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Remote sensing applications to suppo...

Brewer, Charles Kenneth.

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Remote sensing applications to support sustainable natural resource management.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Remote sensing applications to support sustainable natural resource management./
作者:	Brewer, Charles Kenneth.
面頁冊數:	169 p.
附註:	Adviser: LLoyd P. Queen.
Contained By:	Dissertation Abstracts International68-09B.
標題:	Agriculture, Forestry and Wildlife. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3278261
ISBN:	9780549225263

Remote sensing applications to support sustainable natural resource management.
Brewer, Charles Kenneth.

Remote sensing applications to support sustainable natural resource management. - 169 p.

Adviser: LLoyd P. Queen.

Thesis (Ph.D.)--University of Montana, 2007.

The original design of this dissertation project was relatively simple and straightforward. It was intended to produce one single, dynamic, classification and mapping system for existing vegetation that could rely on commonly available inventory and remote sensing data. This classification and mapping system was intended to provide the analytical basis for resource planning and management. The problems encountered during the first phase of the original design transformed this project into an extensive analysis of the nature of these problems and a decade-long remote sensing applications development endeavor. What evolved from this applications development process is a portion of what has become a "system of systems" to inform and support natural resource management.

ISBN: 9780549225263Subjects--Topical Terms:

783690
Agriculture, Forestry and Wildlife.

Remote sensing applications to support sustainable natural resource management.
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100 1 $a Brewer, Charles Kenneth. $3 1266243
245 1 0 $a Remote sensing applications to support sustainable natural resource management.
300 $a 169 p.
500 $a Adviser: LLoyd P. Queen.
500 $a Source: Dissertation Abstracts International, Volume: 68-09, Section: B, page: 5648.
502 $a Thesis (Ph.D.)--University of Montana, 2007.
520 $a The original design of this dissertation project was relatively simple and straightforward. It was intended to produce one single, dynamic, classification and mapping system for existing vegetation that could rely on commonly available inventory and remote sensing data. This classification and mapping system was intended to provide the analytical basis for resource planning and management. The problems encountered during the first phase of the original design transformed this project into an extensive analysis of the nature of these problems and a decade-long remote sensing applications development endeavor. What evolved from this applications development process is a portion of what has become a "system of systems" to inform and support natural resource management.
520 $a This dissertation presents the progression of work that sequentially developed a suite of remote sensing applications designed to address different aspects of the problems encountered with the original project. These remote sensing applications feature different resource issues, and resource components and are presented in separate chapters. Chapter one provides an introduction and description of the project evolution and chapter six provides a summary of the work and concluding discussion. Chapters two through five describe remote sensing applications that represent related, yet independent studies that are presented essentially as previously published.
520 $a Chapter two evaluates different approaches to classifying and mapping fire severity using multi-temporal Landsat TM data. The recommended method currently represents the analytical basis for fire severity data produced by the USDA Forest Service and the US Geological Survey. Chapter three also uses multi-temporal Landsat data and compares quantitative, remote-sensing-based change detection methods for forest management related canopy change. The recommended method has been widely applied for a variety of forest health and disaster response applications. Chapter four presents a method for multi-source and multi-classifier regional land cover mapping that is currently incorporated in the USDA Forest Service Existing Vegetation Classification and Mapping Technical Guide. Chapter five presents a study using nearest neighbor imputation methods to generate geospatial data surfaces for simulation modeling of vegetation through time and space. While these results have not yet been successful enough to support widespread adoption and implementation, it is possible that these general methods can be adapted to perform adequately for simulation modeling data needs.
590 $a School code: 0136.
650 4 $a Agriculture, Forestry and Wildlife. $3 783690
650 4 $a Biology, Ecology. $3 1017726
650 4 $a Remote Sensing. $3 1018559
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710 2 $a University of Montana. $b Forestry. $3 1031083
773 0 $t Dissertation Abstracts International $g 68-09B.
790 $a 0136
790 1 0 $a Milner, Kelsey S. $e committee member
790 1 0 $a Moeur, Melinda $e committee member
790 1 0 $a Pfister, Robert D. $e committee member
790 1 0 $a Queen, LLoyd P., $e advisor
790 1 0 $a Zuuring, Hans R. $e committee member
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3278261