Spatial and Temporal Amazon Vegetation Dynamics and Phenology Using Time Series Satellite Data

Persistent Link:
http://hdl.handle.net/10150/194427
Title:
Spatial and Temporal Amazon Vegetation Dynamics and Phenology Using Time Series Satellite Data
Author:
Ratana, Piyachat
Issue Date:
2006
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Improved knowledge of landscape seasonal variations and phenology at the regional scale is needed for carbon and water flux studies, and biogeochemical, hydrological, and climate models. Amazon vegetation mechanisms and dynamics controlling biosphere-atmosphere interactions are not entirely understood. To better understand these processes, vegetation photosynthetic activity and canopy water and temperature dynamics were analyzed over various types of vegetation in Amazon using satellite data from the Terra-Moderate Resolution Imaging Spectroradiometer (MODIS). The objectives of this dissertation were to 1) assess the spatial and temporal variations of satellite data over the Amazon as a function of vegetation physiognomies for monitoring and discrimination, 2) investigate seasonal vegetation photosynthetic activity and phenology across the forest-cerrado ecotone and conversion areas, and 3) investigate seasonal variations of satellite-based canopy water and land surface temperature in relation to photosynthetic activity over the Amazon basin.The results of this study showed the highly diverse and complex cerrado biome and associated cerrado conversions could be monitored and analyzed with MODIS vegetation index (VI) time series data. The MODIS enhanced vegetation index (EVI) seasonal profiles were found useful in characterizing the spatial and temporal variability in landscape phenology across a climatic gradient of rainfall and sunlight conditions through the rainforest-cerrado ecotone. Significant trends in landscape phenology were observed across the different biomes with strong seasonal shifts resulting from differences in vegetation physiognomic responses to rainfall and sunlight. We also found unique seasonal and temporal patterns of the land surface water index (LSWI) and land surface temperature (LST), which in combination with the EVI provided improved information for monitoring the seasonal ecosystem dynamics of the Amazon rainforest, cerrado, ecotone, and conversion areas. In conclusion, satellite-based, regional scale studies were found to aid in understanding land surface processes and mechanisms at the ecosystem level, providing a "big picture" of landscape dynamics. Coupling this with ground, in-situ measurements, such as from flux towers, can greatly improve the estimation of carbon and water fluxes, and our understanding of the biogeochemistry and climate in very dynamic and changing landscapes.
Type:
text; Electronic Dissertation
Keywords:
Remote Sensing; Phenology; Amazon
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Soil, Water & Environmental Science; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Huete, Alfredo; Moran, Susan
Committee Chair:
Huete, Alfredo; Moran, Susan

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleSpatial and Temporal Amazon Vegetation Dynamics and Phenology Using Time Series Satellite Dataen_US
dc.creatorRatana, Piyachaten_US
dc.contributor.authorRatana, Piyachaten_US
dc.date.issued2006en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractImproved knowledge of landscape seasonal variations and phenology at the regional scale is needed for carbon and water flux studies, and biogeochemical, hydrological, and climate models. Amazon vegetation mechanisms and dynamics controlling biosphere-atmosphere interactions are not entirely understood. To better understand these processes, vegetation photosynthetic activity and canopy water and temperature dynamics were analyzed over various types of vegetation in Amazon using satellite data from the Terra-Moderate Resolution Imaging Spectroradiometer (MODIS). The objectives of this dissertation were to 1) assess the spatial and temporal variations of satellite data over the Amazon as a function of vegetation physiognomies for monitoring and discrimination, 2) investigate seasonal vegetation photosynthetic activity and phenology across the forest-cerrado ecotone and conversion areas, and 3) investigate seasonal variations of satellite-based canopy water and land surface temperature in relation to photosynthetic activity over the Amazon basin.The results of this study showed the highly diverse and complex cerrado biome and associated cerrado conversions could be monitored and analyzed with MODIS vegetation index (VI) time series data. The MODIS enhanced vegetation index (EVI) seasonal profiles were found useful in characterizing the spatial and temporal variability in landscape phenology across a climatic gradient of rainfall and sunlight conditions through the rainforest-cerrado ecotone. Significant trends in landscape phenology were observed across the different biomes with strong seasonal shifts resulting from differences in vegetation physiognomic responses to rainfall and sunlight. We also found unique seasonal and temporal patterns of the land surface water index (LSWI) and land surface temperature (LST), which in combination with the EVI provided improved information for monitoring the seasonal ecosystem dynamics of the Amazon rainforest, cerrado, ecotone, and conversion areas. In conclusion, satellite-based, regional scale studies were found to aid in understanding land surface processes and mechanisms at the ecosystem level, providing a "big picture" of landscape dynamics. Coupling this with ground, in-situ measurements, such as from flux towers, can greatly improve the estimation of carbon and water fluxes, and our understanding of the biogeochemistry and climate in very dynamic and changing landscapes.en_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.subjectRemote Sensingen_US
dc.subjectPhenologyen_US
dc.subjectAmazonen_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineSoil, Water & Environmental Scienceen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorHuete, Alfredoen_US
dc.contributor.advisorMoran, Susanen_US
dc.contributor.chairHuete, Alfredoen_US
dc.contributor.chairMoran, Susanen_US
dc.contributor.committeememberMatthais, Allanen_US
dc.contributor.committeememberArcher, Steven R.en_US
dc.contributor.committeememberMarsh, Stuarten_US
dc.identifier.proquest1879en_US
dc.identifier.oclc659746436en_US
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