00978563

Component

https://doi.org/10.3141/1868-12

http://scholar.google.com...nnis&publication_year=2004

Conventional approaches to solve slope failure problems involve deterministic and probabilistic models to calculate the factor of safety for slopes. These models usually require a large amount of field and laboratory data on soil properties and slope geometry. This requirement makes the determination of conventional factors of safety highly unrealistic if required over large areas, unless some techniques are used to direct investigative efforts to those areas with higher potential for failure. An efficient screening methodology involves creating a hazard zonation map in which regions are classified according to varying instability potential. A database of slope failure details and the power of a geographic information system (GIS) were used to analyze digital data for various causative factors of slope instability to assess the reliability of current landslide prediction methods in northwest Arkansas. A hazard zonation model was created through statistical weighting techniques from remotely sensed imagery, publicly available spatial data, and slope failure data. All of this information was visualized and analyzed by using a GIS. The model's general applicability was tested on another area with similar geoenvironmental conditions with good results.

This paper appears in Transportation Research Record No. 1868, Soil Mechanics 2004.

00978551

English

p. 113-123

2004

Transportation Research Record

0309094623

Figures (9) ; Photos (1) ; References (15) ; Tables (1)

Classification; Geographic information systems; Imagery; Landslides; Slope failure; Slope stability; Spatial analysis; Statistical analysis; Weighting

Hazard zonation model

Arkansas

Data and Information Technology; Geotechnology; Highways; I42: Soil Mechanics

TRIS, TRB, ATRI

Sep 27 2004 12:00AM

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