Small Area Population Estimation | Using GIS, Remote Sensing and Spatial Statistics - Size and Distribution of Human Population

Shuo-Sheng Wu

ISBN 10: 3639450108 / ISBN 13: 9783639450101

Published by AV Akademikerverlag, 2012

About this Item

Small Area Population Estimation | Using GIS, Remote Sensing and Spatial Statistics - Size and Distribution of Human Population | Shuo-Sheng Wu | Taschenbuch | 100 S. | Englisch | 2012 | AV Akademikerverlag | EAN 9783639450101 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 106333749

Bibliographic Details

• Title: Small Area Population Estimation | Using GIS, Remote Sensing and Spatial Statistics - Size and Distribution of Human Population
• Publisher: AV Akademikerverlag
• Publication Date: 2012
• Language: English
• ISBN 10: 3639450108
• ISBN 13: 9783639450101
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 7D millimeters 220 millimeters width by 150 millimeters height by 7 millimeters depth
• Weight: 167 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Revision with unchanged content. Knowledge of the size and distribution of human population is essential for understanding and responding to many social, political, economical, and environmental problems. In the United States, the decennial census is the primary source of demographic data. Although the U.S. Census Bureau conducts census surveys at the household level, the agency only releases the data by aggregated enumeration units, not only to preserve the confidentiality of original respondents, but also for administrative convenience. Currently the finest census population data available to the public is at the block level. The main purpose of this study is to develop methodology to estimate sub-block-level population and to assess the estimation errors. In addition, the author intends to develop methodology for classifying detailed urban land use classes. This study will have broader impacts to the society in its potential applications.

About the Author

The author is a Program Faculty in the Department of Geography at Texas State University-San Marcos, and a UCGIS (University Consortium for Geographic Information Science) Postdoctoral Research Associate at the U.S. Geological Survey (USGS) Center of Excellence for Geospatial Information Science (CEGIS).