cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5683/sp3/zvcu0n
title: Climate adaptation scenarios for a resilient future at University of British Columbia Botanical Garden: Modeling 4 Species of Acer (Maple)

description: As anthropogenic climate change continues to disrupt forests and species’ ecological niches, there is increasing urgency to create plans surrounding adaptation and mitigation for especially vulnerable species. The University of British Columbia’s Botanical Garden (UBCBG) wants to understand species responses to climate change and whether species within their collection will be able to survive in the Garden, given the effects of climate change. One especially important collection UBCBG curates is maple (Acer) trees, currently leading the global consortium of Acer and housing over 50 different species. This study examined the survival probability of four Acer species UBCBG curates including: five-fingered Maple (Acer pentaphyllum Diels), considered critically endangered; paperbark/bloodbark Maple (Acer griseum (Franch.) Pax), considered endangered; bigleaf maple (Acer macrophyllum Pursh), not endangered; and vine maple (Acer circinatum Pursh), not endangered. Maxent, a popular machine-learning algorithm, was used with open-source WorldClim’s 19 bioclimatic variables and provided presence-only occurrence data to conduct species distribution models for each tree species. Each model was evaluated using area under the curve (AUC). AUC scores were considered ‘good’ for each model; A. griseum - 0.95; A. pentaphyllum - 0.877; A. macrophyllum - 0.986; A. circinatum - 0.976. However, future distribution maps contain questionable results due to insufficient field data to inform the model, such as in-field temperature, moisture, elevation, and surrounding vegetation data. Though results can be interpreted as binary regarding whether or not UBCBG will be suitable for each species, they should be taken as preliminary ideas where management plans for mitigation and adaptation can be developed. This study concludes by detailing the importance of field data collection and provides future directions for research that UBCBG may consider when conducting similar analysis.
DOI: 10.5683/sp3/r1ymnd
title: Examining the University of British Columbia Vancouver campus views using LIDAR data

description: This study examines the application possibilities of LIDAR data in 
building a digital model of the campus in three dimensions to: 
a) assess whether strategic observations point still exist on campus. 
b) mapping the built landscape across campus.
c) determine planning principles for areas of interest where the 
new building height is considered. 
The study presents various methods, such as viewshed analysis and raster 
calculations. It mimics the observation boundaries from critical points 
on-campus to understand better the threatened interest points and elements 
that block these observation areas. The height element was a significant
component in the analysis, and the maximum height of future buildings is 
also considered in this way. Out of interest in seeing if new buildings 
disturbed the balance of nature seen by one of the selected observations 
points. The study results showed accuracy in the input data that made it 
possible to build an advanced three-dimensional campus model. This model 
enables real-time performance to simulate and test the construction 
evolution of UBC's future built form.
DOI: 10.5683/sp3/tnnbsf
title: Applying a Faster R-CNN Model Coupled with a Generalized Linear Model to Optical Imagery to Fill Population Data Gaps in Villages along the Southwest Coast of Madagascar

description: This data includes the training data used to create the models used in the study, as well as the digitized features converted to shapefiles which were used to create the training data. Lastly, this data contains the resulting accuracy metrics from the model run on three villages of interest. Metadata can be found within the data as well as in a zipped metadata folder. See the readme text file for more information surrounding each file.
DOI: 10.5683/sp3/xxfe13
title: Musandam Arabic demonstratives

description: This dataset contains recordings of demonstratives - masculine and feminine singular, proximal and distal - in twelve varieties of Musandam (Shihhi) Arabic.
DOI: 10.5683/sp3/tgwnna
title: Using SAR Imagery to Assess Forest Distribution on a Cloudy Tropical Island

