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The use of coarse-grain, global-scal...

Young, Stephen Slocum.

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The use of coarse-grain, global-scale remote sensing data to analyze forest cover, extent and change, in China, 1982-1992.

Record Type:	Electronic resources : Monograph/item
Title/Author:	The use of coarse-grain, global-scale remote sensing data to analyze forest cover, extent and change, in China, 1982-1992./
Author:	Young, Stephen Slocum.
Description:	255 p.
Notes:	Source: Dissertation Abstracts International, Volume: 58-04, Section: A, page: 1401.
Contained By:	Dissertation Abstracts International58-04A.
Subject:	Geography. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9729027
ISBN:	9780591382013

The use of coarse-grain, global-scale remote sensing data to analyze forest cover, extent and change, in China, 1982-1992.
Young, Stephen Slocum.

The use of coarse-grain, global-scale remote sensing data to analyze forest cover, extent and change, in China, 1982-1992. - 255 p.

Source: Dissertation Abstracts International, Volume: 58-04, Section: A, page: 1401.

Thesis (Ph.D.)--Clark University, 1997.

For millions of years humans have been altering, even transforming the natural environment. Until recently, the transformation of the environment was principally local and regional, but today, it has become truly global in proportion. In understanding the human influence on regional and global environmental change, land-use/land-cover change has been identified as a critical subject of study. Within the realm of land-use/land-cover change, "forest" heads virtually every list of important cover changes requiring extensive investigation. Of all the major forest regions of the world, forest extent and conversion in China is perhaps the least well understood and the most controversial. Current data sets which are used for regional and global land-cover research are insufficient. Recent advances in Remote Sensing and Geographic Information Systems are providing data for potential global land-cover data sets. The International Geosphere-Biosphere Programme (IGBP) has endorsed the use of coarse spatial resolution, high temporal resolution remotely sensed imagery for deriving land-cover classifications for global change research.

ISBN: 9780591382013Subjects--Topical Terms:

524010
Geography.

The use of coarse-grain, global-scale remote sensing data to analyze forest cover, extent and change, in China, 1982-1992.
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100 1 $a Young, Stephen Slocum. $3 3184622
245 1 4 $a The use of coarse-grain, global-scale remote sensing data to analyze forest cover, extent and change, in China, 1982-1992.
300 $a 255 p.
500 $a Source: Dissertation Abstracts International, Volume: 58-04, Section: A, page: 1401.
502 $a Thesis (Ph.D.)--Clark University, 1997.
520 $a For millions of years humans have been altering, even transforming the natural environment. Until recently, the transformation of the environment was principally local and regional, but today, it has become truly global in proportion. In understanding the human influence on regional and global environmental change, land-use/land-cover change has been identified as a critical subject of study. Within the realm of land-use/land-cover change, "forest" heads virtually every list of important cover changes requiring extensive investigation. Of all the major forest regions of the world, forest extent and conversion in China is perhaps the least well understood and the most controversial. Current data sets which are used for regional and global land-cover research are insufficient. Recent advances in Remote Sensing and Geographic Information Systems are providing data for potential global land-cover data sets. The International Geosphere-Biosphere Programme (IGBP) has endorsed the use of coarse spatial resolution, high temporal resolution remotely sensed imagery for deriving land-cover classifications for global change research.
520 $a The research uses three AVHRR-derived global-scale remotely sensed data bases (NOAA-EPA's Monthly Generalized Global Vegetation Index, NOAA's Weekly Maximum Value Composite Global Vegetation Index, and NASA-NOAA's Pathfinder AVHRR Land (PAL) data set) to evaluate land-cover, extent and change, in China with special emphasis on forest cover. The time period for the research is 1982 to 1992. The research uses the analytical techniques of Standardized Principal Components Analysis, and various phenological methods such as Temporal Profiling along with different vegetation reference materials of China.
520 $a The research shows the ability of global-scale remote sensing land-cover data to distinguish different biomes in China with the potential of mapping China's vegetation cover, as well as detecting discrete and broad changes in vegetation over time due to climatic variations as well as land-cover changes (natural and human-induced). The research shows that the most significant change in vegetation cover for China between 1982 and 1992 is decreasing productivity in forest regions, and dramatic increases in productivity in agricultural regions, especially the North China Plain.
520 $a The research has also brought to light some significant problems with the PAL data set. The data set has a major spatial misregistration of the data, particularly for data from NOAA-9 relative to data from NOAA-7 and -11. The effect of this spatial misregistration on the interpretation of vegetation classification and vegetation change will vary depending on the scale of the analysis and the homogeneity of the land cover being analyzed. In general, the larger the area being studied, the less the influence of the spatial misregistration. More influential is the type of land cover in the area being analyzed where the more homogeneous the land-cover, the less influence the spatial misregistration. More importantly, the data set has problems with radiometric miscalibration, especially during the change-over in satellites from NOAA-9 to NOAA-11, with particular problems for forested regions. This is potentially a severe problem because many using the data set believe that the radiometric problems found in early GVI studies have been corrected in the PAL data, but they have only been corrected for regions of low vegetation cover. The data are also severely affected by the eruption of Mount Pinatubo, especially for forested regions and areas in low latitudes. The eruption of Mount Pinatubo has made the data from 1991 and 1992 unreliable for many regions in China.
590 $a School code: 0048.
650 4 $a Geography. $3 524010
650 4 $a Forestry. $3 895157
650 4 $a Remote sensing. $3 535394
650 4 $a Physical geography. $3 516662
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710 2 0 $a Clark University. $3 1017690
773 0 $t Dissertation Abstracts International $g 58-04A.
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791 $a Ph.D.
792 $a 1997
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9729027