Environmental Modelling with GIS and Remote Sensing
"Environmental Modelling with GIS and Remote Sensing" edited by Andrew Skidmore is a comprehensive guide that explores the application of geographic information systems (GIS) and remote sensing in environmental modeling. The book begins with an introduction that discusses the challenges and motivations behind writing the book and provides an overview of environmental modeling and how GIS and remote sensing can aid in this field.
The book then delves into the taxonomy of environmental models in the spatial sciences, including deductive models, inductive models, deterministic models, and stochastic models. The authors discuss the logic and processes behind these models, and how they can be used in environmental modeling.
The next section of the book focuses on new environmental remote sensing systems, including high spatial resolution sensors, high spectral resolution satellites, high temporal resolution satellites, radar systems, and other related technologies. The authors provide historical overviews, an overview of sensors, and discuss applications and perspectives for each type of system.
The book also covers the availability and use of geographic data for environmental modeling and assessment. It discusses various global and sub-global databases that can be used in environmental modeling, such as land cover databases, topographic data, soil data, and population data. The authors also highlight the role of the end-user in the USGS global land cover characterization project.
The biosphere is examined from a global perspective in the next section, focusing on Landsat-based and AVHRR-based regional and global studies. The authors discuss crop inventory, deforestation, habitat fragmentation, and wildfire detection, among others.
Vegetation mapping and monitoring is another important topic covered in the book. The authors provide a historical overview of vegetation mapping, discuss the use of multispectral data and image classification, and explore the use of spatial and temporal patterns in monitoring vegetation change.
The application of remote sensing and GIS in wildlife mapping and modeling is also discussed in detail. Topics such as wildlife conservation, mapping wildlife distribution, mapping wildlife resource requirements, and habitat suitability for wildlife are covered. The authors also discuss species-environment relationships and innovative techniques for wildlife mapping and modeling.
The book concludes with discussions on climate modeling, hydrological modeling, and the future of environmental modeling with GIS and remote sensing. It provides a comprehensive overview of the applications of GIS and remote sensing in environmental modeling and serves as a valuable resource for researchers, professionals, and students in the field of environmental science and remote sensing.