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Registro Completo |
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Biblioteca(s): |
Embrapa Territorial. |
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Data corrente: |
03/10/2011 |
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Data da última atualização: |
03/05/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
LU, D.; LI, G.; BATISTELLA, M.; FREITAS, C. C. |
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Afiliação: |
DENGSHENG LU, INDIANA UNIVERSITY; GUIYING LI, INDIANA UNIVERSITY; MATEUS BATISTELLA, CNPM; CORINA C. FREITAS, INPE. |
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Título: |
Mapping impervious surfaces with the integrated use of Landsat Thematic Mapper and radar data: a case study in an urban-rural landscape in the Brazilian Amazon. |
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Ano de publicação: |
2011 |
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Fonte/Imprenta: |
ISPRS Journal of Photogrammetry and Remote Sensing, v. 66, p. 798-808, 2011. |
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DOI: |
10.1016/j.isprsjprs.2011.08.004 |
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Idioma: |
Português |
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Conteúdo: |
This research explored the integrated use of Landsat Thematic Mapper (TM) and radar (i.e., ALOS PALSAR L-band and RADARSAT-2 C-band) data for mapping impervious surface distribution to examine the roles of radar data with different spatial resolutions and wavelengths. The wavelet-merging technique was used to merge TM and radar data to generate a new dataset. A constrained least-squares solution was used to unmix TM multispectral data and multisensor fusion images to four fraction images (high-albedo, low-albedo, vegetation, and soil). The impervious surface image was then extracted from the high-albedo and low-albedo fraction images. QuickBird imagery was used to develop an impervious surface image for use as reference data to evaluate the results from TM and fusion images. This research indicated that increasing spatial resolution by multisensor fusion improved spatial patterns of impervious surface distribution, but cannot significantly improve the statistical area accuracy. This research also indicated that the fusion image with 10-m spatial resolution was suitable for mapping impervious surface spatial distribution, but TM multispectral image with 30 m was too coarse in a complex urban?rural landscape. On the other hand, this research showed that no significant difference in improving impervious surface mapping performance by using either PALSAR L-band or RADARSAT C-band data with the same spatial resolution when they were used for multi-sensor fusion with the wavelet-based method. MenosThis research explored the integrated use of Landsat Thematic Mapper (TM) and radar (i.e., ALOS PALSAR L-band and RADARSAT-2 C-band) data for mapping impervious surface distribution to examine the roles of radar data with different spatial resolutions and wavelengths. The wavelet-merging technique was used to merge TM and radar data to generate a new dataset. A constrained least-squares solution was used to unmix TM multispectral data and multisensor fusion images to four fraction images (high-albedo, low-albedo, vegetation, and soil). The impervious surface image was then extracted from the high-albedo and low-albedo fraction images. QuickBird imagery was used to develop an impervious surface image for use as reference data to evaluate the results from TM and fusion images. This research indicated that increasing spatial resolution by multisensor fusion improved spatial patterns of impervious surface distribution, but cannot significantly improve the statistical area accuracy. This research also indicated that the fusion image with 10-m spatial resolution was suitable for mapping impervious surface spatial distribution, but TM multispectral image with 30 m was too coarse in a complex urban?rural landscape. On the other hand, this research showed that no significant difference in improving impervious surface mapping performance by using either PALSAR L-band or RADARSAT C-band data with the same spatial resolution when they were used for multi-sensor fusion with the wavelet-b... Mostrar Tudo |
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Palavras-Chave: |
ALOS PALSAR L-band; Impervious sufarce; Landsat TM; RADARSAT-2 C-band; Spectral mixture analysis; Wavelet-merging technique. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/42780/1/Impervious-TM-radar-ISPRS-2011.pdf
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Marc: |
LEADER 02317naa a2200241 a 4500
001 1902116
005 2019-05-03
008 2011 bl uuuu u00u1 u #d
024 7 $a10.1016/j.isprsjprs.2011.08.004$2DOI
100 1 $aLU, D.
245 $aMapping impervious surfaces with the integrated use of Landsat Thematic Mapper and radar data$ba case study in an urban-rural landscape in the Brazilian Amazon.
260 $c2011
520 $aThis research explored the integrated use of Landsat Thematic Mapper (TM) and radar (i.e., ALOS PALSAR L-band and RADARSAT-2 C-band) data for mapping impervious surface distribution to examine the roles of radar data with different spatial resolutions and wavelengths. The wavelet-merging technique was used to merge TM and radar data to generate a new dataset. A constrained least-squares solution was used to unmix TM multispectral data and multisensor fusion images to four fraction images (high-albedo, low-albedo, vegetation, and soil). The impervious surface image was then extracted from the high-albedo and low-albedo fraction images. QuickBird imagery was used to develop an impervious surface image for use as reference data to evaluate the results from TM and fusion images. This research indicated that increasing spatial resolution by multisensor fusion improved spatial patterns of impervious surface distribution, but cannot significantly improve the statistical area accuracy. This research also indicated that the fusion image with 10-m spatial resolution was suitable for mapping impervious surface spatial distribution, but TM multispectral image with 30 m was too coarse in a complex urban?rural landscape. On the other hand, this research showed that no significant difference in improving impervious surface mapping performance by using either PALSAR L-band or RADARSAT C-band data with the same spatial resolution when they were used for multi-sensor fusion with the wavelet-based method.
653 $aALOS PALSAR L-band
653 $aImpervious sufarce
653 $aLandsat TM
653 $aRADARSAT-2 C-band
653 $aSpectral mixture analysis
653 $aWavelet-merging technique
700 1 $aLI, G.
700 1 $aBATISTELLA, M.
700 1 $aFREITAS, C. C.
773 $tISPRS Journal of Photogrammetry and Remote Sensing$gv. 66, p. 798-808, 2011.
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Registro original: |
Embrapa Territorial (CNPM) |
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Biblioteca |
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| Registros recuperados : 39 | |
| 23. |  | 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.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Territorial. |
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| 28. | | 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| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Territorial. |
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| 29. | | 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.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Agricultura Digital. |
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| 30. | | 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.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Territorial. |
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| 31. | | 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.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Territorial. |
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| 33. | | 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.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Meio Ambiente. |
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| 34. | | 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.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 2 |
| Biblioteca(s): Embrapa Territorial. |
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| 35. | | 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.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Unidades Centrais. |
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| 36. | | 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.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Territorial; Embrapa Unidades Centrais. |
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| 37. | | 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.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Territorial. |
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| 38. | | CHEN, Y.; LU, D.; MORAN, E.; BATISTELLA, M.; DUTRA, L. V.; DEL'ARCO SANCHES, I.; SILVA, R. F. B. da; HUANG, J.; LUIZ, A. J. B.; OLIVEIRA, M. A. F. de. Mapping croplands, cropping patterns, and crop types using MODIS time-series data. International Journal of Applied Earth Observation and Geoinformation, v. 69, p. 133-147, July 2018.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Agricultura Digital. |
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| 39. | | CHEN, Y.; LU, D.; MORAN, E.; BATISTELLA, M.; DUTRA, L. V.; SANCHES, I. D. A.; SILVA, R. F. B. da; HUANG, J.; LUIZ, A. J. B.; OLIVEIRA, M. A. F. de. Mapping croplands, cropping patterns, and crop types using MODIS time-series data. International Journal of Applied Earth Observation and Geoinformation, v. 69, p. 133-147, 2018.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Meio Ambiente. |
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| Registros recuperados : 39 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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