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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34P/3P789DP
Repositorysid.inpe.br/mtc-m21b/2017/06.29.19.11
Last Update2017:06.29.19.11.50 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m21b/2017/06.29.19.11.50
Metadata Last Update2018:06.04.02.27.33 (UTC) administrator
DOI10.3390/rs9040381
ISSN2072-4292
Citation KeyFengLuMoDuCaOl:2017:ExSpDi
TitleExamining spatial distribution and dynamic change of urban Llnd covers in the Brazilian Amazon using multitemporal multisensor high spatial resolution satellite imagery
Year2017
MonthApr.
Access Date2024, Apr. 23
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size5701 KiB
2. Context
Author1 Feng, Yunyun
2 Lu, Dengsheng
3 Moran, Emilio F.
4 Dutra, Luciano Vieira
5 Calvi, Miquéias Freitas
6 Oliveira, Maria Antonia Falcão de
Resume Identifier1
2
3
4 8JMKD3MGP5W/3C9JHMA
Group1
2
3
4 DIDPI-CGOBT-INPE-MCTIC-GOV-BR
5
6 CGOBT-CGOBT-INPE-MCTIC-GOV-BR
Affiliation1 Zhejiang Agriculture and Forestry University
2 Zhejiang Agriculture and Forestry University
3 Michigan State University
4 Instituto Nacional de Pesquisas Espaciais (INPE)
5 Universidade Federal do Pará (UFPA)
6 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 fengyyfm@163.com
2 luds@zafu.edu.cn
3 moranef@msu.edu
4 dutra@dpi.inpe.br
5 mcalvi@ufpa.br
6 marian.florestal@gmail.com
JournalRemote Sensing
Volume9
Number4
Secondary MarkB3_GEOGRAFIA B3_ENGENHARIAS_I B4_GEOCIÊNCIAS B4_CIÊNCIAS_AMBIENTAIS B5_CIÊNCIAS_AGRÁRIAS_I
History (UTC)2017-06-29 19:11:50 :: simone -> administrator ::
2017-06-29 19:11:51 :: administrator -> simone :: 2017
2017-06-29 19:13:04 :: simone -> administrator :: 2017
2018-06-04 02:27:33 :: administrator -> simone :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
Keywordsurban land-cover change
high spatial resolution satellite images
multisensor data
change detection technique
moist tropical region
Belo Monte hydroelectric dam construction
AbstractThe construction of the Belo Monte hydroelectric dam began in 2011, resulting in rapidly increased population from less than 80,000 persons before 2010 to more than 150,000 persons in 2012 in Altamira, Para State, Brazil. This rapid urbanization has produced many problems in urban planning and management, as well as challenging environmental conditions, requiring monitoring of urban land-cover change at high temporal and spatial resolutions. However, the frequent cloud cover in the moist tropical region is a big problem, impeding the acquisition of cloud-free optical sensor data. Thanks to the availability of different kinds of high spatial resolution satellite images in recent decades, RapidEye imagery in 2011 and 2012, Pleiades imagery in 2013 and 2014, SPOT 6 imagery in 2015, and CBERS imagery in 2016 with spatial resolutions from 0.5 m to 10 m were collected for this research. Because of the difference in spectral and spatial resolutions among these satellite images, directly conducting urban land-cover change using conventional change detection techniques, such as image differencing and principal component analysis, was not feasible. Therefore, a hybrid approach was proposed based on integration of spectral and spatial features to classify the high spatial resolution satellite images into six land-cover classes: impervious surface area (ISA), bare soil, building demolition, water, pasture, and forest/plantation. A post-classification comparison approach was then used to detect urban land-cover change annually for the periods between 2011 and 2016. The focus was on the analysis of ISA expansion, the dynamic change between pasture and bare soil, and the changes in forest/plantation. This study indicates that the hybrid approach can effectively extract six land-cover types with overall accuracy of over 90%. ISA increased continuously through conversion from pasture and bare soil. The Belo Monte dam construction resulted in building demolition in 2015 in low-lying areas along the rivers and an increase in water bodies in 2016. Because of the dam construction, forest/plantation and pasture decreased much faster, while ISA and water increased much faster in 2011-2016 than they had between 1991 and 2011. About 50% of the increased annual deforestation area can be attributed to the dam construction between 2011 and 2016. The spatial patterns of annual urban land-cover distribution and rates of dynamic change provided important data sources for making better decisions for urban management and planning in this city and others experiencing such explosive demographic change.
AreaSRE
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGP3W34P/3P789DP
zipped data URLhttp://urlib.net/zip/8JMKD3MGP3W34P/3P789DP
Languageen
Target Filefeng_examining.pdf
User Groupsimone
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Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3EQCCU5
8JMKD3MGPCW/3EU2H28
Citing Item Listsid.inpe.br/mtc-m21/2012/07.13.14.53.50 1
sid.inpe.br/bibdigital/2013/09.09.15.05 1
sid.inpe.br/bibdigital/2013/10.01.23.43 1
DisseminationWEBSCI; PORTALCAPES; MGA; COMPENDEX; SCOPUS.
Host Collectionsid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notes
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