DOI: 10.1016/j.jag.2014.01.001
Scopus记录号: 2-s2.0-84897539789
论文题名: Empirical models for estimating the suspended sediment concentration in Amazonian white water rivers using Landsat 5/TM
作者: Montanher O ; C ; , Novo E ; M ; L ; M ; , Barbosa C ; C ; F ; , Rennó C ; D ; , Silva T ; S ; F
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 29, 期: 1 起始页码: 67
结束页码: 77
语种: 英语
英文关键词: Band ratios
; Fluvial sediments
; Geology of the amazon
; Multiple regressions
; Spectral bands
; Top of atmosphere reflectance
Scopus关键词: alluvial deposit
; database
; empirical analysis
; error analysis
; Landsat thematic mapper
; multiple regression
; numerical model
; reflectance
; remote sensing
; sediment yield
; suspended sediment
; top of atmosphere
; water quality
; Amazonia
英文摘要: Suspended sediment yield is a very important environmental indicator within Amazonian fluvial systems, especially for rivers dominated by inorganic particles, referred to as white water rivers. For vast portions of Amazonian rivers, suspended sediment concentration (SSC) is measured infrequently or not at all. However, remote sensing techniques have been used to estimate water quality parameters worldwide, from which data for suspended matter is the most successfully retrieved. This paper presents empirical models for SSC retrieval in Amazonian white water rivers using reflectance data derived from Landsat 5/TM. The models use multiple regression for both the entire dataset (global model, N = 504) and for five segmented datasets (regional models) defined by general geological features of drainage basins. The models use VNIR bands, band ratios, and the SWIR band 5 as input. For the global model, the adjusted R2 is 0.76, while the adjusted R2 values for regional models vary from 0.77 to 0.89, all significant (p-value < 0.0001). The regional models are subject to the leave-one-out cross validation technique, which presents robust results. The findings show that both the average error of estimation and the standard deviation increase as the SSC range increases. Regional models were more accurate when compared with the global model, suggesting changes in optical proprieties of water sampled at different sampling stations. Results confirm the potential for the estimation of SSC from Landsat/TM historical series data for the 1980s and 1990s, for which the in situ database is scarce. Such estimates supplement the SSC temporal series, providing a more comprehensive SSC temporal series which may show environmental dynamics yet unknown. © 2013 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79778
Appears in Collections: 气候变化事实与影响
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作者单位: Divisão de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, 12201-970, São José dos Campos, SP, Brazil; Departamento de Tecnologia, Universidade Estadual de Maringá, 87506-370, Umuarama, PR, Brazil; Departamento de Geografia, Instituto de Geociências e Ciências Exatas (IGCE), Universidade Estadual Paulista (UNESP), Rio Claro, SP, Brazil
Recommended Citation:
Montanher O,C,, Novo E,et al. Empirical models for estimating the suspended sediment concentration in Amazonian white water rivers using Landsat 5/TM[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,29(1)