description: Tropical forests experience some of the highest rates of deforestation in the world. Accurate mapping and monitoring of the forest is required to mitigate this deforestation, which is complicated in tropical forests due to the high frequency of cloud cover. Synthetic aperture radar (SAR) imagery can overcome this challenge by seeing through the clouds. However, the historical lack of freely available SAR imagery means its role in characterizing forest cover is less developed than that of optical imagery. This study aimed to compare freely available SAR imagery with freely available optical imagery in order to characterize the forest cover of a particularly cloudy, mountainous tropical forest in the Philippines. SAR imagery was downloaded from Sentinel-1 and ALOS-PALSAR-2 missions while optical imagery from Sentinel-2 was used. Single date images from January 2016 were selected used along with derived forest cover metrics as inputs into a two-class Random Forest classification. The results showed that optical imagery outperforms the SAR models with a 97% overall accuracy compared to 88% for the L-band PALSAR-2 data. The predicted maps created using only SAR inputs are significantly noisier than models that included optical data. SAR maps had high levels of speckling throughout the image which made interpretation difficult at larger spatial scales. The SAR map performed worse in the more mountainous areas. The results demonstrate that SAR cannot directly replace optical for the most mountainous, cloud-prone areas.
description: Python, 3.10
description: SAR Predicted Rasters
DOI: 10.5683/sp3/hpeyca
title: Nature of War: The Political Ecology of the 2020 Nagorno-Karabakh Conflict

description: The Nagorno-Karabakh conflict has had profound consequences for both the political and physical geography of the South Caucasus region. Since the fighting of the 1990s there has been a relative status quo, with a militarised line of contact separating the two sides. This changed on September 27 2020, when intense fighting erupted along the whole of the front, and especially in the south-east. After a month and a half, fighting concluded on 10 November 2020 which saw the implementation of a ceasefire which ceded large portions of the Nagorno-Karabakh (Artsakh) Republic to Azerbaijan. There has yet to be an investigation on the kinds of changes to human and natural systems that the most recent conflict (2020) engendered.

In response to this research lacuna, this paper asked whether the effects of the 2020 armed conflict had a significant effect on the region’s agricultural systems. This paper approached the question by examining per-pixel NDVI metrics - derived from Landsat 8 composites from April through June - before and after the conflict. These per-pixel metrics were correlated with conflict data from ACLED. This approach aims to test the hypothesis that areas which witnessed the most intense fighting saw significant drops in NDVI, indicating land fallowness and abandonment. The results from this study indicate that conflict intensity has a significant effect on vegetation health (p-value &lt; 2.2e-16), and supports the hypothesis that conflict leads to a decrease in NDVI, however conflict intensity on its own does not have strong explanatory power for estimating changes in NDVI (R2 0.09667) and future work ought to segment the study area in order to obtain a non-obfuscated regression coefficient (coefficient -0.0057322).
description: ArcGIS Pro, 2.8.6
DOI: 10.5683/sp3/rdxi6p
title: Identifying brain correlates of cybersecurity notifications

description: This is the file repository used for our study Identifying Brain Correlates of Cybersecurity Notifications, REB 2019-4404 at Dalhousie University, done through the NeuroCognitive Imaging Lab. This study was later nicknamed "tsn" for short, standing for "threats and security notifications". We are currently preparing an article to disseminate the results of this study in a way that is accessible to anyone in the world. In this folder you will find our original and processed files collected throughout the experiment. The repository consists of 24 electroencephalography (EEG) and behavioural recordings recorded while participants attended various images. Many of the images were positive, negative or neutral valence pictures extracted from the International Affective Pictures Database (IAPS) while some of the images consisted of images of cybersecurity notifications or other computer stimuli not related to security warnings. The EEG recordings were used to compare event-related potentials, which ultimately revealed a distinct pattern in response to cybersecurity notifications which had many commonalities with the negative valence IAPS pictures.
DOI: 10.5683/sp3/owk1ne
title: Burn-P3 modelling of fire behaivour on Rose Swanson Mountain, British Columbia before and after harvesting

