Artigo

Carbon budget estimation in Central Amazonia: Successional forest modeling from remote sensing data

The carbon budget resulting from the dynamics of forest vegetation was estimated spatially for a study region with intensive land use change in the Central Amazonia forest. Vegetation height was recovered from airborne SAR interferometry, and was used along with an established relationship between f...

ver descrição completa

Autor principal: Neeff, Till
Outros Autores: Graça, Paulo Maurício Lima Alencastro de, Vieira Dutra, Luciano, Costa Freitas, Corina C. da
Grau: Artigo
Idioma: English
Publicado em: Remote Sensing of Environment 2020
Assuntos:
Acesso em linha: https://repositorio.inpa.gov.br/handle/1/18855
id oai:repositorio:1-18855
recordtype dspace
spelling oai:repositorio:1-18855 Carbon budget estimation in Central Amazonia: Successional forest modeling from remote sensing data Neeff, Till Graça, Paulo Maurício Lima Alencastro de Vieira Dutra, Luciano Costa Freitas, Corina C. da Agriculture Biomass Forestry Interferometry Land Use Mathematical Models Synthetic Aperture Radar Vegetation Carbon Budget Forest Height Growth Models Primary Forests Remote Sensing Biomass Carbon Budget Estimation Method Land-use Change Remote Sensing Synthetic Aperture Radar Vegetation Dynamics Agriculture Biomass Forestry Interferometry Land Use Mathematical Models Plants Remote Sensing Amazonia South America Western Hemisphere World The carbon budget resulting from the dynamics of forest vegetation was estimated spatially for a study region with intensive land use change in the Central Amazonia forest. Vegetation height was recovered from airborne SAR interferometry, and was used along with an established relationship between forest height and age for mapping the successional stages of vegetation. A map of forest ages could be generated and validated (age RMSE was 3.5 years). Biomass stocks and annual rates of increment in biomass could be attributed to the forest ages by a comprehensive growth model for forests in the study area. A conceptual model of land use change was developed for the study area that accounts for four different types of land use: primary forest, secondary forest, degraded forest and nonforest. The transition probabilities between those land use types were recovered from internal modeling of available data, from literature sources, and from large-scale remote sensing results. The land use change matrix, area-age densities of secondary forests, and a growth model, yield a spatialized estimate of the carbon budget. The committed emissions from annual land use change were computed. For the year 2000-2001 the carbon balance was negative, on an area of ca. 5700 ha, land use dynamics resulted in a release of approximately 16,000 t of carbon, mainly arising from the cutting of primary forest for agricultural purposes. The secondary forest carbon budget was almost balanced, and forest degradation was revealed less important. © 2004 Elsevier Inc. All rights reserved. 2020-06-15T22:03:29Z 2020-06-15T22:03:29Z 2005 Artigo https://repositorio.inpa.gov.br/handle/1/18855 10.1016/j.rse.2004.12.002 en Volume 94, Número 4, Pags. 508-522 Restrito Remote Sensing of Environment
institution Instituto Nacional de Pesquisas da Amazônia - Repositório Institucional
collection INPA-RI
language English
topic Agriculture
Biomass
Forestry
Interferometry
Land Use
Mathematical Models
Synthetic Aperture Radar
Vegetation
Carbon Budget
Forest Height
Growth Models
Primary Forests
Remote Sensing
Biomass
Carbon Budget
Estimation Method
Land-use Change
Remote Sensing
Synthetic Aperture Radar
Vegetation Dynamics
Agriculture
Biomass
Forestry
Interferometry
Land Use
Mathematical Models
Plants
Remote Sensing
Amazonia
South America
Western Hemisphere
World
spellingShingle Agriculture
Biomass
Forestry
Interferometry
Land Use
Mathematical Models
Synthetic Aperture Radar
Vegetation
Carbon Budget
Forest Height
Growth Models
Primary Forests
Remote Sensing
Biomass
Carbon Budget
Estimation Method
Land-use Change
Remote Sensing
Synthetic Aperture Radar
Vegetation Dynamics
Agriculture
Biomass
Forestry
Interferometry
Land Use
Mathematical Models
Plants
Remote Sensing
Amazonia
South America
Western Hemisphere
World
Neeff, Till
Carbon budget estimation in Central Amazonia: Successional forest modeling from remote sensing data
topic_facet Agriculture
Biomass
Forestry
Interferometry
Land Use
Mathematical Models
Synthetic Aperture Radar
Vegetation
Carbon Budget
Forest Height
Growth Models
Primary Forests
Remote Sensing
Biomass
Carbon Budget
Estimation Method
Land-use Change
Remote Sensing
Synthetic Aperture Radar
Vegetation Dynamics
Agriculture
Biomass
Forestry
Interferometry
Land Use
Mathematical Models
Plants
Remote Sensing
Amazonia
South America
Western Hemisphere
World
description The carbon budget resulting from the dynamics of forest vegetation was estimated spatially for a study region with intensive land use change in the Central Amazonia forest. Vegetation height was recovered from airborne SAR interferometry, and was used along with an established relationship between forest height and age for mapping the successional stages of vegetation. A map of forest ages could be generated and validated (age RMSE was 3.5 years). Biomass stocks and annual rates of increment in biomass could be attributed to the forest ages by a comprehensive growth model for forests in the study area. A conceptual model of land use change was developed for the study area that accounts for four different types of land use: primary forest, secondary forest, degraded forest and nonforest. The transition probabilities between those land use types were recovered from internal modeling of available data, from literature sources, and from large-scale remote sensing results. The land use change matrix, area-age densities of secondary forests, and a growth model, yield a spatialized estimate of the carbon budget. The committed emissions from annual land use change were computed. For the year 2000-2001 the carbon balance was negative, on an area of ca. 5700 ha, land use dynamics resulted in a release of approximately 16,000 t of carbon, mainly arising from the cutting of primary forest for agricultural purposes. The secondary forest carbon budget was almost balanced, and forest degradation was revealed less important. © 2004 Elsevier Inc. All rights reserved.
format Artigo
author Neeff, Till
author2 Graça, Paulo Maurício Lima Alencastro de
Vieira Dutra, Luciano
Costa Freitas, Corina C. da
author2Str Graça, Paulo Maurício Lima Alencastro de
Vieira Dutra, Luciano
Costa Freitas, Corina C. da
title Carbon budget estimation in Central Amazonia: Successional forest modeling from remote sensing data
title_short Carbon budget estimation in Central Amazonia: Successional forest modeling from remote sensing data
title_full Carbon budget estimation in Central Amazonia: Successional forest modeling from remote sensing data
title_fullStr Carbon budget estimation in Central Amazonia: Successional forest modeling from remote sensing data
title_full_unstemmed Carbon budget estimation in Central Amazonia: Successional forest modeling from remote sensing data
title_sort carbon budget estimation in central amazonia: successional forest modeling from remote sensing data
publisher Remote Sensing of Environment
publishDate 2020
url https://repositorio.inpa.gov.br/handle/1/18855
_version_ 1787143940237950976
score 11.755432