Reconstructing historical forest cover change in the Lower Amazon floodplains using the LandTrendr algorithm
Main Author: | |
---|---|
Publication Date: | 2016 |
Other Authors: | , |
Format: | Article |
Language: | eng |
Source: | Acta Amazonica |
Download full: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0044-59672016000100013 |
Summary: | ABSTRACTThe Amazon várzeas are an important component of the Amazon biome, but anthropic and climatic impacts have been leading to forest loss and interruption of essential ecosystem functions and services. The objectives of this study were to evaluate the capability of the Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) algorithm to characterize changes in várzeaforest cover in the Lower Amazon, and to analyze the potential of spectral and temporal attributes to classify forest loss as either natural or anthropogenic. We used a time series of 37 Landsat TM and ETM+ images acquired between 1984 and 2009. We used the LandTrendr algorithm to detect forest cover change and the attributes of "start year", "magnitude", and "duration" of the changes, as well as "NDVI at the end of series". Detection was restricted to areas identified as having forest cover at the start and/or end of the time series. We used the Support Vector Machine (SVM) algorithm to classify the extracted attributes, differentiating between anthropogenic and natural forest loss. Detection reliability was consistently high for change events along the Amazon River channel, but variable for changes within the floodplain. Spectral-temporal trajectories faithfully represented the nature of changes in floodplain forest cover, corroborating field observations. We estimated anthropogenic forest losses to be larger (1.071 ha) than natural losses (884 ha), with a global classification accuracy of 94%. We conclude that the LandTrendr algorithm is a reliable tool for studies of forest dynamics throughout the floodplain. |
id |
INPA-3_68c2d1dc97d50df43a7962a80af6128a |
---|---|
oai_identifier_str |
oai:scielo:S0044-59672016000100013 |
network_acronym_str |
INPA-3 |
network_name_str |
Acta Amazonica |
repository_id_str |
|
spelling |
Reconstructing historical forest cover change in the Lower Amazon floodplains using the LandTrendr algorithmWetlandsflooded forestland use changemonitoringLandsatABSTRACTThe Amazon várzeas are an important component of the Amazon biome, but anthropic and climatic impacts have been leading to forest loss and interruption of essential ecosystem functions and services. The objectives of this study were to evaluate the capability of the Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) algorithm to characterize changes in várzeaforest cover in the Lower Amazon, and to analyze the potential of spectral and temporal attributes to classify forest loss as either natural or anthropogenic. We used a time series of 37 Landsat TM and ETM+ images acquired between 1984 and 2009. We used the LandTrendr algorithm to detect forest cover change and the attributes of "start year", "magnitude", and "duration" of the changes, as well as "NDVI at the end of series". Detection was restricted to areas identified as having forest cover at the start and/or end of the time series. We used the Support Vector Machine (SVM) algorithm to classify the extracted attributes, differentiating between anthropogenic and natural forest loss. Detection reliability was consistently high for change events along the Amazon River channel, but variable for changes within the floodplain. Spectral-temporal trajectories faithfully represented the nature of changes in floodplain forest cover, corroborating field observations. We estimated anthropogenic forest losses to be larger (1.071 ha) than natural losses (884 ha), with a global classification accuracy of 94%. We conclude that the LandTrendr algorithm is a reliable tool for studies of forest dynamics throughout the floodplain.Instituto Nacional de Pesquisas da Amazônia2016-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0044-59672016000100013Acta Amazonica v.46 n.1 2016reponame:Acta Amazonicainstname:Instituto Nacional de Pesquisas da Amazônia (INPA)instacron:INPA10.1590/1809-4392201500835info:eu-repo/semantics/openAccessFRAGAL,Everton HafemannSILVA,Thiago Sanna FreireNOVO,Evlyn Márcia Leão de Moraeseng2015-10-19T00:00:00Zoai:scielo:S0044-59672016000100013Revistahttps://acta.inpa.gov.br/PUBhttps://old.scielo.br/oai/scielo-oai.phpacta@inpa.gov.br||acta@inpa.gov.br1809-43920044-5967opendoar:2015-10-19T00:00Acta Amazonica - Instituto Nacional de Pesquisas da Amazônia (INPA)false |
