Where to put bike counters? Stratifying bicycling patterns in the city using crowdsourced data

This work was supported by a grant from the Public Health Agency of Canada to BikeMaps.org.When designing bicycle count programs, it can be difficult to know where to locate counters to generate a representative sample of bicycling ridership. Crowdsourced data on ridership has been shown to represent patterns of temporal ridership in dense urban areas. Here we use crowdsourced data and machine learning to categorize street segments into classes of temporal patterns of ridership. We used continuous signal processing to group 3,880 street segments in Ottawa, Ontario into six classes of temporal ridership that varied based on overall volume and daily patterns (commute vs non-commute). Transportation practitioners can use this data to strategically place counters across these strata to efficiently capture bicycling ridership counts that better represent the entire city.Publisher PDFPeer reviewe

Using inventory based field attributes to characterize carbon stocks and carbon stock changes within eddy-flux covariance tower footprints

Forests are an important part of the global carbon (C) cycle, and understanding and quantifying forest C dynamics is necessary for informed forest management decisions and accurate C budget accounting. This thesis contributes to the understanding of forest C dynamics by comparing biometric measurements of C stock changes (ΔC) and eddy covariance (EC) flux-tower measurements of cumulative net ecosystem productivity (ΣNEP) at three sites at the Fluxnet Canada Research Network British Columbia Flux Station; a young (near-end-of-rotation) forest established in 1949 (DF1949), a pole sapling stand established in 1988 (HDF1988), and a recent clearcut established in 2000 (HDF2000). To address spatial variability in stand and tower footprint conditions, first, light detection and ranging (lidar) remote sensing data were used to quantify large tree and snag aboveground mass (TSAM) at DF1949 (r²=0.75, SEE=29.68 Mg/ha). Next, for all three sites, remote sensing estimates were combined with advanced GIS data to estimate the spatial distribution of C stocks that are more difficult to measure directly using only remote sensing data. The resulting spatial representation of forest structure was combined with published EC flux-tower footprint probability distributions to enable a comparison between biometric ΔC stocks and tower ΣNEP. Where biometric ΔC stocks were difficult to resolve, changes were modeled using parameters from the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3). The best agreement between biometric ΔC stocks and tower ΣNEP was at DF1949 (mean = 15.18 ± 7.94 MgC/ha/4 years ΔC; 13.63 MgC/ha/4 years ΣNEP). The other two sites followed the same rank but had larger divergences and differences of sign (HDF1988: mean = 11.52 ± 1.17 MgC/ha/4 years ΔC and -1.93 MgC/ha/4 years ΣNEP; HDF2000: 3.59 ± 1.59 MgC/ha/4 years ΔC and -20.08 MgC/ha/4 years ΣNEP). An unaccounted source of respiration at the more recently disturbed sites may be related to stump, coarse root, and logging-slash decomposition. This study develops an approach and methodology that may be applied at other EC flux-tower sites where researchers wish to compare biometric-based measurements with micrometeorological-based measurements.Forestry, Faculty ofGraduat

Public participation to estimate forest fuels loading : the development and testing of an application for remote sensing

Advances in mobile computing provide an increasing number of possibilities for public participation in scientific research (PPSR). For example, a growing number of people have access to mobile computing devices, such as smartphones, equipped with sensors including a camera, global positioning system, the ability to record observations, and the ability transfer them over a network for collection and analysis. Literature has shown that PPSR-based approaches can have positive outcomes for volunteers (e.g., opportunities to pursue interests, develop skills, and influence decisions), for resource management (by providing data to inform management strategies), and for science. The objective of this dissertation is to explore how volunteers can use smartphones to collect data to inform forest management in a remote sensing project. The management of wildfires in communities near forested areas was chosen as a case study, and a smartphone application was developed and tested for collecting observations of the amount and arrangement of forest fuels by participants with a range of forestry experience living in fire-affected communities. First, to establish context, other projects using smartphones to collect Earth observation data were reviewed including related terms, concepts, challenges, and opportunities to identify methods of data collection and data processing. Second, questionnaires were given to the volunteers before and after using the application to collect data and were analyzed to understand the social and management considerations including the volunteers’ motivations, attitudes, and behaviours, and the potential of using a PPSR approach for wildfire management. Third, the locations where volunteers submitted data were re-measured and the quality of the data were assessed to provide guidelines for ensuring attribute accuracy and logical consistency. Fourth, the smartphone data was combined with multispectral remote sensing data and topography data to make estimates over broader areas. Finally, a framework was presented to direct future efforts using volunteered remote sensing data. This dissertation demonstrates an approach with potential to apply technology to help inform forest management in communities, with potentially positive outcomes for volunteers, communities, and forest managers.Forestry, Faculty ofGraduat

