1. Identity statement | |
Reference Type | Journal Article |
Site | mtc-m21d.sid.inpe.br |
Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
Identifier | 8JMKD3MGP3W34T/49FEQUS |
Repository | sid.inpe.br/mtc-m21d/2023/07.18.11.37 |
Last Update | 2023:07.18.11.37.11 (UTC) simone |
Metadata Repository | sid.inpe.br/mtc-m21d/2023/07.18.11.37.11 |
Metadata Last Update | 2024:01.02.17.16.44 (UTC) administrator |
DOI | 10.3390/rs15123102 |
ISSN | 2072-4292 |
Citation Key | SantosPinhPáezAmar:2023:IdUrSo |
Title | Identifying Urban and Socio-Environmental Patterns of Brazilian Amazonian Cities by Remote Sensing and Machine Learning ![](http://mtc-m21d.sid.inpe.br/col/dpi.inpe.br/banon/2000/01.23.20.24/doc/externalLink.gif) |
Year | 2023 |
Month | June |
Access Date | 2024, June 26 |
Type of Work | journal article |
Secondary Type | PRE PI |
Number of Files | 1 |
Size | 23338 KiB |
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2. Context | |
Author | 1 Santos, Bruno Dias dos 2 Pinho, Carolina Moutinho Duque de 3 Páez, Antonio 4 Amaral, Silvana |
Resume Identifier | 1 2 3 4 8JMKD3MGP5W/3C9JJ8Q |
ORCID | 1 0000-0002-6748-2038 2 0000-0002-7054-4463 3 0000-0001-6912-9919 4 0000-0003-4314-7291 |
Group | 1 SER-SRE-DIPGR-INPE-MCTI-GOV-BR 2 3 4 DIOTG-CGCT-INPE-MCTI-GOV-BR |
Affiliation | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 Universidade Federal do ABC (UFABC) 3 McMaster University 4 Instituto Nacional de Pesquisas Espaciais (INPE) |
Author e-Mail Address | 1 bruno.santos@inpe.br 2 carolina.pinho@ufabc.edu.br 3 paezha@mcmaster.ca 4 silvana.amaral@inpe.br |
Journal | Remote Sensing |
Volume | 15 |
Number | 12 |
Pages | e3102 |
Secondary Mark | B3_GEOGRAFIA B3_ENGENHARIAS_I B4_GEOCIÊNCIAS B4_CIÊNCIAS_AMBIENTAIS B5_CIÊNCIAS_AGRÁRIAS_I |
History (UTC) | 2023-07-18 11:37:11 :: simone -> administrator :: 2023-07-18 11:37:11 :: administrator -> simone :: 2023 2023-07-18 11:37:40 :: simone -> administrator :: 2023 2024-01-02 17:16:44 :: administrator -> simone :: 2023 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Content Type | External Contribution |
Version Type | publisher |
Keywords | amazon unsupervised classification urban morphology urban pattern urban remote sensing |
Abstract | Identifying urban patterns in the cities in the Brazilian Amazon can help to understand the impact of human actions on the environment, to protect local cultures, and secure the cultural heritage of the region. The objective of this study is to produce a classification of intra-urban patterns in Amazonian cities. Concretely, we produce a set of Urban and Socio-Environmental Patterns (USEPs) in the cities of Santarém and Cametá in Pará, Brazilian Amazon. The contributions of this study are as follows: (1) we use a reproducible research framework based on remote sensing data and machine learning techniques; (2) we integrate spatial data from various sources into a cellular grid, separating the variables into environmental, urban morphological, and socioeconomic dimensions; (3) we generate variables specific to the Amazonian context; and (4) we validate these variables by means of a field visit to Cametá and comparison with patterns described in other works. Machine learning-based clustering is useful to identify seven urban patterns in Santarém and eight urban patterns in Cametá. The urban patterns are semantically explainable and are consistent with the existing scientific literature. The paper provides reproducible and open research that uses only open software and publicly available data sources, making the data product and code available for modification and further contributions to spatial data science analysis. |
Area | SRE |
Arrangement 1 | urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Identifying Urban and... |
Arrangement 2 | urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > Identifying Urban and... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | |
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4. Conditions of access and use | |
data URL | http://mtc-m21d.sid.inpe.br/ibi/8JMKD3MGP3W34T/49FEQUS |
zipped data URL | http://mtc-m21d.sid.inpe.br/zip/8JMKD3MGP3W34T/49FEQUS |
Language | en |
Target File | remotesensing-15-03102.pdf |
User Group | simone |
Reader Group | administrator simone |
Visibility | shown |
Archiving Policy | allowpublisher allowfinaldraft |
Update Permission | not transferred |
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5. Allied materials | |
Next Higher Units | 8JMKD3MGPCW/3F3NU5S 8JMKD3MGPCW/46KUATE |
Citing Item List | sid.inpe.br/bibdigital/2022/04.03.22.23 8 sid.inpe.br/bibdigital/2013/10.18.22.34 8 sid.inpe.br/mtc-m21/2012/07.13.15.00.22 1 |
Dissemination | WEBSCI; PORTALCAPES; MGA; COMPENDEX; SCOPUS. |
Host Collection | urlib.net/www/2021/06.04.03.40 |
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6. Notes | |
Empty Fields | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark mirrorrepository nextedition notes parameterlist parentrepositories previousedition previouslowerunit progress project readpermission rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url |
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7. Description control | |
e-Mail (login) | simone |
update | |
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