In Canada, more than 35 million kilograms of pesticide active ingredients are applied annually on agricultural land with about 84% of this mass applied in the Canadian Prairies Provinces. Pesticide residues may become airborne through post-volatilization losses from land, water or vegetative surfaces, via wind-eroded soil, and by spray drift during pesticide application. Once in the air, pesticides may be dispersed and transported as parent molecules or as degradation products. Currently used and legacy pesticide air concentrations were measured in the agricultural region of the Prairie Provinces and the northern subarctic and arctic regions of Canada in 2005 and 2007. More intensive air sampling was conducted across the province of Manitoba in 2008 and 2009. Separate wet versus dry atmospheric deposition samples and wetland water samples were also taken in these years. In general, pesticides were detected in the monitored environmental media as mixtures with the frequency and concentrations detected being largest for pesticides that were applied on-site. Although the most commonly used herbicides in western Canadian agriculture were frequently present in the air in the regions where they are applied, they appeared infrequently and at low levels in the Canadian Subarctic, Arctic, and remote sites far from agricultural pesticide applications. Results also indicated that the concentrations of legacy pesticides such as lindane (γ-HCH) and its manufacturing by-product prior to 1971 (α-HCH) continued to decrease over time in the Canadian environment. Air concentrations of pesticides in agricultural regions, and subsequent wet and dry atmospheric deposition, contaminated surface water following periods of pesticide application. Dry deposition contributed 12–51% of the total deposition. Calculations were performed to predict wetland water column pesticide concentrations based on total atmospheric deposits alone. The estimated concentrations were closest to actual concentrations for MCPA and predictions were also reasonable for a range of other herbicides, but a source other than atmospheric deposition was clearly relevant to the detection of clopyralid in the wetland water-column. Individual herbicide concentrations did not exceed Canadian water quality guidelines for the protection of aquatic life.

No description available.

Through inquiry, experience, and discovery, this practicum reveals the landscape of Old Wives Lake, Saskatchewan and the prairie pothole region that surrounds it. It is my intention for this work to become a device for the revealing of unseen forces, for the creation of a different attention, an altering of perception, and an openness to a unique landscape of ever changing and shifting phenomena. It is accepted that complex systems, cannot be fully understood without time, patience, and commitment; however, through learning, understanding and revealing, the potential to not simply ‘see’ a landscape, but ‘read’ a landscape is harvested to enlighten and share in its discovery. The result is an exhibition of the unexpected Saskatchewan landscape.

Through inquiry, experience, and discovery, this practicum reveals the landscape of Old Wives Lake, Saskatchewan and the prairie pothole region that surrounds it. It is my intention for this work to become a device for the revealing of unseen forces, for the creation of a different attention, an altering of perception, and an openness to a unique landscape of ever changing and shifting phenomena. It is accepted that complex systems, cannot be fully understood without time, patience, and commitment; however, through learning, understanding and revealing, the potential to not simply ‘see’ a landscape, but ‘read’ a landscape is harvested to enlighten and share in its discovery. The result is an exhibition of the unexpected Saskatchewan landscape.

The diploma thesis is dealing with the topic of new trends in asphalt road routine maintenance with a focus on new possibilities to repair damaged road surface, especially potholes and cracks. In the diploma thesis, a new advice which uses microwave heating in resurfacing asphalt roads was developed with the aim to observe its effectiveness and the optimal repair time. The obtained results were consulted with the producer of the equipment in order to utilize this new technology for repairing potholes and cracks on asphalt road surface in standard practice.

In this modern era, land transports are increasing dramatically. Moreover, self-driven car or the Advanced Driving Assistance System (ADAS) is now the public demand. For these types of cars, road conditions detection is mandatory. On the other hand, compared to the number of vehicles, to increase the number of roads is not possible. Software is the only alternative solution. Road Conditions Detection system will help to solve the issues. For solving this problem, Image processing, and machine learning have been applied to develop a project namely, Detection of Road Conditions Using Image Processing and Machine Learning Techniques for Situation Awareness. Many issues could be considered for road conditions but the main focus will be on the detection of potholes, Maintenance sings and lane. Image processing and machine learning have been combined for our system for detecting in real-time. Machine learning has been applied to maintains signs detection. Image processing has been applied for detecting lanes and potholes. The detection system will provide a lane mark with colored lines, the pothole will be a marker with a red rectangular box and for a road Maintenance sign, the system will also provide information of aintenance sign as maintenance sing is detected. By observing all these scenarios, the driver will realize the road condition. On the other hand situation awareness is the ability to perceive information from it’s surrounding, takes decisions based on perceived information and it makes decision based on prediction.

