DOI: 10.1016/j.jag.2013.08.010
Scopus记录号: 2-s2.0-84896917800
论文题名: Surface roughness estimation from RADARSAT-2 data in a High Arctic environment
作者: Collingwood A ; , Treitz P ; , Charbonneau F
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 27, 期: PARTA 起始页码: 70
结束页码: 80
语种: 英语
英文关键词: Artificial neural network
; Polarimetry
; Radar
; SAR
; Soil moisture
; Surface roughness
Scopus关键词: artificial neural network
; estimation method
; RADARSAT
; satellite data
; soil moisture
; soil surface
; surface roughness
; synthetic aperture radar
; vegetation cover
; Canada
; Canadian Arctic
英文摘要: Synthetic aperture radar (SAR) data are often used to determine the physical properties of the soil surface, such as soil moisture and surface roughness. Although these analyses are commonly applied in agricultural environments, there has been limited application in more natural environments, particularly at high latitudes. For the research reported here, an artificial neural network (ANN) is developed to model surface roughness in the Canadian High Arctic. This research represents the first phase of the overall goal of developing an operational methodology for estimating surface roughness, vegetation cover and soil moisture using SAR and limited field measurements. Multiple incidence angle data and fully polarimetric data from RADARSAT-2 are combined with long and short profile in situ surface roughness measurements from 134 sample locations located across two distinct High Arctic study sites. Multiple ANN models were developed using various backscatter, textural, and polarimetric variables. The ANN models exhibited a moderate to strong agreement to field-measured surface roughness. This study demonstrates that operational surface roughness modeling in the Canadian High Arctic is feasible with RADARSAT-2 polarimetric data. © 2013 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79771
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Geography, Queen's University, Kingston, ON K7L 3N6, Canada; Canada Centre for Remote Sensing, Natural Resources Canada, 588 Booth Street, Ottawa, ON K1A 0Y7, Canada
Recommended Citation:
Collingwood A,, Treitz P,, Charbonneau F. Surface roughness estimation from RADARSAT-2 data in a High Arctic environment[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,27(PARTA)