Data/hora: 23/09/2024 10:59:52

Biblioteca(s): 	Embrapa Unidades Centrais.	
Data corrente: 	13/06/2014	
Data da última atualização: 	29/05/2017	
Autoria: 	CARVALHO, D. F. de; DURIGON, V. L.; ANTUNES, M. A. H.; ALMEIDA, W. S. de; OLIVEIRA, P. T. S.	
Título: 	Predicting soil erosion using Rusle and NDVI time series from TM Landsat 5.	
Ano de publicação: 	2014	
Fonte/Imprenta: 	Pesquisa Agropecuária Brasileira, Brasília, DF, v. 49, n. 3, p. 215-224, mar. 2014.	
Idioma: 	Inglês	
Notas: 	Título em português: Predição da erosão do solo com uso da Rusle e séries  temporais de NDVI do Landsat 5 TM.	
Conteúdo: 	The objective of this work was to evaluate the seasonal variation of soil cover and rainfall erosivity, and their influences on the revised universal soil loss equation (Rusle), in order to estimate watershed soil losses in a temporal scale. Twenty&#8209;two TM Landsat 5 images from 1986 to 2009 were used to estimate soil use and management factor (C factor). A corresponding rainfall erosivity factor (R factor) was considered for each image, and the other factors were obtained using the standard Rusle method. Estimated soil losses were grouped into classes and ranged from 0.13 Mg ha&#8209;1 on May 24, 2009 (dry season) to 62.0 Mg ha&#8209;1 on March 11, 2007 (rainy season). In these dates, maximum losses in the watershed were 2.2 and 781.5 Mg ha&#8209;1, respectively. Mean annual soil loss in the watershed was 109.5 Mg ha&#8209;1, but the central area, with a loss of nearly 300.0 Mg ha&#8209;1, was characterized as a site of high water&#8209;erosion risk. The use of C factor obtained from remote sensing data, associated to corresponding R factor, was fundamental to evaluate the soil erosion estimated by the Rusle in different seasons, unlike of other studies which keep these factors constant throughout time	
Palavras-Chave: 	C factor; Erosividade; Fator C; Índice de vegetação; Perda de solo; Rainfall erosivity; Soil loss.	
Thesagro: 	Sensoriamento remoto.	
Thesaurus Nal: 	Remote sensing; vegetation index.	
Categoria do assunto: 	--	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/item/103653/1/Predicting-soil-erosion-using.pdf	
Registro original: 	Embrapa Unidades Centrais (AI-SEDE)	
Exemplares: 	AI-SEDE - (56244-1) - UPE - AP - PP - 630.72081 - P474 -  - DIS
CNPS-UEPR - (2926-1) - ADD - AP - PP - 631.45 - C331p - 2017.03482 - DIS