This dataset contains shape files and supporting files for the most up-to-date (as of the published date) land use map at the UBC Farm. The best uses of these maps are: 1) to visualize locations of field codes in other UBC Farm datasets; 2) to visualize field codes for UBC Farm research projects, and 3) to understand the general layout of the Farm.

Urban green spaces are closely related to the abundance and biodiversity of birds by providing important habitats and together contribute to ecosystem health. This project aims to guide the University of British Columbia Botanical Garden to create Bird-friendly green spaces by using LiDAR data to analyze and map UBCBG's bird habitat suitability and create a 3D digital twin model of UBCBG in the open source game engine Minetest to increase 3D visualization and aid in landscape planning. By extracting the Canopy Height Model (CHM) using LiDAR data and performing individual tree segmentation, the derived metrics were used to identify trees with the highest bird habitat suitability index. The results showed that the suitability index ranges from -0.0016 to 0.5187, with a mean value of 0.2051. There are 68 trees with high suitability above the 0.4 intervals which have significance to bird populations and are worthy of being protected, accounting for only 3.38% of the total trees. They usually have a low vertical complexity index and foliage height diversity but are characterized by very tall trees with relatively large tree crowns. The Digital Elevation Model (DEM), Canopy Height Model (CHM) generated by LiDAR data were visualized in Minetest's UBCBG's 3D digital twin model using real terrain mod as topography and vegetation layers, while bird habitat suitability was used to symbolize the tree canopy layer. This study is highly relevant for landscape adaptation and planning in conjunction with other management considerations to support bird-friendly green spaces. The digital twin model can be used for educational and promotional purposes, and for landscape planning and aesthetic design with the consideration of bird conservation.

This study focuses on the use of citizen science and GIS tools for collecting and analyzing data on Rose Swanson Mountain in British Columbia, Canada. While several organizations collect data on wildlife habitats, trail mapping, and fire documentation on the mountain, there are few studies conducted on the area and citizen science is not being addressed. The study aims to aggregate various data sources and involve citizens in the data collection process using ArcGIS Dashboard and ArcGIS Survey 123. These GIS tools allow for the integration and analysis of different kinds of data, as well as the creation of interactive maps and surveys that can facilitate citizen engagement and data collection. The data used in the dashboard was sourced from BC Data Catalogue, Explore the Map, and iNaturalist. Results show effective citizen participation, with 1073 wildlife observations and 3043 plant observations. The dashboard provides a user-friendly interface for citizens to tailor their map extent and layers, access surveys, and obtain information on each attribute included in the pop-up by clicking. Analysis on classification of fuel types, ecological communities, endangered wildlife species presence and critical habitat, and scope of human activities can be conducted based on the distribution of data. The dashboard can provide direction for researchers to develop research or contribute to other projects in progress, as well as advocate for natural resource managers to use citizen science data. The study demonstrates the potential for GIS and citizen science to contribute to meaningful discoveries and advancements in areas.

This research explores the innovative use of a 3D gaming engine, Minetest, for visualizing changes in canopy cover change at the University of British Columbia (UBC) campus, addressing the pressing challenge of urban expansion on green spaces. We compared and visualized canopy height change for UBC campus in both 2D traditional environment and 3D gaming engine environment and we revealed a consistency between the spatial patterns of canopy cover change observed in both environments. Our findings indicate 3D environment provided multi-dimensional insights into canopy cover changes, offering decision-makers more straightforward and transparent insight than traditional maps can achieve in an immersive and interactive environment. We observed there is a significant change in canopy cover with 25 percent loss in total where Wesbrook community area experienced the most significant canopy cover loss in past 5 years due to rapid urban development. Our findings goes beyond merely presenting geographic maps and attributes from a 3D voxel game perspective. Instead, it will serve as a useful tool and references for UBC decision makers and planners to inform management plan on the pathway of building a green, well-planned community.

TransLink route and station data created from General Transit Specification Feed (GTFS), downloaded 8 April 2025. GeoJSON geometry files and a combined Geopackage database were created by UBC Library from the GTFS feed from TransLink. Stops geojson file: Point file showing all transit stops Shapes geojson file: Polyline file showing each route as a separate shape Shapes, routes and trips can be analyzed by joining the attributes of the shapes and stops geometry to the appropriate tables based on matching IDs.

TransLink route and station data created from General Transit Specification Feed (GTFS), downloaded 24 April 2017. Esri shapefiles and geojson were created by UBC library from the GTFS feed from TransLink. Stops shapefile: Transit stops as point shapefile Shapes, routes and trips shapefile and geojson: Bus routes as polyline shape file with trip information. No time codes are included.

Based on the First Series of the Ordnance Survey London Town Plans. Each factory is coded to indicate whether it is on both or just one of the two 19th century series of Ordnance Survey London Town Plans. I have also tried to catagorize the factories. There are some other incomplete fields or fields used in earlier versions of this database. Data used in Jim Clifford, West Ham and the River Lea A Social and Environmental History of London’s Industrialized Marshland, 1839–1914, UBC Press, 2017, https://www.ubcpress.ca/west-ham-and-the-river-lea

