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Registro Completo |
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Biblioteca(s): |
Embrapa Territorial. |
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Data corrente: |
15/09/2014 |
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Data da última atualização: |
15/09/2014 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
LU, D.; LI, G.; VALLADARES, G. S.; BATISTELLA, M. |
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Afiliação: |
DENGSHENG LU, INDIANA UNIVERSITY; G. LI, INDIANA STATE UNIVERSITY; GUSTAVO S. VALLADARES, CNPM; MATEUS BATISTELLA, CNPM. |
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Título: |
Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using rusle, remote sensing and GIS. |
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Ano de publicação: |
2004 |
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Fonte/Imprenta: |
Land Degradation & Development, v. 15, p. 499-512, 2004. |
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DOI: |
10.1002/ldr.634 |
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Idioma: |
Português |
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Conteúdo: |
This article discusses research in which the authors applied the Revised Universal Soil Loss Equation (RUSLE), remote sensing, and geographical information system (GIS) to the maping of soil erosion risk in Brazilian Amazonia. Soil map and soil survey data were used to develop the soil erodibility factor (K), and a digital elevation model image was used to generate the topographic factor (LS). The cover-management factor (C) was developed based on vegetation, shade, and soil fraction images derived from spectral mixture analysis of a Landsat Enhanced Thematic Mapper Plus image. Assuming the same climatic conditions and no support practice in the study area, the rainfall?runoff erosivity (R) and the support practice (P) factors were not used. The majority of the study area has K values of less than 0.2, LS values of less than 2.5, and C values of less than 0.25. A soil erosion risk map with five classes (very low, low, medium, medium-high, and high) was produced based on the simplified RUSLE within the GIS environment, and was linked to land use and land cover (LULC) image to explore relationships between soil erosion risk and LULC distribution. The results indicate that most successional and mature forests are in very low and low erosion risk areas, while agroforestry and pasture are usually associated with medium to high risk areas. This research implies that remote sensing and GIS provide promising tools for evaluating and mapping soil erosion risk in Amazonia. |
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Palavras-Chave: |
Brazilian Amazonia; GIS; RUSLE; Soil erosion risk. |
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Thesaurus Nal: |
Remote sensing. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/108416/1/4024.pdf
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Marc: |
LEADER 02146naa a2200229 a 4500
001 1994981
005 2014-09-15
008 2004 bl uuuu u00u1 u #d
024 7 $a10.1002/ldr.634$2DOI
100 1 $aLU, D.
245 $aMapping soil erosion risk in Rondônia, Brazilian Amazonia$busing rusle, remote sensing and GIS.$h[electronic resource]
260 $c2004
520 $aThis article discusses research in which the authors applied the Revised Universal Soil Loss Equation (RUSLE), remote sensing, and geographical information system (GIS) to the maping of soil erosion risk in Brazilian Amazonia. Soil map and soil survey data were used to develop the soil erodibility factor (K), and a digital elevation model image was used to generate the topographic factor (LS). The cover-management factor (C) was developed based on vegetation, shade, and soil fraction images derived from spectral mixture analysis of a Landsat Enhanced Thematic Mapper Plus image. Assuming the same climatic conditions and no support practice in the study area, the rainfall?runoff erosivity (R) and the support practice (P) factors were not used. The majority of the study area has K values of less than 0.2, LS values of less than 2.5, and C values of less than 0.25. A soil erosion risk map with five classes (very low, low, medium, medium-high, and high) was produced based on the simplified RUSLE within the GIS environment, and was linked to land use and land cover (LULC) image to explore relationships between soil erosion risk and LULC distribution. The results indicate that most successional and mature forests are in very low and low erosion risk areas, while agroforestry and pasture are usually associated with medium to high risk areas. This research implies that remote sensing and GIS provide promising tools for evaluating and mapping soil erosion risk in Amazonia.
650 $aRemote sensing
653 $aBrazilian Amazonia
653 $aGIS
653 $aRUSLE
653 $aSoil erosion risk
700 1 $aLI, G.
700 1 $aVALLADARES, G. S.
700 1 $aBATISTELLA, M.
773 $tLand Degradation & Development$gv. 15, p. 499-512, 2004.
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Registro original: |
Embrapa Territorial (CNPM) |
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| Registros recuperados : 10 | |
| 7. |  | 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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| 8. | | 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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| 9. | | 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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| 10. | | AN, F.; LI, G.; LI, Q. X.; LI, K.; CARVALHO, L. J. C. B.; OU, W.; CHEN, S. The comparatively proteomic analysis in response to cold stress in cassava plantlets. Plant Molecular Biology Reporter, v. 34, n. 6, p. 1095-1110, 2016.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| Registros recuperados : 10 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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