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| Registros recuperados : 42 | |
| 26. |  | LU, D.; BATISTELLA, M.; ALVES, D. HETRICK, S.; MORAN, E. Mapping of Fractional Forest Cover in Rondonia, Brazil with a Combination of Terra MODIS and Landsat TM Images. In: LBA_ECO Science Team Meeting, 11., 2007, Salvador. Resumos... Salvador: LBA, 2007. p. 31-32.| Biblioteca(s): Embrapa Territorial. |
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| 31. | | LU, D.; BATISTELLA, M.; MORAN, E. F.; MIRANDA, E. E. D. A comparative study of Terra ASTER, Landsat TM, and SPT HRG data for land cover classification in the Brazilian Amazon. In: WORLD MULTI-CONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS (WMSCI2005), 9th, 2005, Orlando - Florida. Proceedings... Orlando: International Institute of Informatics and Systemics (IIS), 2005. v. 8, p. 411-416. folhas avulsas| Biblioteca(s): Embrapa Territorial. |
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| 32. | | LI, G.; LU, D.; MORAN, E.; CALVI, M. F.; DUTRA, L. V.; BATISTELLA, M. Examining deforestation and agropasture dynamics along the Brazilian TransAmazon Highway using multitemporal Landsat imagery. GIScience & Remote Sensing, v. 56, n. 2, p. 161-183, 2019.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 33. | | LU, D.; BATISTELLA, M.; MORAN, E.; HETRICK, S.; ALVES, D.; BRONDIZIO, E. Fractional forest cover mapping in the Brazilian Amazon with a combination of MODIS and TM images. International Journal of Remote Sensing, v. 32, n. 22, p. 7131-7149, 2011.| Biblioteca(s): Embrapa Territorial. |
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| 35. | | BATISTELLA, M.; ALVES, D.; LU, D.; MORAN, E. F.; BRONDIZIO, E. S.; D'ANTONA, A. From the Landscape to the region: scaling up approaches in human and physical dimensions of land-use and land-cover change in the Amazon. In: LBA-ECO SCIENCE TEAM MEETING, 10., 2006. Brasília, DF. Abstracts... Brasília: LBA-ECO, 2006. 1 p.| Biblioteca(s): Embrapa Territorial. |
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| 36. | | CAK, A. D.; MORAN, E. F.; FIGUEIREDO, R. de O.; LU, D.; LI, G.; HETRICK, S. Urbanization and small household agricultural land use choices in the Brazilian Amazon and the role for the water chemistry of small streams. Journal of Land Use Science, Abingdon, v. 11, n. 2, p. 203-221, 2016.| Biblioteca(s): Embrapa Meio Ambiente. |
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| 37. | | LU, D.; CHEN, Q.; WANG, G.; MORAN, E.; BATISTELLA, M.; ZHANG, M.; LAURIN, G. V.; SAAH, D. Aboveground forest biomass estimation with Landsat and LiDAR data and uncertainty analysis of the estimates. International Journal of Forestry Research, v. 2012. p. 16, 2012 16 p.| Biblioteca(s): Embrapa Territorial. |
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| 38. | | FENG, Y.; LU, D.; CHEN, Q.; KELLER, M.; MORAN, E.; SANTOS, M. N. dos S.; BOLFE, E. L.; BATISTELLA, M. Examining effective use of data source and modeling algorithms for improving biomass estimation in a moist tropical forest of the brazilian Amazon. International Journal of Digital Earth, London, 2017.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 39. | | LU, D.; BATISTELLA, M.; LI, G.; MORAN, E.; HETRICK, S.; FREITAS, C. DA C.; SANT'ANNA, S. J. Land use/cover classification in the Brazilian Amazon using satellite images. Pesquisa Agropecuária Brasileira, Brasilia, DF, v. 47, n. 9, p. 1185-1208, set. 2012. p. 1185-1208.| Biblioteca(s): Embrapa Territorial; Embrapa Unidades Centrais. |
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| 40. | | CHEN, Q.; LU, D.; KELLER, M.; SANTOS, M. N. DOS; BOLFE, E. L.; FENG, Y.; WANG, C. Modeling and Mapping Agroforestry Aboveground Biomass in the Brazilian Amazon Using Airborne Lidar Data. Remote Sensing, v. 8, n. 1, p. 1-17, 2015.| Biblioteca(s): Embrapa Territorial. |
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| Registros recuperados : 42 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
07/01/2020 |
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Data da última atualização: |
04/02/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
LI, G.; LU, D.; MORAN, E.; CALVI, M. F.; DUTRA, L. V.; BATISTELLA, M. |
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Afiliação: |
GUIYING LI, Fujian Normal University; DENGSHENG LU, Fujian Normal University, Michigan StateUniversity; EMILIO MORAN, Michigan State University; MIQUÉIAS FREITAS CALVI, UFPA; LUCIANO VIEIRA DUTRA, INPE; MATEUS BATISTELLA, CNPTIA. |
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Título: |
Examining deforestation and agropasture dynamics along the Brazilian TransAmazon Highway using multitemporal Landsat imagery. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
GIScience & Remote Sensing, v. 56, n. 2, p. 161-183, 2019. |
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DOI: |
https://doi.org/10.1080/15481603.2018.1497438 |
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Idioma: |
Inglês |
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Conteúdo: |
