<?xml version="1.0" encoding="utf-8" standalone="no"?>
<!DOCTYPE article SYSTEM "http://www.hydrol-earth-syst-sci.net/inc/hess/copernicus.dtd">
<article language="en">
	<journal>
		<journal_title>Hydrology and Earth System Sciences</journal_title>
		<journal_url>www.hydrol-earth-syst-sci.net</journal_url>
		<issn>1027-5606</issn>
		<eissn>1607-7938</eissn>
		<volume_number>10</volume_number>
		<issue_number>5</issue_number>
		<publication_year>2006</publication_year>
	</journal>
	<doi>10.5194/hess-10-663-2006</doi>
	<article_url>http://www.hydrol-earth-syst-sci.net/10/663/2006/</article_url>
	<abstract_html>http://www.hydrol-earth-syst-sci.net/10/663/2006/hess-10-663-2006.html</abstract_html>
	<fulltext_pdf>http://www.hydrol-earth-syst-sci.net/10/663/2006/hess-10-663-2006.pdf</fulltext_pdf>
	<start_page>663</start_page>
	<end_page>677</end_page>
	<publication_date>2006-09-27</publication_date>
	<article_title content_type="html">A new method for determination of most likely landslide initiation points and the evaluation of digital terrain model scale in terrain stability mapping</article_title>
	<authors>
		<author numeration="1" affiliations="1">
			<name>P. Tarolli</name>
			<email>paolo.tarolli@unipd.it</email>
		</author>
		<author numeration="2" affiliations="2">
			<name>D. G. Tarboton</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Department of Land and Agroforest Environments, AGRIPOLIS, University of Padova, 35020 Legnaro, Padova, Italy</affiliation>
		<affiliation numeration="2" content_type="html">Department of Civil and Environmental Engineering, Utah State University, Logan, Utah, USA</affiliation>
	</affiliations>
	<abstract content_type="html">This paper introduces a new approach for determining the most likely
initiation points for landslides from potential instability mapped using a
terrain stability model. This approach identifies the location with critical
stability index from a terrain stability model on each downslope path from
ridge to valley. Any measure of terrain stability may be used with this
approach, which here is illustrated using results from SINMAP, and from
simply taking slope as an index of potential instability. The relative
density of most likely landslide initiation points within and outside mapped
landslide scars provides a way to evaluate the effectiveness of a terrain
stability measure, even when mapped landslide scars include run out zones,
rather than just initiation locations. This relative density was used to
evaluate the utility of high resolution terrain data derived from airborne
laser altimetry (LIDAR) for a small basin located in the Northeastern Region
of Italy. Digital Terrain Models were derived from the LIDAR data for a
range of grid cell sizes (from 2 to 50 m). We found appreciable differences
between the density of most likely landslide initiation points within and
outside mapped landslides with ratios as large as three or more with the
highest ratios for a digital terrain model grid cell size of 10 m. This leads
to two conclusions: (1) The relative density from a most likely landslide
initiation point approach is useful for quantifying the effectiveness of a
terrain stability map when mapped landslides do not or can not differentiate
between initiation, runout, and depositional areas; and (2) in this study
area, where landslides occurred in complexes that were sometimes more than
100 m wide, a digital terrain model scale of 10 m is optimal. Digital
terrain model scales larger than 10 m result in loss of resolution that
degrades the results, while for digital terrain model scales smaller than 10
m the physical processes responsible for triggering landslides are obscured
by smaller scale terrain variability.</abstract>
	<references>
		<reference numeration="1" content_type="text"> Ackermann, F.: Airborne laser scanning &amp;ndash; present status and future expectations, IS-PRN Journal of Photogrammetry and Remote Sensing, 54, 64&amp;ndash;67, 1999. </reference>
		<reference numeration="2" content_type="text"> Barling, R. D., Moore, I. D., and Grayson, R. B.: A Quasi-Dynamic Wetness Index for Characterizing the Spatial Distribution of Zones of Surface Saturation and Soil Water Content, Water Resour. Res., 30(4), 1029&amp;ndash;1044, 1994. </reference>
		<reference numeration="3" content_type="text"> Begueria, S.: Validation and evaluation of predictive models in hazard assessment and risk management, Natural Hazards, 37, 315&amp;ndash;329, 2006. </reference>
		<reference numeration="4" content_type="text"> Beven, K. J., Lamb, R., Quinn, P. F., Romanowicz, R., and Freer, J.: TOPMODEL, in: Computer Models of Watershed Hydrology, edited by: Singh, V. P., Water Resour. Publ., 627&amp;ndash;668, 1995. </reference>
		<reference numeration="5" content_type="text"> Borga, M., Dalla Fontana, G., and Cazorzi, F.: Analysis of topographic and climatic control on rainfall-triggered shallow landsliding using a quasi-dynamic wetness index, J. Hydrol., 268(1&amp;ndash;4), 56&amp;ndash;71, 2002. </reference>
