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Assessing seasonal features of tropi...

Bonifaz-Alfonzo, Roberto.

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Assessing seasonal features of tropical forests using remote sensing.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Assessing seasonal features of tropical forests using remote sensing./
Author:	Bonifaz-Alfonzo, Roberto.
Description:	191 p.
Notes:	Source: Dissertation Abstracts International, Volume: 72-07, Section: B, page: .
Contained By:	Dissertation Abstracts International72-07B.
Subject:	Geography. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3454352
ISBN:	9781124636436

Assessing seasonal features of tropical forests using remote sensing.
Bonifaz-Alfonzo, Roberto.

Assessing seasonal features of tropical forests using remote sensing. - 191 p.

Source: Dissertation Abstracts International, Volume: 72-07, Section: B, page: .

Thesis (Ph.D.)--The University of Nebraska - Lincoln, 2011.

Tropical forests are key components of the biogeochemical cycles, complex in structure, diversity and dynamics, also, tropical regions have been deforested and modified by human activities particularly for agriculture. Understanding the inter-annual and intra-annual variation dynamics of tropical regions could give valuable information on temporal characteristics of ecosystems behavior which is important for mapping and monitoring. This dissertation assesses seasonal and inter-annual changes in the tropical land cover that may be related to changes in the natural environment and/or human activities. Research was focused on the Mayan forest located in southern Mexico and Northwest Guatemala, one of the northern-most important tropical areas in the continent. Using vegetation index products from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 to 2005, the vegetation condition "greenness" was modeled through temporal profiles. The higher spatial resolution data and the availability of two vegetation indices: the standard Normalized Difference Vegetation Index (NDVI), and the Enhanced Vegetation Index (EVI), designed to improve sensitivity to differences in vegetation from sparse to dense vegetation conditions, offer a great opportunity to model vegetation dynamics in tropical areas. Additionally, the Wide Dynamic Range Vegetation Index (WDRVI) which is derived from the NDVI and designed to enhance the spectral response where the NDVI saturates, is included. Comparison between the different vegetation indices is analyzed by means of cross-plots and a wavelet analysis. Then a Fourier series approximation calculation was applied to extract the main seasonal components (high harmonics amplitude and phase) of the biweekly greenness profiles in order to input to an unsupervised classification to obtain a land use/land cover map and to compare mean amplitude and phase parameters value between years.

ISBN: 9781124636436Subjects--Topical Terms:

524010
Geography.

Assessing seasonal features of tropical forests using remote sensing.
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008 130515s2011 ||||||||||||||||| ||eng d
020 $a 9781124636436
035 $a (UMI)AAI3454352
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040 $a UMI $c UMI
100 1 $a Bonifaz-Alfonzo, Roberto. $3 1676564
245 1 0 $a Assessing seasonal features of tropical forests using remote sensing.
300 $a 191 p.
500 $a Source: Dissertation Abstracts International, Volume: 72-07, Section: B, page: .
500 $a Adviser: James W. Merchant.
502 $a Thesis (Ph.D.)--The University of Nebraska - Lincoln, 2011.
520 $a Tropical forests are key components of the biogeochemical cycles, complex in structure, diversity and dynamics, also, tropical regions have been deforested and modified by human activities particularly for agriculture. Understanding the inter-annual and intra-annual variation dynamics of tropical regions could give valuable information on temporal characteristics of ecosystems behavior which is important for mapping and monitoring. This dissertation assesses seasonal and inter-annual changes in the tropical land cover that may be related to changes in the natural environment and/or human activities. Research was focused on the Mayan forest located in southern Mexico and Northwest Guatemala, one of the northern-most important tropical areas in the continent. Using vegetation index products from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 to 2005, the vegetation condition "greenness" was modeled through temporal profiles. The higher spatial resolution data and the availability of two vegetation indices: the standard Normalized Difference Vegetation Index (NDVI), and the Enhanced Vegetation Index (EVI), designed to improve sensitivity to differences in vegetation from sparse to dense vegetation conditions, offer a great opportunity to model vegetation dynamics in tropical areas. Additionally, the Wide Dynamic Range Vegetation Index (WDRVI) which is derived from the NDVI and designed to enhance the spectral response where the NDVI saturates, is included. Comparison between the different vegetation indices is analyzed by means of cross-plots and a wavelet analysis. Then a Fourier series approximation calculation was applied to extract the main seasonal components (high harmonics amplitude and phase) of the biweekly greenness profiles in order to input to an unsupervised classification to obtain a land use/land cover map and to compare mean amplitude and phase parameters value between years.
520 $a Results show differences between indices in terms of seasonal and vegetation response. In terms of mapping the WDRVI was the index with better performance. Fourier parameters mapping, particularly the first harmonic phase, was sensitive to annual variation of environmental conditions (precipitation). The use of multitemporal observations through remote sensing observations, provide a continuous and dynamic view of tropical regions to support monitoring and sustainable development and management of environmental policies.
590 $a School code: 0138.
650 4 $a Geography. $3 524010
650 4 $a Natural Resource Management. $3 676989
650 4 $a Remote Sensing. $3 1018559
690 $a 0366
690 $a 0528
690 $a 0799
710 2 $a The University of Nebraska - Lincoln. $b Geography. $3 1028894
773 0 $t Dissertation Abstracts International $g 72-07B.
790 1 0 $a Merchant, James W., $e advisor
790 1 0 $a Rundquist, Donald C. $e committee member
790 1 0 $a Gitelson, Anatoly $e committee member
790 1 0 $a Wardlow, Brian $e committee member
790 $a 0138
791 $a Ph.D.
792 $a 2011
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3454352