Data/hora: 13/06/2024 08:12:15

Biblioteca(s): 	Embrapa Territorial.	
Data corrente: 	15/09/2014	
Data da última atualização: 	15/09/2014	
Autoria: 	LU, D.; LI, G.; VALLADARES, G. S.; BATISTELLA, M.	
Afiliação: 	DENGSHENG LU, INDIANA UNIVERSITY; G. LI, INDIANA STATE UNIVERSITY; GUSTAVO S. VALLADARES, CNPM; MATEUS BATISTELLA, CNPM.	
Título: 	Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using rusle, remote sensing and GIS.	
Ano de publicação: 	2004	
Fonte/Imprenta: 	Land Degradation & Development, v. 15, p. 499-512, 2004.	
DOI: 	10.1002/ldr.634	
Idioma: 	Português	
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.	
Palavras-Chave: 	Brazilian Amazonia; GIS; RUSLE; Soil erosion risk.	
Thesaurus Nal: 	Remote sensing.	
Categoria do assunto: 	--	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/item/108416/1/4024.pdf	
Registro original: 	Embrapa Territorial (CNPM)	
Exemplares: 	CNPM - (4024-1) - UPC - AP - DD - 04/006 - AP - 2004.006 - DIS