Occupancy

About: Occupancy is a research topic. Over the lifetime, 2757 publications have been published within this topic receiving 68288 citations.

Cross-Space Building Occupancy Modeling by Contextual Information Based Learning

Abstract: Research on building occupancy modeling is becoming increasingly important and prevalent, as occupancy is closely related to building energy efficiency, lighting control, security monitoring, emergency evacuation, and rescue operations. Building occupancy is time-sequenced occupancy changes that represent how occupants occupy a building, including both occupant presence and occupant number. Extensive research has been carried out to model building occupancy based on ambient sensing. However, occupancy models reported in previous work are mostly used to detect and estimate the occupancy in the same spaces, where the models are trained, and the generalizability of existing occupancy models to different spaces has not been explored. In general, collecting precise and continuous occupancy data for each space for training can be time consuming and intrusive. In most cases, it might not be realistic to have access to actual occupancy for all of the spaces in a building, thus it is difficult to establish an individual model for each space and improve large-scale occupancy awareness at the building level. We present a systematic framework for cross-space occupancy modeling through non-intrusive ambient sensing and relationship learning, by which the model was trained in one space and then applied to other geometrically similar spaces. Six rooms in two buildings were selected to validate the effectiveness of the framework. It was found that daily F-measure ranged from 0.71 to 0.94 with the mean of 0.80, and daily RMSE ranged from 0.42 to 1.72 with the mean of 1.23 for all classes of occupancy. Daily occupied/unoccupied detection accuracy ranged from 0.79 to 0.99 with the mean of 0.91; and the daily number estimation accuracy ranged from 0.63 to 0.78 with the mean of 0.71, when only the occupied periods were considered. The results showed that the F-measure and daily RMSE had an approximately negative linear relationship while the daily occupied/unoccupied detection accuracy had an approximately positive logarithmic relationship with the daily number estimation accuracy. Three potential influential factors on cross-modeling performance were also investigated. It was found that the level of real-time occupancy variation, the degree of long-term occupancy difference between spaces, and the operation of HVAC systems had negatively logarithmic, linear, and logistic relations with the daily cross-space occupancy modeling accuracies, respectively.

Changing habitat use associated with distributional shifts of wintering raptors

Abstract: There is widespread evidence that multiple drivers of global change, such as habitat degradation, invasive species, and climate change, are influencing wildlife. Understanding how these drivers interact with and affect species may be difficult because outcomes depend on the magnitude and duration of environmental change and the life history of the organism. In addition, various environmental drivers may be evaluated and managed at different spatial scales. We used a historical dataset from 1991 to 1994 and current information from 2010 to 2012 to examine whether occupancy patterns of wintering raptors were consistent with regional changes in distribution or habitat conditions within a local management unit, the Morley Nelson Snake River Birds of Prey National Conservation Area (NCA). We predicted that if local populations reflected regional shifts, then rates of raptor occupancy within the NCA would be higher compared to historical estimates and birds would use different habitats compared to historical use. Alternatively, if local populations were determined by habitat conditions, then we predicted that occupancy rate of raptors within the NCA would be lower compared to historical estimates and current habitat use would be consistent with historical use. Results support the hypothesis that northward distributional shifts influenced wintering raptor populations in southwest Idaho to a greater extent than local habitat conditions. Wintering raptors had higher occupancy rates in 2010–2012 compared to 1991–1994, whereas invasive grasses have increased and native shrubs have decreased suggesting that habitat suitability for raptors has declined over time. On the species level, changes in habitat use were associated with greater increases in occupancy rates in 2010–2012 compared to 1991–1994. Organisms flexible in their habitat use may be better able to respond to continental forces driving distribution shifts. Conversely, habitat or prey specialists may be poorly equipped to handle such rapid, large-scale global change. Further, Grinnellian niche models predicting species response to change by mapping current habitat use to forecasted vegetation maps should consider plasticity in habitat use and changes in the cost-benefits of life-history strategies. © 2015 The Wildlife Society.