Perpendicular distance sampling (PDS) has emerged as a compelling alternative to line intersect sampling (LIS) for the inventory of forest fuels and other downed woody materials (DWM), particularly where the aggregate volume of DWM is of primary interest. This article develops a selection protocol and design-unbiased estimators for a new probability proportional-to-volume sampling strategy, termed line intersect distance sampling (LIDS). LIDS combines the distance sampling protocol of PDS with the transect sampling protocol of LIS and provides unbiased estimates of aggregate DWM volume from counts of selected logs or log fragments. Simulations indicate that LIDS along multidirectional (e.g., Y-shaped) transects should perform similarly to PDS in terms of sampling error; however, it remains unclear how LIDS and PDS compare with LIS, especially when interest is attached to multiple DWM population parameters. It is argued that LIDS will be most useful in reducing implementation errors, particularly detection errors, relative to PDS under limited visibility field conditions.