Mapping Clearances in Tropical Dry Forests Using Breakpoints, Trend, and Seasonal Components from MODIS Time Series: Does Forest Type Matter?

Tropical environments present a unique challenge for optical time series analysis, primarily owing to fragmented data availability, persistent cloud cover and atmospheric aerosols. Additionally, little is known of whether the performance of time series change detection is affected by diverse forest types found in tropical dry regions. In this paper, we develop a methodology for mapping forest clearing in Southeast Asia using a study region characterised by heterogeneous forest types. Moderate Resolution Imaging Spectroradiometer (MODIS) time series are decomposed using Breaks For Additive Season and Trend (BFAST) and breakpoints, trend, and seasonal components are combined in a binomial probability model to distinguish between cleared and stable forest. We found that the addition of seasonality and trend information improves the change model performance compared to using breakpoints alone. We also demonstrate the value of considering forest type in disturbance mapping in comparison to the more common approach that combines all forest typesinto a single generalised forest class. By taking a generalised forest approach, there is less control over the error distribution in each forest type. Dry-deciduous and evergreen forests are especially sensitive to error imbalances using a generalised forest model i.e., clearances were underestimated in evergreen forest, and overestimated in dry-deciduous forest. This suggests that forest type needs to be considered in time series change mapping, especially in heterogeneous forest regions. Our approach builds towards improving large-area monitoring of forest-diverse regions such as Southeast Asia. The findings of this study should also be transferable across optical sensors and are therefore relevant for the future availability of dense time series for the tropics at higherspatial resolutions.

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Bibliographic Details
Main Authors: Grogan, Kenneth, Pflugmacher, Dirk, Hostert, Patrick, Verbesselt, Jan, Fensholt, Rasmus
Format: Article/Letter to editor biblioteca
Language:English
Subjects:Accuracy, BFAST, Change detection, Deforestation, Dry deciduous, Evergreen, Southeast Asia,
Online Access:https://research.wur.nl/en/publications/mapping-clearances-in-tropical-dry-forests-using-breakpoints-tren
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spelling dig-wur-nl-wurpubs-5072342024-10-01 Grogan, Kenneth Pflugmacher, Dirk Hostert, Patrick Verbesselt, Jan Fensholt, Rasmus Article/Letter to editor Remote Sensing 8 (2016) 8 ISSN: 2072-4292 Mapping Clearances in Tropical Dry Forests Using Breakpoints, Trend, and Seasonal Components from MODIS Time Series: Does Forest Type Matter? 2016 Tropical environments present a unique challenge for optical time series analysis, primarily owing to fragmented data availability, persistent cloud cover and atmospheric aerosols. Additionally, little is known of whether the performance of time series change detection is affected by diverse forest types found in tropical dry regions. In this paper, we develop a methodology for mapping forest clearing in Southeast Asia using a study region characterised by heterogeneous forest types. Moderate Resolution Imaging Spectroradiometer (MODIS) time series are decomposed using Breaks For Additive Season and Trend (BFAST) and breakpoints, trend, and seasonal components are combined in a binomial probability model to distinguish between cleared and stable forest. We found that the addition of seasonality and trend information improves the change model performance compared to using breakpoints alone. We also demonstrate the value of considering forest type in disturbance mapping in comparison to the more common approach that combines all forest typesinto a single generalised forest class. By taking a generalised forest approach, there is less control over the error distribution in each forest type. Dry-deciduous and evergreen forests are especially sensitive to error imbalances using a generalised forest model i.e., clearances were underestimated in evergreen forest, and overestimated in dry-deciduous forest. This suggests that forest type needs to be considered in time series change mapping, especially in heterogeneous forest regions. Our approach builds towards improving large-area monitoring of forest-diverse regions such as Southeast Asia. The findings of this study should also be transferable across optical sensors and are therefore relevant for the future availability of dense time series for the tropics at higherspatial resolutions. en application/pdf https://research.wur.nl/en/publications/mapping-clearances-in-tropical-dry-forests-using-breakpoints-tren 10.3390/rs8080657 https://edepot.wur.nl/389700 Accuracy BFAST Change detection Deforestation Dry deciduous Evergreen Southeast Asia https://creativecommons.org/licenses/by/4.0/ Wageningen University & Research
institution WUR NL
collection DSpace
country Países bajos
countrycode NL
component Bibliográfico
access En linea
databasecode dig-wur-nl
tag biblioteca
region Europa del Oeste
libraryname WUR Library Netherlands
language English
topic Accuracy
BFAST
Change detection
Deforestation
Dry deciduous
Evergreen
Southeast Asia
Accuracy
BFAST
Change detection
Deforestation
Dry deciduous
Evergreen
Southeast Asia
spellingShingle Accuracy
BFAST
Change detection
Deforestation
Dry deciduous
Evergreen
Southeast Asia
Accuracy
BFAST
Change detection
Deforestation
Dry deciduous
Evergreen
Southeast Asia
Grogan, Kenneth
Pflugmacher, Dirk
Hostert, Patrick
Verbesselt, Jan
Fensholt, Rasmus
Mapping Clearances in Tropical Dry Forests Using Breakpoints, Trend, and Seasonal Components from MODIS Time Series: Does Forest Type Matter?