description: It has been long known that wildfire and harvesting can have a relationship. However, this relationship is not straightforward and well understood. In this paper, we hope to quantify the impact of proposed harvesting on the wildfire severity and probability on Rose Swanson Mountain. Rose Swanson Mountain is a small mountain in South Central BC near the town of Armstrong used by the locals for its bountiful outdoor recreation. In early 2020 British Columbia Timber Sales added part of the Rose Swanson Mountain Sensitive Area to its list of soon-to-be harvested areas. This paper illustrates the research done in BurnP3 and ArcPro to simulate and measure fire in a pre and post logged Rose Swanson. After 5,000 iterations of the BurnP3 model using the pre-logging fuel type data, the fire probability ranged from 0% to 49.7%, with a mean probability of 6.45% across the landscape. After 5000 iterations of the BurnP3 model using post logging fuel types on Rose Swanson, the burn probability ranged from 0-49.34%, with a mean of 6.43% across Rose Swanson Mountain. This indicated the fire probability across the mountain and little increase as a whole. However, an apparent increase in fire probability was present in the close vicinity to the logged areas. Additionally, the pre-logged average fire intensity values on Rose Swanson ranged from 0 to 60,599 kW/m with a mean value of 2,841 kW/m, while the post-logged ranged from 0 to 122,849 KW/m with a mean of 3,183 kW/m. This difference was clear in the maps produced by BurnP3. While the results were insightful, many limitations were noted, including poor fuel type accuracy, limited model run count, and low-resolution data. The research offers valuable insight into the wildfire and harvesting relationship and sets the toon for further research.
DOI: 10.5683/sp3/0kdocx
title: How do shading and cooling of urban forests across the University of British Columbia Vancouver Campus affect building temperatures?

description: Understanding temporal and spatial variations in environmental conditions is important for determining how urban forests affect ecological communities at the local scale. This study aims to use LiDAR data to investigate how shading and cooling affect urban forests at the UBC Vancouver campus within an ecosystem services framework. To quantify the cooling and shading effects of urban forests on the UBC Vancouver campus, it is first necessary to obtain a general understanding of the spatial and temporal variations in campus temperature to identify areas that have experienced dramatic temperature changes. Next is to analyze the relationship between temperature and multiple environmental factors, including tree characteristics and ground conditions based on local context. The last step is to weigh the importance of each variable to assess the vulnerability and resilience of the region in coping with summer heat waves and mitigating the Urban Heat Islands (UHI) effect. The results showed the mean temperature range of the whole study area was higher than 15◦C, which was closely related to the specific environmental factors such as canopy height, canopy area, and canopy density. This study went further to illustrate that cross-comparisons of the importance of each environmental factor to temperature changes can help predict the distribution of heat in cities and the resistance of regions to heat waves. Additional research is needed on identifying and assessing other critical variables that mitigate the UHI effect.
DOI: 10.5683/sp3/59pxf6
title: Determining Floodplain Characteristics Using Active Remote Sensing
title: How accurately can floodplain extent and bench heights be modelled using available digital elevation models for the floodplains of the Date Creek Research Forest in northwestern British Columbia, Canada?

description: Currently, light detection and ranging (LiDAR) scans have been used to produce 1m & 5m digital elevation models (DEMs) throughout many important drainages across the province and are ideal candidates to effectively inform vegetation classification within floodplain and riparian ecosystems. These ecosystems are highly influenced by fluctuating freshwater regimes and are invaluable in providing, regulating, and supporting various ecosystem functions. This paper explored the extent that various floodplain characteristics, including bench heights and overall floodplain extent, can be modelled using a readily available 1m DEM within the Date Creek Research Forest (DCRF) in northwestern British Columbia (BC), Canada. Stream paths were derived from a flow accumulation analysis of the DEM. These paths highlighted how the pre-existing river feature network, the Freshwater Atlas, differed up to 230.8m, with a median distance between segments being 23.4m. Bench height transition areas were easily identifiable considering slope and curvature, yet further research is needed to classify areas of the varying benches across the landscape. The Height Above Nearest Drainage (HAND) method was used to assess floodplain extent using peak water depth values observed at nearby water survey of Canada hydrometric stations. Overall, the HAND method is limited to generating water height along flow paths that drain into the main stream, and such are inaccurate in demonstrating any spill over into adjacent braided river channels. This paper demonstrates the inadequacies of using the HAND method to define floodplain extent within braided river channels common throughout BC floodplains and therefore concludes that alternative methods should be employed when expanding floodplain prediction to other rivers systems within the province.
DOI: 10.5683/sp3/drbkno
title: Post-Fire Mortality and Fire Resistance of Old-growth Forests in the Kootenay Lake Timber Supply Area, British Columbia

