ABSTRACT
Integrating Scale in Remote Sensing and GIS serves as the most comprehensive documentation of the scientific and methodological advances that have taken place in integrating scale and remote sensing data. This work addresses the invariants of scale, the ability to change scale, measures of the impact of scale, scale as a parameter in process models, and the implementation of multiscale approaches as methods and techniques for integrating multiple kinds of remote sensing data collected at varying spatial, temporal, and radiometric scales. Researchers, instructors, and students alike will benefit from a guide that has been pragmatically divided into four thematic groups: scale issues and multiple scaling; physical scale as applied to natural resources; urban scale; and human health/social scale. Teeming with insights that elucidate the significance of scale as a foundation for geographic analysis, this book is a vital resource to those seriously involved in the field of GIScience.
Introduction. Fundamentals of Multiscaled Remote Sensing Data for GIS Integration. Scale and Remote Sensing and GIS Integration: A Revisit of the Issues. Remote Sensing: Advances in Sensors and Data. Integration of Multispatial, Multitemporal, and Multispectral Remote Sensing Data in GIS: Progress and Challenges. Theory, Methods, and Techniques for Multiscale Data Integration. Computational and Technological Issues. Implementation of Multiscale Approaches: Methods and Examples. Modeling Methods for GIS Integration of Multiscaled Remote Sensing Data. Multiscaled Data Fusion for GIS Integration. Uncertainty and Error Analysis in Remote Sensing Data Integration with GIS. Geographic Object-Based Image Analysis. Temporal Analysis for Remote Sensing/GIS Integration. Applications of Multiscaled Remote Sensing and GIS. Approaches to Land Use/Land Change with Multiscaled Remote Sensing Data. Multiscaled Remote Sensing Data for Analysis of Landscape Heterogeneity. Environmental Modeling with Multiscaled Data. Use of Hyperspectral Data Remote Sensing Data in GIS. Analysis of Multiscaled Thermal Remote Sensing Data. Multiscaled Remote Sensing Data and GIS for Modeling Land Surface Processes. GIS, Multiscaled Remote Sensing Data for Climate Change Analysis. Integration of GPS, GIS, and Multiscaled Remote Sensing Data. Real Time Data and GIS Integration Applications. Multiscaled Remote Sensing Data, GIS Integration, and the Future. Summary. Epilogue.