description Tropical environments present a unique challenge for optical time series analysis, primarily owing to fragmented data availability, persistent cloud cover and atmospheric aerosols. Additionally, little is known of whether the performance of time series change detection is affected by diverse forest types found in tropical dry regions. In this paper, we develop a methodology for mapping forest clearing in Southeast Asia using a study region characterised by heterogeneous forest types. Moderate Resolution Imaging Spectroradiometer (MODIS) time series are decomposed using Breaks For Additive Season and Trend (BFAST) and breakpoints, trend, and seasonal components are combined in a binomial probability model to distinguish between cleared and stable forest. We found that the addition of seasonality and trend information improves the change model performance compared to using breakpoints alone. We also demonstrate the value of considering forest type in disturbance mapping in comparison to the more common approach that combines all forest typesinto a single generalised forest class. By taking a generalised forest approach, there is less control over the error distribution in each forest type. Dry-deciduous and evergreen forests are especially sensitive to error imbalances using a generalised forest model i.e., clearances were underestimated in evergreen forest, and overestimated in dry-deciduous forest. This suggests that forest type needs to be considered in time series change mapping, especially in heterogeneous forest regions. Our approach builds towards improving large-area monitoring of forest-diverse regions such as Southeast Asia. The findings of this study should also be transferable across optical sensors and are therefore relevant for the future availability of dense time series for the tropics at higherspatial resolutions.
format Article/Letter to editor
topic_facet Accuracy
BFAST
Change detection
Deforestation
Dry deciduous
Evergreen
Southeast Asia
author Grogan, Kenneth
Pflugmacher, Dirk
Hostert, Patrick
Verbesselt, Jan
Fensholt, Rasmus
author_facet Grogan, Kenneth
Pflugmacher, Dirk
Hostert, Patrick
Verbesselt, Jan
Fensholt, Rasmus
author_sort Grogan, Kenneth
title Mapping Clearances in Tropical Dry Forests Using Breakpoints, Trend, and Seasonal Components from MODIS Time Series: Does Forest Type Matter?
title_short Mapping Clearances in Tropical Dry Forests Using Breakpoints, Trend, and Seasonal Components from MODIS Time Series: Does Forest Type Matter?
title_full Mapping Clearances in Tropical Dry Forests Using Breakpoints, Trend, and Seasonal Components from MODIS Time Series: Does Forest Type Matter?
title_fullStr Mapping Clearances in Tropical Dry Forests Using Breakpoints, Trend, and Seasonal Components from MODIS Time Series: Does Forest Type Matter?
title_full_unstemmed Mapping Clearances in Tropical Dry Forests Using Breakpoints, Trend, and Seasonal Components from MODIS Time Series: Does Forest Type Matter?
title_sort mapping clearances in tropical dry forests using breakpoints, trend, and seasonal components from modis time series: does forest type matter?
url https://research.wur.nl/en/publications/mapping-clearances-in-tropical-dry-forests-using-breakpoints-tren
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AT pflugmacherdirk mappingclearancesintropicaldryforestsusingbreakpointstrendandseasonalcomponentsfrommodistimeseriesdoesforesttypematter
AT hostertpatrick mappingclearancesintropicaldryforestsusingbreakpointstrendandseasonalcomponentsfrommodistimeseriesdoesforesttypematter
AT verbesseltjan mappingclearancesintropicaldryforestsusingbreakpointstrendandseasonalcomponentsfrommodistimeseriesdoesforesttypematter
AT fensholtrasmus mappingclearancesintropicaldryforestsusingbreakpointstrendandseasonalcomponentsfrommodistimeseriesdoesforesttypematter
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