Comparison of three models for predicting gross primary production across and within forested ecoregions in the contiguous United States

Gross primary production (GPP), the photosynthetic uptake of carbon, is an important variable in the global carbon cycle. Although continuous measurements of GPP are being collected from a network of micrometeorological towers, each site represents a small area with records available for only a limited period. As a result, GPP is commonly modeled over forested landscapes as a function of climatic and soil variables, often supplemented with satellite-derived estimates of the vegetation\u27s light-absorbing properties. Since the late 1990s, a number of models have been developed to provide seasonal and annual estimates of GPP across much of the Earth. Each model, however, contains different underlying assumptions and requires different amounts of data. As a result, predictions vary, sometimes significantly. In this paper we compare modeled estimates of GPP for forested areas across the U.S.A. derived from: NASA\u27s MODIS Product (MOD17); the C-Fix model using SPOT-VGT satellite-derived vegetation data; and the Physiological Principles Predicting Growth from Satellites (3-PGS) model, a process-based model that requires information on both climate and soil properties. The models predicted average ecoregion values of forest GPP between 9.8 and 14.1 MgC ha−1 y−1 across the United States. 3-PGS predicted the lowest values while the C-Fix model, which included a CO2 fertilization factor, produced the highest estimates. In the western part of the country, estimates of GPP within a given ecoregion varied by as much as 50%, whereas in the northeast, where topography and climate are less extreme, variation in GPP was less than 10%. Within ecoregions, 3PGS predicted the most variation, reflecting its sensitivity to variation in soil properties. We conclude that where model predictions disagree, an opportunity is presented to evaluate underlying assumptions through sensitivity analyses, additional data collection and where more detailed study is warranted

Bicycle streetscapes: a data driven approach to mapping streets based on bicycle usage

Cities are making infrastructure investments to make travel by bicycle safer and more attractive. A challenge for promoting bicycling is effectively using data to support decision making and ensuring that data represent all communities. However, ecologists have been addressing a similar type of question for decades and have developed an approach to stratifying landscapes based on ecozones or areas with homogenous ecology. Our goal is to classify street and path segments and map streetscape categories by applying ecological classification methods to diverse spatial data on the built environment, communities, and bicycling. Piloted in Ottawa, Canada, we use GIS data on the built environment, socioeconomics and demographics of neighborhoods, and bicycling infrastructure, behavior, and safety, and apply a k-means clustering algorithm. Each street or path, an intuitive spatial unit that reflects lived experience in cities, is assigned a streetscape category: bicycling destination; wealthy neighborhoods; urbanized; lower income neighborhoods; and central residential streets. We demonstrate how streetscape categories can be used to prioritize monitoring (counts), safety, and infrastructure interventions. With growing availability of continuous spatial data on urban settings, it is an opportune time to consider how street and path classification approaches can help guide our data collection, analysis, and monitoring. While there is no one right answer to clustering, care must be taken when selecting appropriate input variables, the number of categories, and the correct spatial unit for output. The approach used here is designed for bicycling application, yet the methods are applicable to other forms of active transportation and micromobility

Promoting Crowdsourcing for Urban Research: Cycling Safety Citizen Science in Four Cities

People generate massive volumes of data on the Internet about cities. Researchers may engage these crowds to fill data gaps and better understand and inform planning decisions. Crowdsourced tools for data collection must be supported by outreach; however, researchers typically have limited experience with marketing and promotion. Our goal is to provide guidance on effective promotion strategies. We evaluated promotion efforts for BikeMaps.org, a crowdsourced tool for cycling collisions, near misses, hazards, and thefts. We analyzed website use (sessions) and incidents reported, and how they related to promotion medium (social, traditional news, or in-person), intended audience (cyclists or general), and community context (cycling mode share, cycling facilities, and a survey in the broader community). We compared four Canadian cities, three with active promotion, and one without, over eight months. High-use events were identified in time periods with above average web sessions. We found that promotion was essential for use of the project. Targeting cycling specific audiences resulted in more data submitted, while targeting general audiences resulted in greater age and gender diversity. We encourage researchers to use tools to monitor and adapt to promotion medium, audience, and community context. Strategic promotion may help achieve more diverse representation in crowdsourced data

Vegetation Mortality within Natural Wildfire Events in the Western Canadian Boreal Forest: What Burns and Why?