dc.title.none.fl_str_mv |
Reconstructing historical forest cover change in the Lower Amazon floodplains using the LandTrendr algorithm |
title |
Reconstructing historical forest cover change in the Lower Amazon floodplains using the LandTrendr algorithm |
spellingShingle |
Reconstructing historical forest cover change in the Lower Amazon floodplains using the LandTrendr algorithm FRAGAL,Everton Hafemann Wetlands flooded forest land use change monitoring Landsat |
title_short |
Reconstructing historical forest cover change in the Lower Amazon floodplains using the LandTrendr algorithm |
title_full |
Reconstructing historical forest cover change in the Lower Amazon floodplains using the LandTrendr algorithm |
title_fullStr |
Reconstructing historical forest cover change in the Lower Amazon floodplains using the LandTrendr algorithm |
title_full_unstemmed |
Reconstructing historical forest cover change in the Lower Amazon floodplains using the LandTrendr algorithm |
title_sort |
Reconstructing historical forest cover change in the Lower Amazon floodplains using the LandTrendr algorithm |
author |
FRAGAL,Everton Hafemann |
author_facet |
FRAGAL,Everton Hafemann SILVA,Thiago Sanna Freire NOVO,Evlyn Márcia Leão de Moraes |
author_role |
author |
author2 |
SILVA,Thiago Sanna Freire NOVO,Evlyn Márcia Leão de Moraes |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
FRAGAL,Everton Hafemann SILVA,Thiago Sanna Freire NOVO,Evlyn Márcia Leão de Moraes |
dc.subject.por.fl_str_mv |
Wetlands flooded forest land use change monitoring Landsat |
topic |
Wetlands flooded forest land use change monitoring Landsat |
description |
ABSTRACTThe Amazon várzeas are an important component of the Amazon biome, but anthropic and climatic impacts have been leading to forest loss and interruption of essential ecosystem functions and services. The objectives of this study were to evaluate the capability of the Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) algorithm to characterize changes in várzeaforest cover in the Lower Amazon, and to analyze the potential of spectral and temporal attributes to classify forest loss as either natural or anthropogenic. We used a time series of 37 Landsat TM and ETM+ images acquired between 1984 and 2009. We used the LandTrendr algorithm to detect forest cover change and the attributes of "start year", "magnitude", and "duration" of the changes, as well as "NDVI at the end of series". Detection was restricted to areas identified as having forest cover at the start and/or end of the time series. We used the Support Vector Machine (SVM) algorithm to classify the extracted attributes, differentiating between anthropogenic and natural forest loss. Detection reliability was consistently high for change events along the Amazon River channel, but variable for changes within the floodplain. Spectral-temporal trajectories faithfully represented the nature of changes in floodplain forest cover, corroborating field observations. We estimated anthropogenic forest losses to be larger (1.071 ha) than natural losses (884 ha), with a global classification accuracy of 94%. We conclude that the LandTrendr algorithm is a reliable tool for studies of forest dynamics throughout the floodplain. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-03-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0044-59672016000100013 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0044-59672016000100013 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1809-4392201500835 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Instituto Nacional de Pesquisas da Amazônia |
publisher.none.fl_str_mv |
Instituto Nacional de Pesquisas da Amazônia |
dc.source.none.fl_str_mv |
Acta Amazonica v.46 n.1 2016 reponame:Acta Amazonica instname:Instituto Nacional de Pesquisas da Amazônia (INPA) instacron:INPA |
instname_str |
Instituto Nacional de Pesquisas da Amazônia (INPA) |
instacron_str |
INPA |
institution |
INPA |
reponame_str |
Acta Amazonica |
collection |
Acta Amazonica |
repository.name.fl_str_mv |
Acta Amazonica - Instituto Nacional de Pesquisas da Amazônia (INPA) |
repository.mail.fl_str_mv |
acta@inpa.gov.br||acta@inpa.gov.br |
_version_ |
1752129840325066752 |