Integration of GIS and Remote Sensing

Dr. Victor Mesev. Chair, Department of Geography, Florida State University, USA

In an age of unprecedented proliferation of data from disparate sources the urgency is to create efficient methodologies that can optimise data combinations and at the same time solve increasingly complex application problems. Integration of GIS and Remote Sensing explores the tremendous potential that lies along the interface between GIS and remote sensing for activating interoperable databases and instigating information interchange. It concentrates on the rigorous and meticulous aspects of analytical data matching and thematic compatibility - the true roots of all branches of GIS/remote sensing applications. However closer harmonization is tempered by numerous technical and institutional issues, including scale incompatibility, measurement disparities, and the inescapable notion that data from GIS and remote sensing essentially represent diametrically opposing conceptual views of reality.
 
The first part of the book defines and characterises GIS and remote sensing and presents the reader with an awareness of the many scale, taxonomical and analytical problems when attempting integration. The second part of the book moves on to demonstrate the benefits and costs of integration across a number of human and environmental applications.
 
This book is an invaluable reference for students and professionals dealing not only with GIS and remote sensing, but also computer science, civil engineering, environmental science and urban planning within the academic, governmental and commercial/business sectors.

Part of the Mastering GIS series, this invaluable one-stop reference work explores the tremendous potential that lies along the interface between GIS and remote sensing for activating seamless databases and instigating information interchange. Integration of GIS and Remote Sensing concentrates on the rigorous and meticulous aspects of analytical data matching and thematic compatibility - the true roots of all branches of GIS/remote sensing applications.

Preface
 
List of Contributors
 
1 GIS and remote sensing integration: in search of a definition
 
Victor Mesev and Alexandra Walrath
 
1.1 Introduction
 
1.2 In search of a definition
 
1.3 Outline of the book
 
1.4 Conclusions
 
2 Integration taxonomy and uncertainty
 
Manfred Ehlers
 
2.1 Introduction
 
2.2 Taxonomy issues
 
2.3 Uncertainty issues
 
2.4 Modelling positional and thematic error in the integration of remote sensing and GIS
 
2.5 Conclusions
 
3 Data fusion related to GIS and remote sensing
 
Paolo Gamba and Fabio Dell'Acqua
 
3.1 Introduction
 
3.2 Why do we need GIS-remote sensing fusion?
 
3.3 Problems in GIS-remote sensing data fusion
 
3.4 Present and future solutions
 
3.5 Conclusions
 
4 The importance of scale in remote sensing and GIS and its implications for data integration.
 
Peter M. Atkinson
 
4.1 Introduction
 
4.2 Data models and scales of measurement
 
4.3 Scales of spatial variation
 
4.4 Remote sensing and GIS data integration
 
4.5 Conclusion
 
5 Of patterns and processes: spatial metrics and geostatistics in urban analysis
 
XiaoHang Liu and Martin Herold
 
5.1 Introduction
 
5.2 Geostatistics
 
5.3 Spatial metrics
 
5.4 Examples
 
5.5 Conclusion
 
6 Using remote sensing and GIS integration to identify spatial characteristics of sprawl at the building-unit level
 
John Hasse
 
6.1 Introduction
 
6.2 Sprawl in the remote sensing and GIS literature
 
6.3 Integrating remote sensing and GIS for sprawl research
 
6.4 Spatial characteristics of sprawl at a building-unit level
 
6.5 A practical building-unit level model for analysing sprawl
 
6.6. Future benefits of integrating remote sensing and gis in sprawl research
 
7 Remote sensing applications in urban socio-economic analysis
 
Chiangshan Wu
 
7.1 Introduction
 
7.2 Principles of urban socio-economic studies using remote sensing technologies
 
7.3 Socio-economic information estimation
 
7.4 Socio-economic activity modelling
 
7.5 Advantages and limitations of remote sensing technologies in socio-economic applications
 
7.6 Conclusions
 
8 Integrating remote sensing, GIS and spatial modelling for sustainable urban growth management
 
Xiaojun Yang
 
8.1 Introduction
 
8.2 Research methodology
 
8.3 Results and discussion
 
8.4 Conclusions
 
9 An integrative GIS and remote sensing model for place-based urban vulnerability analysis
 
Tarek Rashed, John Weeks, Helen Couclelis and Martin Herold
 
9.1 Introduction
 
9.2 Analysis of urban vulnerability: what is it all about?
 
9.3 A conceptual framework for place-based analysis of urban vulnerability
 
9.4 Integrating GIS and remote sensing into vulnerability analysis
 
9.5 A GIS-remote sensing place-based model for urban vulnerability analysis
 
9.6 An illustrative example of model application
 
9.7 Conclusions
 
10 Using GIS and remote sensing for ecological mapping and monitoring
 
Jennifer Miller and John Rogan
 
10.1 Introduction
 
10.2 Integration of GIS and remote sensing in ecological research
 
10.3 GIS data used in ecological applications
 
10.4 Remotely sensed data for ecological applications
 
10.5 Species distribution models
 
10.6 Change detection
 
10.7 Conclusions

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