There are around 300, 000 kilometer of gravel roads throughout the Swedish countryside, used every day by common people and companies. These roads face constant wear due to harsh weather as well as from heavy traffic, and thus, regular maintenance is required to keep up the road standard. A cost effective maintenance requires knowledge of where support is needed and such data is obtained through inventorying. Today, the road inventory is done primarily by hand using manual tools and requiring trained personel. With new tools, this work could be partially automated which could save on cost as well as open up for more complex analysis. This project aims to investigate the possibility of automating road inventory using computer vision and machine learning. Previous works within the field show promising results using deep convolutional networks to detect and classify road anomalies like potholes and cracks on paved roads. With their results in mind, we try to translate the solutions to also work on unpaved forest roads. During the project, we have collected our own dataset containing 3522 labelled images of gravel and forest roads. There are 203 instances of potholes, 614 bare roads and 3099 snow covered roads. These images were used to train an image segmentation model based on the YOLOv8 architecture for 30 epochs. Using transfer learning we took advantage of pretrained weights gained from training on the COCO dataset. The predicted road segmentation results were also used to estimate the width of the road, using the pinhole camera model and inverse projective geometry. The segmentation model reaches a AP50−95 = 0.746 for the road and 0.813 for the snow covered road. The model shows poor detection of potholes with AP50−95 = 0.048. Using the road segmentations to estimate the road width shows that the model can estimate road width with a mean average error of 0.24 m. The results from this project shows that there are already areas where machine learning could assist human operators with inventory work. Even difficult tasks, like estimating the road width of partially covered roads, can be solved with computer vision and machine learning.

The master thesis is focused on sorting collected primary data, their subsequent analysis and further comparison in the field of road defects. The collection of pavement failures was done by visual inspection with its recording to a computer for the pavement management system. The data later underwent detailed analysis with the aim to find a potential link between the road defect and the location of the damaged section. The study took place on 2nd and 3rd class roads in the Liberec Region, with special focus on those located near forests. The data collection itself took place in the Liberec Region in 2021. The processing and subsequent evaluation of collected data was done thanks to the availability of comparable data sets from 2014 and 2019 to 2021, so the development of road defects of the selected road network in relation to the surrounding afforestation could be assessed. The last part of this master thesis compares results in different classification levels, time periods and levels of afforestation.

No description available.

This practicum is a reference for vertical gardeners in cold climates. Winnipeg, Manitoba is explored, however findings may be applied to other cities in similar climates. First, the history of vertical gardening is discussed, then the types of vertical gardens currently on the market are described. These can be classified into two categories: soil bearing or non-soil bearing. Most designs are modular pre-planted systems that can be attached to any wall, as long as it satisfies the structural requirements recommended by the manufacturer. The benefits of vertical gardening have been shown to be rather extensive, covering a wide range of areas. Aesthetic improvement, reduction of the Urban Heat Island (UHI) effect, improvement of air quality, stormwater absorption, noise reduction, native habitat integration, reduction of heating and cooling costs for buildings, food production, marketing, and biophilia are all benefits explored in detail. Difficulties associated with vertical gardening are discussed, specifically the lack of knowledge and awareness of vertical gardens, lack of empirical evidence (or missing details in existing research), overall cost and lack of financial incentives, lack of industry codes, and various associated risks. Design framework exists within microclimate conditions unique to vertical gardens, as well as neighbourhood and regional (micro)climates. Theories relating to the study of green walls covered include the human ecosystem model, urban reconciliation ecology, habitat templating, the urban cliff hypothesis, and wall ecology. Suitable habitat templates identified for vertical gardens in Winnipeg are cliffs, sand dunes, alvars, mixed grass prairie and prairie potholes. Design parameters to be followed for vertical garden design in Winnipeg are to ensure that lightweight materials are used, to provide insulation to protect plants from sudden temperature changes, to choose plants that grow in the region and are adapted to grow in areas with limited soil, increased wind, varying degrees of sunlight (depending on orientation), and increased pollution and salt spray depending on location. / October 2015