Assessment of phenologic variability in Amazon tropical rainforests using hyperspectral hyperion and MODIS satellite data

Alfredo R. Huete; Youngwook Kim; Piyachat Ratana; Kamel Didan; Yosio E. Shimabukuro; Tomoaki Miura

Assessment of phenologic variability in Amazon tropical rainforests using hyperspectral hyperion and MODIS satellite data

Alfredo R. Huete, Youngwook Kim, Piyachat Ratana, Kamel Didan, Yosio E. Shimabukuro, Tomoaki Miura

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Phenology represents the seasonal timing and annual repetition of biologic life cycle events and is a characteristic property of ecosystem functioning and predictor of ecosystem processes. Shifts in phenology depict a canopy’s integrated response to environmental change and influence local biogeochemical processes, including nutrient dynamics, photosynthesis, water cycling, soil moisture depletion, and canopy physiology [1]. An understanding of vegetation phenology is prerequisite to interannual studies and predictive modeling of land surface responses to climate change [2-4].

Original language	English (US)
Title of host publication	Hyperspectral Remote Sensing of Tropical and Sub-Tropical Forests
Publisher	CRC Press
Pages	233-259
Number of pages	27
ISBN (Electronic)	9781420053432
ISBN (Print)	9781420053418
State	Published - Jan 1 2008

ASJC Scopus subject areas

General Engineering
General Earth and Planetary Sciences
General Agricultural and Biological Sciences
General Environmental Science

Cite this

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abstract = "Phenology represents the seasonal timing and annual repetition of biologic life cycle events and is a characteristic property of ecosystem functioning and predictor of ecosystem processes. Shifts in phenology depict a canopy{\textquoteright}s integrated response to environmental change and influence local biogeochemical processes, including nutrient dynamics, photosynthesis, water cycling, soil moisture depletion, and canopy physiology [1]. An understanding of vegetation phenology is prerequisite to interannual studies and predictive modeling of land surface responses to climate change [2-4].",

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AU - Huete, Alfredo R.

AU - Kim, Youngwook

AU - Ratana, Piyachat

AU - Didan, Kamel

AU - Shimabukuro, Yosio E.

AU - Miura, Tomoaki

PY - 2008/1/1

Y1 - 2008/1/1

N2 - Phenology represents the seasonal timing and annual repetition of biologic life cycle events and is a characteristic property of ecosystem functioning and predictor of ecosystem processes. Shifts in phenology depict a canopy’s integrated response to environmental change and influence local biogeochemical processes, including nutrient dynamics, photosynthesis, water cycling, soil moisture depletion, and canopy physiology [1]. An understanding of vegetation phenology is prerequisite to interannual studies and predictive modeling of land surface responses to climate change [2-4].

AB - Phenology represents the seasonal timing and annual repetition of biologic life cycle events and is a characteristic property of ecosystem functioning and predictor of ecosystem processes. Shifts in phenology depict a canopy’s integrated response to environmental change and influence local biogeochemical processes, including nutrient dynamics, photosynthesis, water cycling, soil moisture depletion, and canopy physiology [1]. An understanding of vegetation phenology is prerequisite to interannual studies and predictive modeling of land surface responses to climate change [2-4].

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M3 - Chapter

AN - SCOPUS:43649097370

SN - 9781420053418

SP - 233

EP - 259

BT - Hyperspectral Remote Sensing of Tropical and Sub-Tropical Forests

PB - CRC Press

ER -

Assessment of phenologic variability in Amazon tropical rainforests using hyperspectral hyperion and MODIS satellite data

Abstract

ASJC Scopus subject areas

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