Estimates of selective logging impacts in tropical forest canopy cover using RapidEye imagery and field data

Pinagé, ER; Matricardi, EAT; Leal, FA; Pedlowski, MA

Estimates of selective logging impacts in tropical forest canopy cover using RapidEye imagery and field data

Pinagé, ER

Matricardi, EAT Leal, FA Pedlowski, MA

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Publication Type:: Journal Article
Citation:: IForest, 2016, 9 (JUNE2016), pp. 461 - 468
Issue Date:: 2016-06-01

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Field	Value	Language
dc.contributor.author	Pinagé, ER https://orcid.org/0000-0003-3714-8175	en_US
dc.contributor.author	Matricardi, EAT	en_US
dc.contributor.author	Leal, FA	en_US
dc.contributor.author	Pedlowski, MA	en_US
dc.date.issued	2016-06-01	en_US
dc.identifier.citation	IForest, 2016, 9 (JUNE2016), pp. 461 - 468	en_US
dc.identifier.uri	http://hdl.handle.net/10453/85295
dc.description.abstract	© SISEF. Selective logging is one of the leading causes of forest degradation in the Brazilian Amazon region. The Brazilian Federal government has adopted a forest concession policy as a strategy to mitigate impacts of selective logging and regulate operations of the tropical timber industry in Brazil. This study used fractional forest coverage derived from satellite imagery and field data to assess forest degradation in two selectively logged study sites within the Jamari National Forest, a protected area located in the western Brazilian state of Rondônia. Initially, we estimated the fractional coverage from vegetation indices using RapidEye imagery and compared to gap fraction data derived from hemispherical photos acquired in the field. Subsequently, we estimated the impacts of different types of selective logging activities (log decks, primary and secondary roads, tree fall gaps, and skid trails) on forest cover using the fractional coverage dataset. The NDVI showed the highest R2 (0.56), indicating that 56% of the sample variation in fractional coverage derived from ground measurements can be explained by fractional coverage derived from the NDVI model. Our results also showed that the intensity of canopy impacts may vary according to the selective logging activity, ranging from skid trails to log decks which had the lightest and the heaviest canopy impacts, respectively.	en_US
dc.relation.ispartof	IForest	en_US
dc.relation.isbasedon	10.3832/ifor1534-008	en_US
dc.title	Estimates of selective logging impacts in tropical forest canopy cover using RapidEye imagery and field data	en_US
dc.type	Journal Article
utslib.citation.volume	JUNE2016	en_US
utslib.citation.volume	9	en_US
utslib.for	0909 Geomatic Engineering	en_US
utslib.for	0601 Biochemistry and Cell Biology	en_US
utslib.for	0705 Forestry Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access
pubs.issue	JUNE2016	en_US
pubs.publication-status	Published	en_US
pubs.volume	9	en_US

Abstract:

© SISEF. Selective logging is one of the leading causes of forest degradation in the Brazilian Amazon region. The Brazilian Federal government has adopted a forest concession policy as a strategy to mitigate impacts of selective logging and regulate operations of the tropical timber industry in Brazil. This study used fractional forest coverage derived from satellite imagery and field data to assess forest degradation in two selectively logged study sites within the Jamari National Forest, a protected area located in the western Brazilian state of Rondônia. Initially, we estimated the fractional coverage from vegetation indices using RapidEye imagery and compared to gap fraction data derived from hemispherical photos acquired in the field. Subsequently, we estimated the impacts of different types of selective logging activities (log decks, primary and secondary roads, tree fall gaps, and skid trails) on forest cover using the fractional coverage dataset. The NDVI showed the highest R2 (0.56), indicating that 56% of the sample variation in fractional coverage derived from ground measurements can be explained by fractional coverage derived from the NDVI model. Our results also showed that the intensity of canopy impacts may vary according to the selective logging activity, ranging from skid trails to log decks which had the lightest and the heaviest canopy impacts, respectively.

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http://hdl.handle.net/10453/85295