description: In an era of climate change, how different tree species in old forests are disturbed by wildfires, and what fire resistance they have are important questions. Old-growth forests are significant because they maintain local biodiversity and ecosystem sustainability, and also contribute to the local economy through timber harvesting. In this research, by analyzing Landsat-8 images of 20 fires from 2016 to 2020, the disturbance data of the forest before and after the fire can be generated. Data from B.C. government and Landsat-8 images are used to analyze fire resistance and recovery of old-growth forests in the Kootenay Lake Timber Supply Area (TSA) by calculating NBR (Normalized burn ratio) and NDVI (Normalized Difference Vegetation Index). Five common tree species (western larch, Douglas fir, western hemlock, Engelmann spruce, subalpine fir) near Kootenay Lake TSA were selected for fire resistance comparison at different burn severities (high, medium, low). The result verified that different tree species have different fire resistance and mortality when facing different burn severities. Western larch and Douglas fir have high fire resistance. Western hemlock has relatively low fire resistance. Engelmann spruce and Subalpine fir have very low fire resistance. This result is highly similar to the report provided by USDA. However, due to the shortage and limitations of data, the NDVI trend after fires cannot well represent the recovery of vegetation. Overall, based on the analysis of Landsat-8 satellite images before and after the fire, this paper verifies the difference in the fire resistance of five tree species in the old-growth forests for different burn severities.
DOI: 10.5683/sp3/nrvt59
title: Paths and Barriers Identification: Algorithm based on LiDAR data

description: The wayfinding system is important for the people on campus. However, the existed wayfinding system of UBC does not consider some walkable paths which are not shown on the street map. Also, the wayfinding system ignores the barriers like stairs, which could be obstacles for wheelchair users, on the paths. LiDAR is developed rapidly in recent years. It can collect the elevation information of the objectives on the ground. University of British Columbia (UBC) collects and publishes the LiDAR dataset of campus every year. This project uses the elevation and the point intensity information from the LiDAR point dataset to identify the walkable paths and the barriers on the paths. Two algorithms are announced. The first one is the intensity-based path identification algorithm, which assumes that the concrete paths have a homogenous intensity. Another algorithm is the barrier identification algorithm, which is based on the Canny edge detection algorithm. As a result, the two algorithms both work well in the research area, and they have the potential to be developed as an automatic process and can be one part of the wayfinding system.
DOI: 10.5683/sp3/qskca3
title: Polygonization of discontinuous raster classes from machine-learning predictive ecosystem mapping (PEM)