		<reference numeration="6" content_type="text"> Borga, M., Dalla Fontana, G., Gregoretti, C., and Marchi, L.: Assessment of shallow landsliding by using a physically based model of hillslope stability, Hydrol. Processes, 16(14), 2833&amp;ndash;2851, 2002. </reference>
		<reference numeration="7" content_type="text"> Brenning, A.: Spatial Prediction Models for Landslide Hazards: Review, Comparison and Evaluation, Nat. Hazards Earth Syst. Sci., 5, 853&amp;ndash;862, 2005. </reference>
		<reference numeration="8" content_type="text"> Briese, C.: Breakline Modelling from Airborne Laser Scanner Data, PHD Thesis, Institute of Photogrammetry and Remote Sensing, Vienna University of Technology, 2004. </reference>
		<reference numeration="9" content_type="text"> Chinnayakanahalli, K.: An Objective Method for the Intercomparison of Terrain Stability Models and Incorporation of Parameter Uncertainty, MS Thesis, Civil and Environmental Engineering, Utah State University, 2004. </reference>
		<reference numeration="10" content_type="text"> Chung, C. J. and Fabbri, A. G.: Validation of spatial prediction models for landslide hazard mapping&quot;, Natural Hazards, 30, 451&amp;ndash;472, 2003. </reference>
		<reference numeration="11" content_type="text"> Chung, C. J. and Fabbri, A. G.: Systematic procedures of landslide-hazard mapping for risk assessment using spatial prediction models, in: Landslide Hazard and Risk, edited by: Glade, T., Anderson, M. G., and Crozier, M. J., John Wiley &amp; Sons, Ltd., Chichester, England, 139&amp;ndash;174, 2005. </reference>
		<reference numeration="12" content_type="text"> Dietrich, W. E., Bellugi, D., and de Asua, R. R.: Validation of Shallow Landslide Model, Shalstab, for Forest Management, in: Land Use and Watersheds: Human Influence on Hydrology and Geomorphology in Urban and Forest Areas, edited by: Wigmosta, M. S. and Burges, S. J., Water Sci. Appl. 2, Amer. Geoph. Union, 195&amp;ndash;227, 2001. </reference>
		<reference numeration="13" content_type="text"> Dietrich, W. E., Wilson, C. J., Montgomery, D. R., McKean J., and Bauer, R.: Erosion Thresholds and Land Surface Morphology, Geology, 20, 675&amp;ndash;679, 1992. </reference>
		<reference numeration="14" content_type="text"> Freer, J., McDonnell, J. J. Beven, K. J., Peters, N. E., Burns, D. A., Hooper, R. P., Aulenbach, B., and Kendall, C.: The Role of Bedrock Topography on Subsurface Storm Flow, Water Resour. Res., 38(12), 1269, doi:10.1029/2001WR000872, 2002. </reference>
		<reference numeration="15" content_type="text"> Hammond, C., Hall, D., Miller, S., and Swetik, P.: Level I Stability Analysis (LISA) Documentation for Version 2.0, General Technical Report INT-285, USDA Forest Service Intermountain Research Station, 1992. </reference>
		<reference numeration="16" content_type="text"> Hutchinson, M. F.: Calculation of hydrologically sound digital elevation models, Third International Symposium on Spatial Data Handling, Sydney, Columbus, Ohio, International Geographical Union, 1988. </reference>
		<reference numeration="17" content_type="text"> Hutchinson, M. F.: A new procedure for gridding elevation and stream line data with automatic removal of spurious pits, J. Hydrol., 106, 211&amp;ndash;232, 1989. </reference>
		<reference numeration="18" content_type="text"> Iverson, R. M.: Landslide Triggering by Rain Infiltration, Water Resour. Res., 36(7), 1897&amp;ndash;1910, 2000. </reference>
		<reference numeration="19" content_type="text"> Kraus, K. and Pfeifer, N.: Advanced DTM generation from LIDAR data, International Archives of Photogrammetry and Remote Sensing, XXXIV-3/W4, 23&amp;ndash;35, 2001. </reference>
		<reference numeration="20" content_type="text"> McKean, J. and Roering, J.: Objective landslide detection and surface morphology mapping using high-resolution airborne laser altimetry, Geomorphology, 57, 331&amp;ndash;351, 2004. </reference>
		<reference numeration="21" content_type="text"> Montgomery, D. R. and Dietrich, W. E.: A physically based model for the topographic control on shallow landsliding, Water Resour. Res., 30(4), 1153&amp;ndash;1171, 1994. </reference>
		<reference numeration="22" content_type="text"> Pack, R. T., Tarboton, D. G., and Goodwin, C. N.: The SINMAP Approach to Terrain Stability Mapping, 8th Congress of the International Association of Engineering Geology, Vancouver, British Columbia, Canada, 1998. </reference>
		<reference numeration="23" content_type="text"> Tarboton, D. G.: A new method for the determination of flow directions and upslope areas in grid digital elevation models, Water Resour. Res., 33, 309&amp;ndash;319, 1997. </reference>
		<reference numeration="24" content_type="text"> Wu, W. and Sidle, R. C.: A Distributed Slope Stability Model for Steep Forested Watersheds, Water Resour. Res., 31(8), 2097&amp;ndash;2110, 1995.  </reference>
	</references>
</article>

