東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Extracting temporal and spatial info...

Wallace, Cynthia S. A.

Linked to FindBook

Google Book

Amazon

博客來

Extracting temporal and spatial information from remotely sensed data for mapping wildlife habitat.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Extracting temporal and spatial information from remotely sensed data for mapping wildlife habitat./
Author:	Wallace, Cynthia S. A.
Description:	198 p.
Notes:	Source: Dissertation Abstracts International, Volume: 63-12, Section: B, page: 5734.
Contained By:	Dissertation Abstracts International63-12B.
Subject:	Physical Geography. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3073271
ISBN:	0493934510

Extracting temporal and spatial information from remotely sensed data for mapping wildlife habitat.
Wallace, Cynthia S. A.

Extracting temporal and spatial information from remotely sensed data for mapping wildlife habitat. - 198 p.

Source: Dissertation Abstracts International, Volume: 63-12, Section: B, page: 5734.

Thesis (Ph.D.)--The University of Arizona, 2002.

The research accomplished in this dissertation used both mathematical and statistical techniques to extract and evaluate measures of landscape temporal dynamics and spatial structure from remotely sensed data for the purpose of mapping wildlife habitat. By coupling the landscape measures gleaned from the remotely sensed data with various sets of animal sightings and population data, effective models of habitat preference were created.

ISBN: 0493934510Subjects--Topical Terms:

893400
Physical Geography.

Extracting temporal and spatial information from remotely sensed data for mapping wildlife habitat.
LDR:03630nmm 2200349 4500 001 1845576
005 20051101072032.5
008 130614s2002 eng d
020 $a 0493934510
035 $a (UnM)AAI3073271
035 $a AAI3073271
040 $a UnM $c UnM
100 1 $a Wallace, Cynthia S. A. $3 1933731
245 1 0 $a Extracting temporal and spatial information from remotely sensed data for mapping wildlife habitat.
300 $a 198 p.
500 $a Source: Dissertation Abstracts International, Volume: 63-12, Section: B, page: 5734.
500 $a Director: Stuart E. Marsh.
502 $a Thesis (Ph.D.)--The University of Arizona, 2002.
520 $a The research accomplished in this dissertation used both mathematical and statistical techniques to extract and evaluate measures of landscape temporal dynamics and spatial structure from remotely sensed data for the purpose of mapping wildlife habitat. By coupling the landscape measures gleaned from the remotely sensed data with various sets of animal sightings and population data, effective models of habitat preference were created.
520 $a Measures of temporal dynamics of vegetation greenness as measured by National Oceanographic and Atmospheric Administration's Advanced Very High Resolution Radiometer (AVHRR) satellite were used to effectively characterize and map season specific habitat of the Sonoran pronghorn antelope, as well as produce preliminary models of potential yellow-billed cuckoo habitat in Arizona. Various measures that capture different aspects of the temporal dynamics of the landscape were derived from AVHRR Normalized Difference Vegetation Index composite data using three main classes of calculations: basic statistics, standardized principal components analysis, and Fourier analysis. Pronghorn habitat models based on the AVHRR measures correspond visually and statistically to GIS-based models produced using data that represent detailed knowledge of ground-condition.
520 $a Measures of temporal dynamics also revealed statistically significant correlations with annual estimates of elk population in selected Arizona Game Management Units, suggesting elk respond to regional environmental changes that can be measured using satellite data. Such relationships, once verified and established, can be used to help indirectly monitor the population.
520 $a Measures of landscape spatial structure derived from IKONOS high spatial resolution (1-m) satellite data using geostatistics effectively map details of Sonoran pronghorn antelope habitat. Local estimates of the nugget, sill, and range variogram parameters calculated within 25 x 25-meter image windows describe the spatial autocorrelation of the image, permitting classification of all pixels into coherent units whose signature graphs exhibit a classic variogram shape. The variogram parameters captured in these signatures have been shown in previous studies to discriminate between different species-specific vegetation associations.
520 $a The synoptic view of the landscape provided by satellite data can inform resource management efforts. The ability to characterize the spatial structure and temporal dynamics of habitat using repeatable remote sensing data allows closer monitoring of the relationship between a species and its landscape.
590 $a School code: 0009.
650 4 $a Physical Geography. $3 893400
650 4 $a Agriculture, Forestry and Wildlife. $3 783690
650 4 $a Agriculture, Range Management. $3 1022885
650 4 $a Remote Sensing. $3 1018559
690 $a 0368
690 $a 0478
690 $a 0777
690 $a 0799
710 2 0 $a The University of Arizona. $3 1017508
773 0 $t Dissertation Abstracts International $g 63-12B.
790 1 0 $a Marsh, Stuart E., $e advisor
790 $a 0009
791 $a Ph.D.
792 $a 2002
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3073271