This research aims to understand the difference of major land-cover change results caused in various time periods and to examine the impacts of human-induced factors on land-cover changes along the TransAmazon Highway region. The Landsat Thematic Mapper and Operational Land Imager data from 2011, 2014, and 2017 and our previous land-cover classification results in 1991, 2000, and 2008 were used to examine land-cover dynamics. A classification system consisting of five land-cover classes ? primary forest (PF), secondary forest (SF), agropasture (AP), urban area, and water ? were chosen. The hierarchical-based classification method was used to generate land-cover classification results, and the post-classification comparison approach was used to produce detailed ?from-to? conversions for each detection period. The emphasis was on deforestation of PF, dynamic change of SF and AP, and urbanization over time. The impacts of human-induced factors such as population and economic conditions on urban expansion, AP expansion, and deforestation were examined. This research indicated that selection of a suitable time period was critical for effectively detecting land-cover changes; that is, too long time period (i.e., 9 years) cannot accurately capture some land-cover changes such as the AP and SF in this research. Although deforestation ? the conversion from PF to SF and AP ? accounted for a large proportion of land-cover changes, the changes between SF and AP became moreproportion important than PF conversion, and required a short time period (i.e., 3 years here) for effectively reflecting their dynamics. Human-induced factors play important roles in deforestation, dynamic changes between AP and SF, and urbanization. MenosThis research aims to understand the difference of major land-cover change results caused in various time periods and to examine the impacts of human-induced factors on land-cover changes along the TransAmazon Highway region. The Landsat Thematic Mapper and Operational Land Imager data from 2011, 2014, and 2017 and our previous land-cover classification results in 1991, 2000, and 2008 were used to examine land-cover dynamics. A classification system consisting of five land-cover classes ? primary forest (PF), secondary forest (SF), agropasture (AP), urban area, and water ? were chosen. The hierarchical-based classification method was used to generate land-cover classification results, and the post-classification comparison approach was used to produce detailed ?from-to? conversions for each detection period. The emphasis was on deforestation of PF, dynamic change of SF and AP, and urbanization over time. The impacts of human-induced factors such as population and economic conditions on urban expansion, AP expansion, and deforestation were examined. This research indicated that selection of a suitable time period was critical for effectively detecting land-cover changes; that is, too long time period (i.e., 9 years) cannot accurately capture some land-cover changes such as the AP and SF in this research. Although deforestation ? the conversion from PF to SF and AP ? accounted for a large proportion of land-cover changes, the changes between SF and AP became moreproportion imp... Mostrar Tudo |
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Palavras-Chave: |
Agropasture expansion; Cobertura da terra; Human-induced factors; Multitemporal Landsat imagery; Secondary forest; TransAmazon; Transamazônica. |
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Thesagro: |
Desmatamento. |
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Thesaurus NAL: |
Deforestation; Land cover. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02700naa a2200313 a 4500
001 2118287
005 2020-02-04
008 2019 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1080/15481603.2018.1497438$2DOI
100 1 $aLI, G.
245 $aExamining deforestation and agropasture dynamics along the Brazilian TransAmazon Highway using multitemporal Landsat imagery.$h[electronic resource]
260 $c2019
520 $aThis research aims to understand the difference of major land-cover change results caused in various time periods and to examine the impacts of human-induced factors on land-cover changes along the TransAmazon Highway region. The Landsat Thematic Mapper and Operational Land Imager data from 2011, 2014, and 2017 and our previous land-cover classification results in 1991, 2000, and 2008 were used to examine land-cover dynamics. A classification system consisting of five land-cover classes ? primary forest (PF), secondary forest (SF), agropasture (AP), urban area, and water ? were chosen. The hierarchical-based classification method was used to generate land-cover classification results, and the post-classification comparison approach was used to produce detailed ?from-to? conversions for each detection period. The emphasis was on deforestation of PF, dynamic change of SF and AP, and urbanization over time. The impacts of human-induced factors such as population and economic conditions on urban expansion, AP expansion, and deforestation were examined. This research indicated that selection of a suitable time period was critical for effectively detecting land-cover changes; that is, too long time period (i.e., 9 years) cannot accurately capture some land-cover changes such as the AP and SF in this research. Although deforestation ? the conversion from PF to SF and AP ? accounted for a large proportion of land-cover changes, the changes between SF and AP became moreproportion important than PF conversion, and required a short time period (i.e., 3 years here) for effectively reflecting their dynamics. Human-induced factors play important roles in deforestation, dynamic changes between AP and SF, and urbanization.
650 $aDeforestation
650 $aLand cover
650 $aDesmatamento
653 $aAgropasture expansion
653 $aCobertura da terra
653 $aHuman-induced factors
653 $aMultitemporal Landsat imagery
653 $aSecondary forest
653 $aTransAmazon
653 $aTransamazônica
700 1 $aLU, D.
700 1 $aMORAN, E.
700 1 $aCALVI, M. F.
700 1 $aDUTRA, L. V.
700 1 $aBATISTELLA, M.
773 $tGIScience & Remote Sensing$gv. 56, n. 2, p. 161-183, 2019.
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