Scale in Remote Sensing and GIS

by Michael F. Goodchild (Editor), Dale A. Quattrochi (Editor)

Overview

The recent emergence and widespread use of remote sensing and geographic information systems (GIS) has prompted new interest in scale as a key component of these and other geographic information technologies. With a balanced mixture of concepts, practical examples, techniques, and theory, Scale in Remote Sensing and GIS is a guide for students and users of remote sensing and GIS who must deal with the issues raised by multiple temporal and spatial scales. Sixteen pages of full-color photographs help demonstrate key points made in the text.

Product Details

ISBN-13:	9781351417617
Publisher:	CRC Press
Publication date:	01/13/2023
Sold by:	Barnes & Noble
Format:	eBook
Pages:	432
File size:	18 MB
Note:	This product may take a few minutes to download.

About the Author

Dale A. Quattrochi is a geographer and senior research scientist with the NASA George C. Marshall Space Flight Center, Earth Science Office in Huntsville, Alabama. His research has focused on the analysis of multiscaled remote sensing data for GIS integration, the use of NASA satellite and airborne remote sensing data for analysis of land cover/land use changes, particularly as related to the urban environment, thermal remote sensing of the urban heat island effect, and in the applications of NASA data and models to public health issues. He is the coeditor of three books published by CRC Press: Scale in Remote Sensing and GIS (1997), Thermal Remote Sensing in Land Surface Processes (2004), and Urban Remote Sensing (2007). Michael F. Goodchild (University of Califorinia, Santa Barbara, USA).

Table of Contents

Introduction: Scale, Multiscaling, Remote Sensing, and GIS. Multiscale Nature of Spatial Data in Scaling Up Environmental Models. Scale Dependence of NDVI and its Relationship to Mountainous Terrain. Understanding the Scale and Resolution Effects in Remote Sensing and GIS. Multiresolution Covariation among Landsat and AVHRR Vegetation Indices. Multiscaling Analysis in Distributed Modeling and Remote Sensing: An Application Using Soil Moisture. Examining the Effects of Sensor Resolution and Sub-Pixel Heterogeneity on Spectral Vegetation Indices: Implications for Biophysical Modeling. Multiscale Vegetation Data for the Mountains of Southern California: Spatial and Categorical Resolution. The Use of Remotely Sensed Surface Temperatures from an Aircraft-Based Thermal Infrared Multispectral Scanner (TIMS) to Estimate the Spatial and Temporal Variability of Latent Heat Fluxes and Thermal Response Numbers from a White Pine (Pinus strobus L.) Plantation. Scaling Predicted Pine Forest Hydrology and Productivity across the Southern United States. Modeling Effects of Spatial Pattern, Drought, and Grazing on Rates of Rangeland Degradation: A Combined Markov and Cellular Automaton Approach. Scaling Land Cover Heterogeneity for Global Atmosphere-Biosphere Models. Quadtrees: Hierarchical Multiresolution Data Structures for Analysis of Digital Images. Statistical Models for Multiple Scaled Analysis. Image Characterization and Modeling System (ICAMS): A Geographic Information System for the Characterization and Modeling of Multiscale Remote Sensing Data. Approaches to Scaling of Geo-Spatial Data. Multifractals and Remotely Sensed Data: Generalized Scale Invariance, Geographical Information Systems and Resolution Dependence. Index.