Wildfires are a common disturbance event in the Canadian boreal forest. Within event boundaries, the level of vegetation mortality varies greatly. Understanding where surviving vegetation occurs within fire events and how this relates to pre-fire vegetation, topography, and fire weather can inform forest management decisions. We used pre-fire forest inventory data, digital elevation maps, and records of fire weather for 37 naturally-occurring wildfires (1961 to 1982; 30 to 5500 ha) covering a wide range of conditions in the western Canadian boreal forest to investigate these relationships using multinomial logistic models. Overall, vegetation mortality related to a combination of factors representing different spatial scales. Lower vegetation mortality occurred where there was lower fuel continuity and when fires occurred under non-drought conditions. Higher classification accuracy occurred for class extremes of no mortality (i.e., unburned areas within the burn event) and high mortality; partial vegetation mortality classes were harder to distinguish. This research contributes to the knowledge required for natural pattern emulation strategies, and developing responses to climate change.Forestry, Faculty ofNon UBCForest Resources Management, Department ofReviewedFacult

Comparison of carbon-stock changes, eddy-covariance carbon fluxes and model estimates in coastal Douglas-fir stands in British Columbia

Background The global network of eddy-covariance (EC) flux-towers has improved the understanding of the terrestrial carbon (C) cycle, however, the network has a relatively limited spatial extent compared to forest inventory data and plots. Developing methods to use inventory-based and EC flux measurements together with modeling approaches is necessary evaluate forest C dynamics across broad spatial extents. Methods Changes in C stock change (ΔC) were computed based on repeated measurements of forest inventory plots and compared with separate measurements of cumulative net ecosystem productivity (ΣNEP) over four years (2003 – 2006) for Douglas-fir (Pseudotsuga menziesii var menziesii) dominated regeneration (HDF00), juvenile (HDF88 and HDF90) and near-rotation (DF49) aged stands (6, 18, 20, 57 years old in 2006, respectively) in coastal British Columbia. ΔC was determined from forest inventory plot data alone, and in a hybrid approach using inventory data along with litter fall data and published decay equations to determine the change in detrital pools. These ΔC-based estimates were then compared with ΣNEP measured at an eddy-covariance flux-tower (EC-flux) and modelled by the Carbon Budget Model - Canadian Forest Sector (CBM-CFS3) using historic forest inventory and forest disturbance data. Footprint analysis was used with remote sensing, soils and topography data to evaluate how well the inventory plots represented the range of stand conditions within the area of the flux-tower footprint and to spatially scale the plot data to the area of the EC-flux and model based estimates. Results The closest convergence among methods was for the juvenile stands while the largest divergences were for the regenerating clearcut, followed by the near-rotation stand. At the regenerating clearcut, footprint weighting of CBM-CFS3 ΣNEP increased convergence with EC flux ΣNEP, but not for ΔC. While spatial scaling and footprint weighting did not increase convergence for ΔC, they did provide confidence that the sample plots represented site conditions as measured by the EC tower. Conclusions Methods to use inventory and EC flux measurements together with modeling approaches are necessary to understand forest C dynamics across broad spatial extents. Each approach has advantages and limitations that need to be considered for investigations at varying spatial and temporal scales

An Exploratory Assessment of a Smartphone Application for Public Participation in Forest Fuels Measurement in the Wildland-Urban Interface

Wildfire management in the wildland-urban interface (WUI) protects property and life from wildland fire. One approach that has potential to provide information about the amount and location of fuels to forest managers and, at the same time, increase public knowledge and engagement in reducing wildfire threats is public participation in scientific research (PPSR)—also known as citizen science—where members of the public participate in the research process. In this exploratory study, residents of a wildfire-affected community tested a smartphone application to collect data about forest fuels and answered questions about wildfire, their community, and experiences using the application. In this paper, the application is introduced, the volunteers’ motivations, attitudes, and behaviors are considered, and the potential of using a PPSR approach for wildfire management discussed. Although there are practical challenges to applying PPSR approaches to wildfire hazard management, the participants in this study demonstrated the potential of PPSR to increase awareness and understanding of actions that can reduce the threat of wildfire. Wildfire managers may consider utilizing PPSR approaches to engage the community in wildfire preparedness.Forestry, Faculty ofNon UBCForest Resources Management, Department ofWood Science, Department ofReviewedFacult