description: Biogeoclimatic Ecosystem Classification (BEC) has been applied extensively in characterizing forested ecosystems in British Columbia. With a lack of qualified vectorization method used for BEC data transformation, the main goal of this research is to polygonize discontinuous BEC raster classes into vector map with better overall effectiveness and efficiency especially regarding the linear areas. The original data input for analysis is a machine-learning BEC zone raster map of Deception Study Area located in middle BC near Telkwa, with a resolution of 5m*5m. A comprehensive comparison between vectorization algorithms in GIS applications was conducted, including different filtering, simplifying and smoothing algorithms. Since we have the original predicted BEC raster map as the performance measurement, accuracy was directly measured as the percentage of correctly classified pixels when rasterizing the polygons. The evaluation criteria include visual effect, number of polygons, linear patches accuracy processing time. We found an appropriate vectorization routine to polygonize the classification raster maps. The polygonal map using Scenario D has overall satisfactory effectiveness and efficiency with a 46% linear patch accuracy and 62,014 polygons. The method also provides good approximations of the areas with moderate processing time. This is partly because we allow vertices to be located anywhere and not just exactly on the boundary of the original raster zones. We can promote this polygonization method in future predicted ecosystem mapping (PEM) product with similar linear and discontinuous areas. Priority of several key BEC zone classification with importance level regarding to the ecosystem condition related to endangered species can be further explored and added to the algorithms to better polygonize those areas in future studies.
DOI: 10.5683/sp3/ay5lc4
title: Determining conservation priority areas for mangrove conservation and quantifying mangrove dynamics

description: Here I document a method for determining priority conservation areas using a suitability analysis combining data sources on surrounding forest loss (Global Forest Change Database), mangrove loss (Global Mangrove Watch), soil carbon content (Global Mangrove Soil Database), and above ground biomass (Global Mangrove Above Ground Biomass Database) that was applied to 96 of Blue Ventures (BV) global locally managed marine areas. The site determined to be the highest conservation priority was the Kubu Raya region of Indonesia with the highest suitability score across all sites (0.8 compared to 0.39). This was a result of the large loss of mangroves within the region (1161 Ha from 1996-2016), its vast soil carbon stock (2 \times\ {10}^8\ Mg), and above ground biomass (9.7 \times\ {10}^5\ Mg). Mangrove dynamics were also further quantified by classifying composites from 2000-2001 using 800 CRA’s, and 8 different spectral indices to inform a random forest classifier. There was calculated to be 5718 Ha of loss with 6315 Ha of gain within the same period, however the loss metric was determined to be more reliable with 1114 Ha of loss within known logging concessions. This analysis represents a consistent and replicable workflow for determining priority target areas and quantifying dynamics for informing mangrove forest conservation programs for any site around the world

This dataset comprises a) the Landsat composites for 2000 and 2021 that I created, b) the Classificaition Reference Areas (CRA's) I used to inform the random forest classifier, c) the output classified images for 2000 and 2021, d) a raster indicating mangrove loss between the two periods and, d) a raster indicating mangrove gain between the two period. Further information can be found in the readme file and full text.
DOI: 10.5683/sp3/gfekzw
title: Within-Ecosystem Quantification and Comparison of Treeline Advancement in Cariboo Mountain, British Columbia

description: High elevation ecotones are susceptible to the rising temperature, under current climate
change crisis. This paper aims to quantify the loss of alpine habitat to treeline advancement in the mountainous areas of the Cariboo Natural Resource Region. Specifically, this study focuses on comparing the patterns and rate of treeline advancement in the dry and wet subzones of Englemann Spruce – Subalpine Fir (ESSF) zone. Landsat 5 imageries and Digital Elevation Models are used to determine the treeline during 1985 – 2010. The Normalized Difference Vegetation Index (NDVI) are determined at a 5-year interval. The threshold value for pixels transition from non-forested to forested is set at 0.3. All the transition pixels are identified and the elevational analysis was conducted. The identified transition pixels (treeline ecotones) of Wet subzones have a higher R2 and mainly show a decreasing trend. This means that the growth rate of treeline ecotone is slowing down in wet subzones. Dry subzones have a relatively small R2 and mainly show an increasing trend. The increasing trend represents the growth rate of treeline ecotone is accelerating in dry subzones, which also means that the rate of alpine habitat loss is accelerating
DOI: 10.5683/sp3/qknq08
title: Trait syndromes of hyperaccumulator plants

description: Data and script used for the letter 'Trait syndromes of hyperaccumulator plants: a call for trait data contributions'. Data extracted form the plant trait base TRY and the global hyperaccumulator database.
description: under submission processes