Adapting a global stratified random sample for regional estimation of forest cover change derived from satellite imagery

Stehman, S; Hansen, M; Broich, M; Potapov, P

Adapting a global stratified random sample for regional estimation of forest cover change derived from satellite imagery

Stehman, S Hansen, M Broich, M Potapov, P

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Publisher:: Elsevier Inc.
Publication Type:: Journal Article
Citation:: Remote Sensing of Environment, 2011, 115 pp. 650 - 658
Issue Date:: 2011-01

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Field	Value	Language
dc.contributor.author	Stehman, S	en_US
dc.contributor.author	Hansen, M	en_US
dc.contributor.author	Broich, M	en_US
dc.contributor.author	Potapov, P	en_US
dc.date.issued	2011-01	en_US
dc.identifier.citation	Remote Sensing of Environment, 2011, 115 pp. 650 - 658	en_US
dc.identifier.issn	0034-4257	en_US
dc.identifier.uri	http://hdl.handle.net/10453/26083
dc.description.abstract	A desirable feature of a global sampling design for estimating forest cover change based on satellite imagery is the ability to adapt the design to obtain precise regional estimates, where a region may be a country, state, province, or conservation area.	en_US
dc.publisher	Elsevier Inc.	en_US
dc.relation.ispartof	Remote Sensing of Environment	en_US
dc.relation.isbasedon	10.1016/j.rse.2010.10.009	en_US
dc.subject.classification	Geological & Geomatics Engineering	en_US
dc.title	Adapting a global stratified random sample for regional estimation of forest cover change derived from satellite imagery	en_US
dc.type	Journal Article
utslib.citation.volume	115	en_US
utslib.for	0909 Geomatic Engineering	en_US
utslib.for	0406 Physical Geography and Environmental Geoscience	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
utslib.copyright.status	closed_access
pubs.consider-herdc	false	en_US
pubs.volume	115	en_US

Abstract:

A desirable feature of a global sampling design for estimating forest cover change based on satellite imagery is the ability to adapt the design to obtain precise regional estimates, where a region may be a country, state, province, or conservation area.

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http://hdl.handle.net/10453/26083