cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57745/bfvgwn
title: S036402000_projection_datasheet.pdf

description: :unav
DOI: 10.57745/duaj2v
title: S213401001_projection_datasheet.pdf
DOI: 10.57745/gpfseo
title: S131501000_projection_datasheet.pdf

description: :unav
DOI: 10.57745/obhixc
title: S224251001_projection_datasheet.pdf
DOI: 10.57745/qbakhp
title: S224251001_projection_datasheet.pdf

description: :unav
DOI: 10.57745/tl76lq
title: S131501000_projection_datasheet.pdf
DOI: 10.57745/wbrwqi
title: Notice_fiche_synthese.pdf
DOI: 10.57745/yxzf6g
title: S213401001_projection_datasheet.pdf

description: :unav
DOI: 10.14288/1.0412939
title: Rose Swanson Mountain, British Columbia - A Forest Health Assessment

description: Rose Swanson Mountain is an ecologically and culturally important forested region in the Northern Okanagan, British Columbia, Canada. In the summer of 2021, BC Timber Sales proposed eleven clear cut blocks on this area. Clear cut logging is a common practice in British Columbia, and while many studies have focused on recovery within the harvested areas, little research has analyzed the effects on the surrounding forest. Additionally, without localized scientific analysis, it is difficult for rural communities to preserve valued recreational areas on Crown land from logging. The goal of this study was to explore the trend in forest health and assess the effects of clear-cut harvesting on the immediately surrounding forest over time using freely available data and methods of analysis in order to empower rural communities to engage in their own assessments of local forests. Using Normalized Difference Vegetation Index (NDVI) and Green Chlorophyll Index (GCI) calculated from Landsat scenes of the area from 1985 to 2020, forest stress was calculated based on changes in these indices. There was found to be no significant trend in the vegetation indices over the 36 years measured. With a maximum NDVI value of 0.49 calculated, other important disturbance factors may be at play, such as pest infestation or changing climate. Preliminary analysis found significantly higher NDVI values within 30m of a cut block as compared to 120m away. However, future research and quality assessments are needed to confirm this result. Providing a baseline analysis, this study can help the Friends of Rose Swanson Ecosystem Stewardship Society (FORSES) and local community members start to work with geospatial data in ways that allow them to maintain and enhance the values of Rose Swanson Mountain.
DOI: 10.57745/5msmbg
title: S036402000_projection_datasheet.pdf
DOI: 10.57745/s93n2c
title: Notice_fiche_synthese_Explore2.pdf
DOI: 10.57745/uc3kaf
title: S514401000_projection_datasheet.pdf
DOI: 10.14288/1.0413301
title: Vegetation Change in the Tumbler Ridge Region, British Columbia from 1940 to 2020

description: In recent years, the application of remote sensing technology in vegetation change monitoring has played an important role. The purpose of this project is to explore changes in vegetation in the Tumbler Ridge region of British Columbia between the 1940s and 2020 and to discuss the relationship to fire urbanization and deforestation. A series of aerial photographs (taken in the 1940s), Landsat 5 remote sensing images (1985), and forest vegetation composite polygons (2020) were classified and analyzed by Object-Based Image Analysis (OBIA) and Support Vector Machines (SVM) for evaluation Vegetation Composition and Matrix Analysis of Vegetation Change in the Tumbler Ridge Region Using Vegetation Transition Matrix. The results showed that, between the 1940s and 2020, the area of the broadleaf forest increased from 7.415 km2 to 16.262 km2, and the area of the coniferous forest increased from 12.177 km2 to 23.477 km2, and the area of the mixed forest increased from 23.611 km2 fell to 11.951 km2. The area of shrubs and bare land increased first and then decreased. The transformation of vegetation mainly occurs between the three types of forests and the transformation into bare land. Considering the reasons for the change, although forest fires may also be contributing factors, the changes in vegetation patterns may be mainly attributable to rapid urbanization and deforestation in the 1980s. These findings add to the understanding of historical reference conditions and may help identify restoration targets in the Tumbler Ridge area.
DOI: 10.14288/1.0416751
title: Evaluating Landscape Metrics and Landcover Class Change at Rose Swanson Mountain

