This study evaluates the effectiveness of using detailed cellular network signalling data for travel time estimation and route classification. Here, the authors propose a processing pipeline for ...estimating travel times and route classification based on Cell ID and received signal strength (RSS) measurements from a cellular network. The pipeline combines cellular fingerprinting, particle filtering, integrity monitoring, and map matching based on a hidden Markov model (HMM). The method is evaluated using a dataset of 11,000 cellular RSS measurements with corresponding GPS locations for the city of Norrköping, Sweden. The basic fingerprinting method has a CEP-67 location accuracy of 111 m and both particle filtering and integrity monitoring improved the results: 79 and 38 m for particle filtering and particle filtering with integrity monitoring, respectively. The route classification method resulted in a precision of 0.83 and a recall of 0.92, which are clear improvements compared to basic map matching of fingerprinting estimates. This new type of noise-adaptive travel time sampling in combination with an HMM-based route classification shows promising results and can potentially support large-scale estimates of both route choice and travel times using detailed cellular network signalling data in urban areas.
The role of predation in ecological systems has received considerable attention in scientific literature and is one of the most important, yet least understood aspects of carnivore ecology. Knowledge ...of factors that improve our ability to detect predation events using animal telemetry data could be used to develop strategies to reduce time and resources required to obtain reliable kill estimates. Using Global Positioning System telemetry-collars, we investigated 246 bobcat Lynx rufus location clusters to identify white-tailed deer Odocoileus virginianus kill sites in the Upper Peninsula of Michigan, USA, during May-August, 2009-2011. We documented kills of white-tailed deer at 42 location clusters. We used logistic regression and Akaike Information Criterion for small samples to identify factors (i.e. number of locations in cluster, time from cluster formation to investigation, time of day and land cover) that may influence bobcat behaviour and our ability to detect white-tailed deer kill sites. Clusters with more locations and the search of clusters within 14 days after cluster formation increased odds of detecting bobcat kill sites. The best-performing model was 67% accurate overall and identified 34% of kill sites and 75% of non-kill sites. Applying our best-performing model with the optimal cut-off value would result in a twofold increase in the identification of white-tailed deer kill sites reducing time and effort to find a similar number of kill sites without models by half. Identifying factors that improve our ability to identify bobcat kill sites can reduce field effort and search time.
Besides providing habitat to the grizzly bear (Ursus arctos) and other wildlife, the Rocky Mountain foothills of Alberta, Canada hosts considerable mining, seismic oil and gas exploration and ...production, and forest harvesting activities. Worldwide, such human activities influence the configuration and composition of the landscape. We assessed seismic cutline effects on landscape structure and grizzly bear use during early summer of 1999 and 2000. We studied five female and two male bears, which were GPS-collared in the spring following den emergence. The area available to this population was stratified into 49 km^sup 2^ hexagon-shaped sub-landscapes. The scale of this stratification was determined by patterns of bear movement. Fourteen compositional and configurational landscape metrics were calculated within each landscape unit, and bear use points were pooled or 'binned' within each unit. Landscape use was related to landscape metrics using a Generalized Linear Model (GLM). We found that seismic cutline proportion did not explain landscape use by grizzly bears; however secondary effects of cutlines on landscape structure did. Declining use was mainly associated with increasing proportions of closed forest, and increasing variation of inter-patch distances, while use was mainly increasing with increasing mean patch size. An earlier investigation had demonstrated that adding seismic cutlines to grizzly bear habitat caused increases in the variation of inter-patch distances. Since the landscape structure of this grizzly bear population will continue to change as a function of increased levels of resource extraction activities in the near future, it is crucial to further study the detailed meaning of landscape structure at the large and small scale for effective conservation efforts.PUBLICATION ABSTRACT
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