background	p. 278
Methodology	p. 279
Pressure-State-Response Model	p. 279
Driving Forces-Pressure-State-Impact-Response Model	p. 281
Millennium Ecosystem Assessment Framework	p. 281
Indicator Selection	p. 282
A Landscape Approach for Victoria	p. 283
Definitions of Five Victoria Landscapes	p. 284
The Role of Indicators	p. 285
Case Study 1: Semi-arid Landscape	p. 285
Overview	p. 286
Employment Indicator	p. 288
Index of Stream Condition Indicator	p. 290
Land Use Diversity Indicator	p. 291
Management Response	p. 293
Case Study 2: Coastal Landscape	p. 293
Overview	p. 294
Visitors to Parks and Reserves Indicator	p. 295
Ratio of Land Value to Production Value Indicator	p. 296
Land Use Diversity Indicator	p. 297
Policy Response	p. 298
Overview of Results	p. 299
Conclusion	p. 299
Future Research Directions	p. 300
The Social Landscapes of Rural Victoria	p. 305
Introduction	p. 305
A Narrative of Rural Transformation in Australia	p. 306
International Agricultural Competition	p. 306
Agricultural Restructuring	p. 307
Amenity Values in the Rural Land Market	p. 307
Indicators Derived from the Narrative	p. 308
From Indicators to Social Landscapes	p. 310
Factor Analysis Using the Principal Components Method	p. 310
Creating a Geography of Amenity and Intensification	p. 314
Five Social Landscapes	p. 315
The Production Landscape	p. 316
The Transitional Landscape	p. 317
The Amenity Farming Landscape	p. 318
The High Amenity Landscape	p. 319
The Intensive Agriculture Landscape	p. 319
Conclusion	p. 322
Future Research Directions	p. 323
A Decision Aiding System for Predicting People's Scenario Preferences	p. 327
Introduction	p. 327
Background	p. 328
An Extra Step for the SDSS Discipline	p. 329
Description of the Preference Prediction Software	p. 331
Finding a Larger Set of Criteria	p. 331
Finding Relationships between Criterion Scores and Overall Scenario Merit	p. 331
The Underlying Assumption	p. 333
An Urban Planning Case Study Application of the Preference Prediction Software	p. 334
Assigning Criteria Scores to the Scenarios	p. 335
Predicting Scenario Ratings for Overall Merit	p. 336
Checking the Personal Characteristics of the Advisors	p. 338
Predicting Scenario Merit Ratings on Behalf of Past Workshops	p. 338
Exploring How Scenario Ratings Were Derived	p. 339
Searching for Reasons behind Each Scenario Merit Rating	p. 342
Predicting All Groups' Preferences Simultaneously	p. 345
Future Trends	p. 347
Conclusion	p. 347
Future Research Directions	p. 348
Land Use Change and Scenario Modelling	p. 351
Mapping and Modelling Land Use Change: an Application of the SLEUTH Model	p. 353
Introduction	p. 353
Methodology	p. 355
Results and Discussion	p. 358
Conclusion	p. 364
Uncertainty in Landscape Models: Sources, Impacts and Decision Making	p. 367
Introduction	p. 368
Models, Variability and Sources of Uncertainty	p. 369
Model Structure	p. 370
Natural Variability, Temporal Resolution and Spatial Resolution	p. 371
Taxonomic Scale and Data Collection	p. 375
Summary on Models and Sources of Uncertainty	p. 377
Model Uncertainty and Decision Making	p. 377
Conclusion	p. 381
Assessing Water Quality Impacts of Community Defined Land Use Change Scenarios for the Douglas Shire, Far North Queensland	p. 383
Context and Case Study Location	p. 384
Dialogue over Sustainable Future Landscapes and Seascapes	p. 386
Methodology of an Application of a Social-Ecological Framework for Sustainable Landscape Planning	p. 387
Stage I: Community Perceptions and Visions	p. 387
Stage II: Community-driven Landscape Scenarios	p. 389
Stage III: Modelling of Landscape Scenarios and Assessing Water Quality	p. 389
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