This study investigates the utility of an off-the-shelf, consumer-grade unmanned aerial vehicle (UAV) for invasive species mapping in a lacustrine fringe environment. Specifically, this work sought to determine whether such UAV would be capable creating accurate maps extent patches plant, yellow flag iris (Iris pseudacorus L.), more efficiently than could accomplished by traditional field survey, which is often considered literature provide most maps. The was conducted at two lakes central...

With large volumes of data arriving in near real time from environmental sensors, there is a need for automated detection anomalous caused by sensor or transmission errors infrequent system behaviors. This study develops and evaluates three anomaly methods using dynamic Bayesian networks (DBNs), which perform fast, incremental evaluation as they become available, scale to quantities data, require no priori information regarding process variables types anomalies that may be encountered....

We used geographic datasets and field measurements to examine the mechanisms that affect soil carbon (SC) storage for 65 grazed non-grazed pastures in southern interior grasslands of British Columbia, Canada. Stepwise linear regression (SR) modeling was compared with random forest (RF) modeling. Models produced SR performed better than those using RF models (r2 = 0.56–0.77 AIC 0.16–0.30 models; r2 0.38–0.53 0.18–0.30 models). The factors most significant when predicting SC were elevation,...

The Mental Health Locus of Control (MHLC) Scale is an area-specific measure locus control expectancies designed to predict mental health related behaviors, particularly those occurring in treatment situations. discriminant validity the MHLC, contrast with Rotter's 1-E generalized expectancies, was demonstrated two variables: beliefs concerning etiology psychopathology, and information about abnormal psychology. Beliefs were measured by Origin (MHLO) Scale. primary hypothesis, that...

This study investigates the combination of image processing and supervised classification to identify invasive yellow flag iris (YFI; Iris pseudacorus) plants in images collected by an un-calibrated, visible-light camera carried aloft unmanned aerial vehicle. Specifically, image-processing steps colour thresholding, template matching, and/or de-speckling prior training a random forest classifier are explored terms their benefits towards improving resulting YFI within image. The impacts...

The Internet of Things (IoT) offers immense benefits by enabling devices to leverage networked resources thereby making intelligent decisions. numerous heterogeneous connected that exist throughout the IoT system creates new security and privacy concerns. Some these concerns can be overcome through trust, transparency, integrity, which achieved with data provenance. Data provenance, also known as lineage, provides a history transformations occurs on object from time it was created its...

Spatial proximity is an important metric in cattle behaviour, which used to study social structure, dyadic relationships, as well grazing and maternal behaviours. We developed efficient, novel, non-invasive method quantify the spatial of beef by using UAV-based image acquisition photogrammetric analysis. Orthomosaics constructed images obtained from UAVs were measure, with accuracy ±1.96 m (95% likelihood), inter-individual distances between cows calves. Aerial videos calves their dams, held...

This study examined the effectiveness of solar UV forecasts and supporting communications in assisting adults to protect themselves from excessive weekend sun exposure. The was conducted Australia, where 557 adult participants with workplace e-mail Internet access were randomly allocated one three weather forecast conditions: standard (no UV), + UV, sun-protection messages. From late spring through summer early autumn, they e-mailed working week. Each Monday a prompt complete Web-based...

This paper describes our first step towards the realization of complex and large scale cross-organization virtual observatories by presenting a new semantically-enhanced ldquosensor network as servicerdquo (SNaaS) framework, which can repurpose existing sensor networks needed aggregate fuse heterogeneous sensors into in near-real-time. The architecture this system allows users to create Web 2.0 collaborative map interface. Components are highlighted including semantically enhanced streaming...

Abstract Radio frequency identification ( RFID ) provides a simple and inexpensive approach for examining the movements of tagged animals, which can provide information on species behavior ecology, such as habitat/resource use social interactions. In addition, tracking animal is appealing to naturalists, citizen scientists, general public thus represents tool engagement in science education. Although useful tool, large amount data collected using may quickly become overwhelming. Here, we...

Assimilation of data from heterogeneous sensors and sensor networks is critical for achieving accurate measurements environmental processes at the time space scales necessary to improve forecasting decision-making. Owing different measurement accuracies types spatial and/or temporal support component sensors, it often unclear how best combine these data. This study explores utility ubiquitous producing categorical wet/dry rainfall improving resolution areal quantitative precipitation...

This study develops and evaluates a sensing system capable of measuring stemflow at high temporal resolutions. Leveraging affordable hobbyist grade electronics has allowed for the development which is low-cost, easy to reproduce adaptable. Eschewing classic measurement techniques, demonstrated herein utilizes payload includes wetness sensor ultrasonic rangefinder. Combined, these sensors are determining precise initiation cessation times as well capturing resolution volume measurements 10 s...

Daily minimum and maximum air temperature (min/max Ta) exhibits a strong linear correlation with remotely sensed land surface (LST). However, LST-based predictions of min/max Ta exhibit seasonal pattern in their errors. This study examines the temporal trends LST, shows that strongest exhibited by any these variables is autocorrelation periodic nature. analyses relationship between this results trend errors can primarily be explained phase shift oscillations LST. After removing elevation...