description: Landcover reflects distribution characteristics of surface vegetation, spatial differentiation and evolution across time. Controversial logging project that took place at Mount Rose-Swanson had raised concerns from the local community. Landcover maps and metrics can be used to study effects of human disturbances on the landscape. With the advancement of spatial pattern analysis program, ‘landscapemetrics’ package in R was used to quantify and investigate relationship between forest landcover and timber harvesting which occurred within. 35 high resolution annual forest landcover maps for Canada’s forested ecosystems from 1985 to 2019 inclusive were reclassified into five classes which are no change, shrubs, herbs, conifer and mixed wood. 1km x 1km grid cells were applied onto Mount Rose-Swanson to separate grid cells which experienced harvesting or remained unharvested. Harvested grid cells were found to have a higher mean number of patches of sum of all landcover classes 36.55 compare to unharvested grid cells 29.00 (p &lt; 0.01) which indicates grid cells that experienced harvesting had more fragmentations. Coniferous landcover class remained the largest with an area of 208.92 hectares. Despite harvesting is expected to decrease coniferous landcover class, no significant differences in number of patches, mean patch area, metric values such as landscape shape index and edge density were found between each year for harvested and unharvested across 35 years. Surprisingly, mixed wood landcover had significant increase in number of patches for unharvested land (p &lt; 0.03). Changes in landcover class, harvested year and size enables insights on formulating future logging schemes for sustainable development. Unreported small-scale logging continues to present as a challenge and the use of landcover time series is crucial in monitoring ecology of the mountain.
DOI: 10.5281/zenodo.15277758
title: Define-ML: An Approach to Ideate Machine Learning-Enabled Systems

description: This dataset contains the anonymized responses to questionnaires completed by participants in the static and dynamic validation phases of the Define-ML approach. The questionnaires assess user experience, perceived usability, and other relevant metrics related to the validation process. The data is structured for reproducibility and further analysis, supporting research in ideation methods for ML-enabled systems.
DOI: 10.5281/zenodo.15277759
title: Define-ML: An Approach to Ideate Machine Learning-Enabled Systems

description: This dataset contains the anonymized responses to questionnaires completed by participants in the static and dynamic validation phases of the Define-ML approach. The questionnaires assess user experience, perceived usability, and other relevant metrics related to the validation process. The data is structured for reproducibility and further analysis, supporting research in ideation methods for ML-enabled systems.
DOI: 10.14288/1.0412884
title: Development of Interactive Data Visualization Tool for the Predictive Ecosystem Mapping Project

description: Biogeoclimatic Ecosystem Classification (BEC) system is the ecosystem classification adopted in the forest management within British Columbia based on vegetation, soil, and climate characteristics whereas Site Series is the smallest unit of the system. The Ministry of Forests, Lands, Natural Resource Operations and Rural Development held under the Government of British Columbia (“the Ministry”) developed a web-based tool known as BEC Map for maintaining and sharing the information of the BEC system, but the Site Series information was not included in the tool due to its quantity and complexity. In order to allow users to explore and interact with the information, this project aimed to develop a web-based tool with high data quality and flexibility to users for the Site Series classes using the “Shiny” and “Leaflet” packages in R. The project started with data classification and pre-processing of the raster images and attribute tables through identification of client requirements, spatial database design and data cleaning. After data transformation was conducted, spatial relationships among these data were developed for code development. The code development included the setting-up of web map and interactive tools for facilitating user friendliness and flexibility. The codes were further tested and enhanced to meet the requirements of the Ministry. The web-based tool provided an efficient and effective platform to present the complicated Site Series features with the use of Web Mapping System (WMS) in map rendering. Four interactive tools were developed to allow users to examine and interact with the information. The study also found that the mode filter performed well in data preservation and noise minimization but suffered from long processing time and creation of tiny sliver polygons.
DOI: 10.14288/1.0412889
title: Understanding Microclimate in University of British Columbia's Botanical Garden

description: Climate change is a key factor in how extreme weather events affect how ecosystems and species react to these changes in temperatures. University of British Columbia's (UBC) Botanical Garden is interested in improving microclimate information within the garden to understand how areas with shade create respite zones for species. Due to the recent extreme weather temperatures in Vancouver, the garden is interested in how to continue to adapt and mitigate to these extremes. Microclimates are important as they are cooler temperatures beneath the canopy. Looking at how canopy cover influences land surface temperature can give insight on microclimates. Using LiDAR metrics to calculate canopy cover and Landsat to calculate land surface temperature, a model was built to understand the significance of canopy cover and land surface temperature, with the addition of other LiDAR metrics. The model could only determine a 34% variation between the variables tested. Canopy cover showed to have a p-value of 0.0993 and maximum height had a p-value of 0.0034. To investigate the results further, an unpaired t-test was run to determine the relationship between areas with canopy cover and areas without canopy cover. The t-test showed there are significant differences as the p-value was 0.0035. With the results, they provide observations of how canopy cover currently influences microclimate within the garden. Areas found to have a high percentage of canopy cover reflected lower land surface temperatures. Currently, the model has the structure to predict canopy cover with LiDAR metrics. However, finer data is needed to accurately predict microclimate. Recommendations are provided to enhance the study area with future directions for research within UBC Botanical Garden to conduct a more intricate analysis.
DOI: 10.14288/1.0412890
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: 10.14288/1.0412937
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: 10.14288/1.0413207
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: 10.14288/1.0413208
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: 10.14288/1.0413113
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: 10.15468/dl.7kuqun
title: Occurrence Download

description: A dataset containing 6811 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Anodorhynchus hyacinthinus (Latham, 1790)",
 "Year 2020-2025"
 ]
}

 The dataset includes 6811 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000488-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14288/1.0412967
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: 10.14288/1.0413110
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.