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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. | | 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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| 33. | | 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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| 34. | | 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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| 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. | | 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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| 39. | | 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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| 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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Registro Completo
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Biblioteca(s): |
Embrapa Territorial. |
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Data corrente: |
17/03/2008 |
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Data da última atualização: |
22/08/2014 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
LU, D.; BATISTELLA, M.; ALVES, D. HETRICK, S.; MORAN, E. |
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Afiliação: |
Dengsheng Lu ( Auburn University); Mateus Batistellla ( Embrapa Monitoramento por Satélite); Diógenes Alves ( INPE) Scott Hetrick (Indiana University); Emílio Moran ( Indiana University). |
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Título: |
Mapping of Fractional Forest Cover in Rondonia, Brazil with a Combination of Terra MODIS and Landsat TM Images. |
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Ano de publicação: |
2007 |
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Fonte/Imprenta: |
In: LBA_ECO Science Team Meeting, 11., 2007, Salvador. Resumos... Salvador: LBA, 2007. |
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Páginas: |
p. 31-32. |
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Idioma: |
Inglês |
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Conteúdo: |
High deforstation rates in Amazonia have motivated considerable efforts to monitor land-cover changes based on satellite images and image porcesssing techniques. Most commonly, MODIS images are used to provide low-cost region-wide coverage at nearly monthly frequencies, but they offer offer only coarse resolution, Lsndsat TM has been used in a majority of studies for nearly two decades, but these, but these data are expensive, and provide, at best, yearly coverage because of clouds. Here, a new approach to estimate forest change is proposed based on the integration of TM and MODIS images. TM images are processed using a hybrid approach including spectral mixture, expert rules, and usupervised classification, to generate a reference forest image. Three fraction images are derived from MODIS surface reflectance data; expert rules are used to generate a refined vegetation image and regression is then develoned between the TM-derived forest and MODIS derived vegetation data to assess the fractional forest area. This approach was initially applied to 2004 MODIS and TM images from Rondônia, and the regression model was transferred to 2000 and 2006 MODIS images. A similar exercise was made in Pará state for the estimation of forest area in 2005. Compared to TM-derived reference data in Rondônia, the system error for the MODIS-derived forest areas was 1.56% and 4.19% for 2004 and 2000 images, respectively. Compared to INPE prodes data, the error for total forest area in Rondônia in 2004 a 2000 are -0.97% and 0.81%, respectively. The major advantage of this approach is that coarse spatial resolution images from MODIS and AVHRR can be used to estimate fractional forest cover for large areas in a short time, requiring limited work, but yielding accuracies comparable to Landsat TM-derived results. MenosHigh deforstation rates in Amazonia have motivated considerable efforts to monitor land-cover changes based on satellite images and image porcesssing techniques. Most commonly, MODIS images are used to provide low-cost region-wide coverage at nearly monthly frequencies, but they offer offer only coarse resolution, Lsndsat TM has been used in a majority of studies for nearly two decades, but these, but these data are expensive, and provide, at best, yearly coverage because of clouds. Here, a new approach to estimate forest change is proposed based on the integration of TM and MODIS images. TM images are processed using a hybrid approach including spectral mixture, expert rules, and usupervised classification, to generate a reference forest image. Three fraction images are derived from MODIS surface reflectance data; expert rules are used to generate a refined vegetation image and regression is then develoned between the TM-derived forest and MODIS derived vegetation data to assess the fractional forest area. This approach was initially applied to 2004 MODIS and TM images from Rondônia, and the regression model was transferred to 2000 and 2006 MODIS images. A similar exercise was made in Pará state for the estimation of forest area in 2005. Compared to TM-derived reference data in Rondônia, the system error for the MODIS-derived forest areas was 1.56% and 4.19% for 2004 and 2000 images, respectively. Compared to INPE prodes data, the error for total forest area in Rondônia in ... Mostrar Tudo |
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Palavras-Chave: |
forest; MODIS images; Rondônia. |
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Thesagro: |
Terra. |
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Thesaurus NAL: |
Amazonia. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/107111/1/2063.pdf
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Marc: |
LEADER 02458nam a2200217 a 4500
001 1017602
005 2014-08-22
008 2007 bl uuuu u00u1 u #d
100 1 $aLU, D.
245 $aMapping of Fractional Forest Cover in Rondonia, Brazil with a Combination of Terra MODIS and Landsat TM Images.
260 $aIn: LBA_ECO Science Team Meeting, 11., 2007, Salvador. Resumos... Salvador: LBA$c2007
300 $ap. 31-32.
520 $aHigh deforstation rates in Amazonia have motivated considerable efforts to monitor land-cover changes based on satellite images and image porcesssing techniques. Most commonly, MODIS images are used to provide low-cost region-wide coverage at nearly monthly frequencies, but they offer offer only coarse resolution, Lsndsat TM has been used in a majority of studies for nearly two decades, but these, but these data are expensive, and provide, at best, yearly coverage because of clouds. Here, a new approach to estimate forest change is proposed based on the integration of TM and MODIS images. TM images are processed using a hybrid approach including spectral mixture, expert rules, and usupervised classification, to generate a reference forest image. Three fraction images are derived from MODIS surface reflectance data; expert rules are used to generate a refined vegetation image and regression is then develoned between the TM-derived forest and MODIS derived vegetation data to assess the fractional forest area. This approach was initially applied to 2004 MODIS and TM images from Rondônia, and the regression model was transferred to 2000 and 2006 MODIS images. A similar exercise was made in Pará state for the estimation of forest area in 2005. Compared to TM-derived reference data in Rondônia, the system error for the MODIS-derived forest areas was 1.56% and 4.19% for 2004 and 2000 images, respectively. Compared to INPE prodes data, the error for total forest area in Rondônia in 2004 a 2000 are -0.97% and 0.81%, respectively. The major advantage of this approach is that coarse spatial resolution images from MODIS and AVHRR can be used to estimate fractional forest cover for large areas in a short time, requiring limited work, but yielding accuracies comparable to Landsat TM-derived results.
650 $aAmazonia
650 $aTerra
653 $aforest
653 $aMODIS images
653 $aRondônia
700 1 $aBATISTELLA, M.
700 1 $aALVES, D. HETRICK, S.
700 1 $aMORAN, E.
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