Landslides are an important process for sediment delivery to mountain streams [Hovius et al., 2000; Kelsey, 1980]. In forested terrain, timber harvest and road building can alter landslide characteristics [Montgomery et al., 2000; Swanson and Dyrness, 1975], with potentially adverse effects on aquatic ecosystems. Degradation of aquatic habitat associated with increased landsliding [Hartman et al., 1996; Hicks et al., 1991] is a factor implicated in reducing, and even extirpating, culturally and economically important populations of Pacific salmon and trout [Nehlsen et al., 1991]. This has motivated interest in examining effects of land management on landslide processes [Collins and Pess, 1997; Dunne, 1998] and spurred federal and state agencies to assess and monitor landslide occurrences [Bush et al., 1997; Robison et al., 1999] with consequent regulatory constraints to limit human influences on landsliding [Oregon Department of Forestry, 2006; U.S. Department of Agriculture and U.S. Department of the Interior, 1994; Washington Department of Natural Resources, 2005].
 Although any type of landslide can affect stream channels, here we focus on landslides that are likely to initiate debris flows, specifically rainfall-triggered translational landsliding of shallow soils [Iverson et al., 1997]. Debris flows are of particular importance because they can travel long distances to and through stream channels [Benda and Cundy, 1990]. By creating a debris flow, a small landslide can affect stream channels far downslope, both by scouring accumulated soil and organic debris from steep, low-order channels [May and Gresswell, 2003] and by depositing the scoured material into larger, fish-bearing streams [May and Gresswell, 2004]. Landslide-triggered debris flows thus play two important and related roles in river environments. One is creation of persistent geomorphic features: their deposits create distinct valley floor fan and terrace landforms [Benda, 1990; Miller and Benda, 2000; Wohl and Pearthree, 1991]. The other is dynamic: they link forest disturbances, which can increase landslide susceptibility [Schmidt et al., 2001], to downslope stream and riparian disturbances [Cenderelli and Kite, 1998; Gomi et al., 2002; Miller, 1990; Nakamura et al., 2000]. Together, these persistent and transient debris flow influences affect the spatial and temporal distribution of habitat and biota in mountain river networks [Benda et al., 2004; Lamberti et al., 1991; Montgomery, 1999; Pabst and Spies, 2001; Rice et al., 2001] and both must be recognized to anticipate effects of land management in these aquatic ecosystems [Reeves et al., 1995].
 A first step in efforts to discern land management effects on debris flow influences to regional ecosystems is identification of sites susceptible to debris flow initiation and assessment of forest disturbance on the degree of susceptibility. Topographic attributes (i.e., slope gradient and convergence) are recognized as primary factors controlling susceptibility of shallow soils to landsliding [Chen and Jan, 2003; Hack and Goodlett, 1960; Niemann and Howes, 1991; Reneau et al., 1990]. Hillslope topography thus sets the stage for the spatial distribution of debris flow effects. Overprinted on the topographic template is the modulating influence of forest cover, acting through root reinforcement [Burroughs and Thomas, 1977; Schmidt et al., 2001] and perhaps also through smoothing of rainfall intensity [Keim and Skaugset, 2003], on the initiation of shallow landsliding [May, 2002; Montgomery et al., 2000; Sidle and Ochiai, 2006; Swanson and Dyrness, 1975].
 Spatial variability in landslide susceptibility is influenced by topographic and forest cover characteristics at a relatively fine spatial resolution (of order 102 m2); however, land management and conservation planning decisions for many stream-dwelling species, particularly salmon and trout, can benefit from knowledge of landslide susceptibility across large spatial extents (of order 105 km2). Spatial variability in landslide susceptibility is also affected by variability in numerous factors other than topography and forest cover [Dunne, 1998]. These include variability in site conditions, such as soil depth and geotechnical properties [Hammond et al., 1992; Wu, 1996] and spatiotemporal variability in landslide triggers, such as rainfall intensity [Mark and Newman, 1988]. Data are typically lacking to explicitly address these other pertinent factors in high-resolution, regionally applicable models of landslide susceptibility. Therefore a modeling approach that minimizes sensitivity of results to spatial variability in these factors while capitalizing on widely available 10-m digital elevation models (DEMs) [Gesch et al., 2002] and forest cover mapping from satellite imagery could be of great value.
 One approach is to empirically associate mapped landslide initiation sites with topographic and forest cover characteristics [e.g., Coe et al., 2004; May, 2002]. Field surveys and interpretation of aerial photography are common sources of landslide mapping. However, each source presents problems for use in regional modeling of landslide susceptibility. Inventories from field surveys can reasonably include only relatively small areas, yielding landslide counts or densities by forest cover class that may vary substantially from site to site [Robison et al., 1999]. In contrast, inventories from aerial photographs may include a larger area to discern regional trends in the relative density of landslides between forest cover classes, but small landslides are more visible in unforested areas on aerial photographs, which introduces bias in landslide counts between forest cover classes [Brardinoni et al., 2003; Pyles and Froehlich, 1987]. Weaknesses in each type of inventory can be overcome by combining information from the two sources. The proportion of small landslides missed in an air photo inventory can be estimated from landslide size distributions from a field inventory. Consequently, the air photo inventory can be used to evaluate variations in landslide density as a function of the area over which it is measured and to estimate uncertainty in measured values.
 In this paper, we describe methods to identify and characterize initiation sites of rainfall-triggered translational landslides in shallow soils and then demonstrate these methods for areas in the Oregon Coast Range, USA. Our objectives are to (1) characterize topographic influences on landslide density (in terms of number per unit area) using regionally available, high-resolution (10-m) DEMs; (2) specify methods to estimate, and potentially reduce, bias between different forest cover classes in counts of landslide initiation points mapped on aerial photographs; (3) determine ratios in densities of landslide initiation points between forest cover classes when corrected for bias from variable topography and air photo interpretation; and (4) evaluate variability in densities of landslide initiation points between different forest cover classes measured over a range of spatial extents. We also use these techniques to account for effects of forest roads on landslide density. Although results from this study are based on observations that span only a portion of the Oregon Coast Range, they provide the means to extrapolate a spatially distributed estimate of landslide susceptibility across the entire region. Additionally, the methods are readily applied with similar data elsewhere and the results offer insights for interpreting and designing other studies.