Critical Separation Versus Effective Sweep Width: Bridging the Old and New Search-and-Rescue Worlds.

INTRODUCTION: "Critical separation" is a simple method for spacing searchers intended to produce a predictable probability of detection (POD). A more precise method, based on effective sweep width (W), has been adopted only slowly. Accurate PODs are critical in planning priorities in future operational periods. Therefore, it would be useful to know what POD a critical separation determination actually produces. METHODS: Detection ranges (Rd) were measured on high- and low-visibility adult mannequins (stuffed Tyvek suits of varying colors) and a red helmet detected by 6 searcher volunteers. Conversion factors previously described in the literature were used to convert Rds into predicted Ws and the previously described logit model to convert Ws into PODs. RESULTS: The Rds were 26±6 m (mean±SD) for the high-visibility mannequin, 15±5 m for the low-visibility mannequin, and 24±6 m for the helmet used in the critical separation determination. The predicted Ws were 47±15 m, 16±8 m, and 42±14 m, respectively. Critical separation would therefore result in predicted PODs of 67±17% or 32±16% for nonresponsive adults in high- versus low-visibility clothing. CONCLUSIONS: Critical separation is a simple, quick way to array searchers in the field. The current study suggests that the value of critical separation in producing the 50% target POD will depend on the whether the search object used for the critical separation determination has a similar detectability/W to the actual target of the search effort. Still, the results from a critical separation determination may offer more predictability and reliability than the common practice of POD estimation by team leaders.

Deriving Effective Sweep Width for Air-scent Dog Teams.

OBJECTIVE: We sought to obtain the first effective sweep widths (ESWs) ever measured for an air-scent search dog unit to compare their performance to historical data from human searchers and to initially test the validity of atmospheric convection as a limiting factor in air-scent search. METHODS: We used GPS tracks and waypoints to measure lateral hit and miss distances for the dog teams during blinded, randomized training tasks during a 6-year period, calculating ESW using the crossover method. During the tasks we collected weather data for determining convection. We used nonparametric statistics and least-square regression to compare the dog ESW data with historical human data and weather conditions. RESULTS: The mean value of ESW for the 4 teams under all conditions was 95 m (95% CI, 44 to 145). The dog teams' performance was statistically superior to human visual searchers in detecting search subjects in low-visibility colors, but not subjects in high-visibility colors. A nonparametric correlation test of ESW vs convection gave P<.05, suggesting that convection may be an operationally significant factor in air-scent dog performance. CONCLUSIONS: The ESW methodology is applicable to air-scent dog teams, potentially allowing search managers to make decisions in applying resources operationally, as well as improving accuracy of planning calculations. In addition, the methods described appear to be capable, given more widely representative data, of making valid statistical comparisons between different search modalities and weather and other factors.

Use of the visual range of detection to estimate effective sweep width for land search and rescue based on 10 detection experiments in North America.

OBJECTIVE: Standard-of-practice search management requires that the probability of detection (POD) be determined for each search resource after a task. To calculate the POD, a detection index (W) is obtained by field experiments. Because of the complexities of the land environment, search planners need a way to estimate the value of W without conducting formal experiments. We demonstrate a robust empirical correlation between detection range (Rd) and W, and argue that Rd may reliably be used as a quick field estimate for W. METHODS: We obtained the average maximum detection range (AMDR), Rd, and W values from 10 detection experiments conducted throughout North America. We measured the correlation between Rd and W, and tested whether the apparent relationship between W and Rd was statistically significant. RESULTS: On average we found W ≈ 1.645 × Rd with a strong correlation (R(2) = .827). The high-visibility class had W ≈ 1.773 × Rd (also R(2) = .867), the medium-visibility class had W ≈ 1.556 × Rd (R(2) = .560), and the low-visibility had a correction factor of 1.135 (R(2) = .319) for Rd to W. Using analysis of variance and post hoc testing, only the high- and low-visibility classes were significantly different from each other (P < .01). We also found a high correlation between the AMDR and Rd (R(2) = .9974). CONCLUSIONS: Although additional experiments are required for the medium- and low-visibility search objects and in the dry-domain ecoregion, we suggest search planners use the following correction factors to convert field-measured Rd to an estimate of the effective sweep width (W): high-visibility W = 1.8 × Rd; medium-visibility W = 1.6 × Rd; and low-visibility W = 1.1 × Rd.

Effectors of visual search efficacy on the Allegheny Plateau.

BACKGROUND: Although lost-person search managers try to direct search efforts quantitatively, it has historically been difficult to quantify the efficacy of search efforts accurately. The effective-sweep-width (ESW) methodology represents an avenue for accomplishing this goal but has not yet been widely disseminated among practitioners. METHODS: We obtained ESW values in the summer and winter in a typical disturbed-forest environment in southwest Pennsylvania. We used nonparametric statistics to compare individual ESW values for two types of search objects detected by 18 summer and 20 winter searchers, cumulating the P values for similar comparisons and correcting for false discovery via a stepped method. RESULTS: We detected robust differences (all at P <.001) associated with search object color, season, and vegetation thickness. In contrast with earlier studies, we found a significant correlation between individual searchers' ESWs for different search objects and different types of vegetation (P <.001). We also found that adolescent searchers had significantly lower ESW values than adults (P = .002). Apparently significant positive correlations between time spent on the course or field search experience and ESW disappeared when teens were excluded from the comparisons. CONCLUSIONS: These results (the first comparison of seasonal ESW effects in identical terrain) represent the first statistical demonstration that the ESW methodology provides more than enough resolution to answer fundamental questions about the efficacy of visual search for lost persons by human searchers. They also add support to the imperative of operationally disseminating these methods among search-and-rescue practitioners, and offer some initial operational lessons for search managers.