27 October 2017 Using an integrated remote sensing approach for identification of bedrock and alluvium along the Front Range mountains, Colorado
Author Affiliations +
J. of Applied Remote Sensing, 11(4), 046009 (2017). doi:10.1117/1.JRS.11.046009
Abstract
The Colorado front range (CFR) mountains have a history of significant debris flows. For instance, flash floods in September 2013 triggered over 1138 debris flows in the CFR, leading to eight fatalities and causing damage to buildings, highways, railroads, and infrastructure. Following this event, the United States Geological Survey (USGS) studied these debris flows with the intention of modeling debris flow susceptibility in this region. They identified a problem that the preliminary susceptibility map, before correction, included areas of exposed bedrock as regions that were modeled to have high susceptibility, even though those regions should have been low susceptibility. The objective of this research is to develop and execute an integrated sequential land cover classification (iSLCC) remote sensing approach to discriminate bedrock outcrop from colluvium and, hence, constrain the USGS susceptibility modeling. The approach integrates multispectral, hyperspectral, and radar methods to discriminate colluvium from bedrock outcrops over a study area of nine 7½ min quadrangles. Calibrating against six smaller field study areas that span different geologic formations and ecoregions, a map of land cover, including exposed bedrock outcrops, was produced over a study area that encompasses portions of the St. Vrain and Big Thompson watersheds. The resulting map was compared with the results from traditional land cover classification methods. The iSLCC approach yielded the best overall results and the highest observed agreement (observed accuracy).
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Joshua C. Stewart, Wendy Zhou, Paul M. Santi, "Using an integrated remote sensing approach for identification of bedrock and alluvium along the Front Range mountains, Colorado," Journal of Applied Remote Sensing 11(4), 046009 (27 October 2017). http://dx.doi.org/10.1117/1.JRS.11.046009 Submission: Received 20 May 2017; Accepted 19 September 2017
Submission: Received 20 May 2017; Accepted 19 September 2017
JOURNAL ARTICLE
21 PAGES


SHARE
Back to Top