Scale in remote sensing and GIS
Author(s)
Bibliographic Information
Scale in remote sensing and GIS
CRC Lewis, c1997
Available at 19 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
Includes bibliographical references and index
Description and Table of Contents
Description
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. Techniques for dealing explicitly with scale are now available in GIS, but, until now, very little literature was available to consider and solve specific issues of scale.
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.
Table of Contents
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.
by "Nielsen BookData"