In response to the growing concern in geographic information science, which pertains to utilizing contemporary internet technology to communicate past information or knowledge for establishing foundations in geography. Recent studies have investigated geomatics solutions for historical city, and enhancing GIS skills through collaborative approach. In this study, we build upon prior research by exploring how the implementation of current technology can promote a cooperative learning environment, particularly within the realm of forestry education. Minetest, the 3D voxel game engine has high capability of modification, for visualizing natural environments and urban structures. The goal of this study was to investigate the potential of using the game engine for forestry education purposes. To meet this objective, we developed precise and detailed models of building structures and their surrounding environment. We also explored the visualization beyond 3D geospatial data, by generating analytical results of solar radiation on building roofs using GIS software. The visualization process was facilitated by the use of 3D light detection and ranging (LiDAR) data, provided by the UBC Campus + Community Planning department. The proposed approach proved to be effective in producing compatible geospatial data for visualization in the game engine. We also conducted exploratory statistical analysis to examine the relationship between building energy usage and solar radiation. The exploratory regression result of the solar radiation analysis has an R2adj of 0.19, which indicates its insignificant impact on building energy usage. Finally, the findings of this research provide a foundation for future studies that can continue to explore the potential of using 3D game engines. Keywords: 3D Geo-Visualization, Forestry Education, Remote Sensing, Light Detection and Ranging (LiDAR), Building Energy Usage, Solar Radiation Analysis

Based on the First Revised Series of the Ordnance Survey London Town Plans. You can find a different version of the Georeferenced maps on the National Library of Scotland website:

https://maps.nls.uk/geo/explore/#zoom=11&lat=51.4907&lon=-0.1331&layers=163&b=1

Each factory is coded to indicate whether it is on both or just one of the two 19th century series of Ordnance Survey London Town Plans. I have also tried to catagorize the factories. There are some other incomplete fields or fields used in earlier versions of this database.

Data used in Jim Clifford, West Ham and the River Lea A Social and Environmental History of London’s Industrialized Marshland, 1839–1914, UBC Press, 2017, https://www.ubcpress.ca/west-ham-and-the-river-lea

LiDAR (Light Detection and Ranging) data of the City of Vancouver and UBC Endowment Lands with an Area of Interest (AOI) covering a total of 134 square kilometers.​Data products includes a classification that defines "bare earth" ground surface, water and of the upper most surface defined by vegetation cover, buildings and other structures.Data accessEach of the 181 polygons on the map or rows in the table provides corresponding link to the data in LAS format (zipped, file sizes range from 16.45MB to 2.74GB).AttributesPoint data was classified as:Unclassified;Bare-earth and low grass;Low vegetation (height <2m);High vegetation (height >2m);Water;Buildings;Other; andNoise (noise points, blunders, outliners, etc) Note​The 2022 LiDAR data is being utilized for initiatives including land management, planning, hazard assessment, (e.g. floods, landslides, lava flows, and tsunamis), urban forestry, storm drainage, and watershed analysis. Data currency​Aerial LiDAR was acquired on September 7th and September 9th, 2022 and is current as of those dates. Data accuracyThe LiDAR data is positioned with a mean density of approximately 49 points per square metreSidelap: minimum of 60% in north-south and east-west directionsVertical accuracy: 0.081 metre (95% confidence level)Coordinate system​The map of grid cells on this portal is in WGS 84 but the LiDAR data in the LAS files are in the following coordinate system:Projection: UTM Zone 10 (Central Meridian 123 West)Hz Datum: NAD 83 (CSRS) 4.0.0.BC.1.GVRDVertical Datum: CGVD28GVRDMetro Vancouver Geoid (HTMVBC00_Abbbyn.zip) Websites for further information City boundary dataset

Due to the rapid growth of urbanization, species biodiversity is threatened and the innate relationship between humans and nature begins to fade gradually. Urban green spaces play a vital role in reconnecting human and urbanized landscape with its unique characteristics. Meanwhile, virtual gaming technology with applied geographic information has made a spectacular process to promote interactions between humans and their surroundings. Five types of green space were identified in the University of British Columbia Vancouver campus: lawn, planting bed, planting bed on structure, athletic field, and urban forest. A novel approach of combining Light Detection and Ranging (LiDAR) data, ground-based inventory data, geographic information system (GIS) data, and geocoordinates derived from reality game Pokémon GO was applied to explore geospatial gaming technology’s application in mapping cultural use and biodiversity hotspots at a university campus. LiDAR-derived individual tree crown polygons contributed to estimate canopy cover. Manually delineated tree crown from the study area's orthophoto was used to compare the crown area accuracy with LiDAR technology. The point density heat map illustrated the study area's cultural interests, which were generated by Pokestops' geospatial coordinates. A dataset containing two green space assessments was conducted with various factors: native species ratio, species richness, canopy cover, and cultural interest. Both assessments highlighted the importance of urban forest. This green space type achieved 0.396 in the first assessment and 0.501 for the second assessment of cultural and biodiversity values.

Green spaces play an important role in providing ecosystem services such as air purification, temperature regulation, and recreational opportunities; however, their unequal distribution often highlights environmental inequities. This study examines the spatial distribution of green space coverage across the University of British Columbia (UBC) Vancouver campus to identify areas with limited access, termed Equity Initiative Zones (EIZs). A Geographic Information System (GIS)-based methodology was employed, integrating Light Detection and Ranging (LiDAR) data, green space data, a pedestrian walkway dataset, and a hexagonal grid framework to analyze pedestrian accessibility to green spaces using service area analysis, and to identify green space diversity and spatial equity disparities through statistical analysis. Results revealed that while the UBC campus has an average of 37.8% green space and 46.7% tree canopy coverage, approximately 6% of the campus falls within EIZs, primarily in northeast areas near academic buildings and parking lots—with mean green space coverage of approximately 1.8%. A moderate negative correlation between distance to green spaces and canopy coverage (r = −0.25, p = 1.96 × 10⁻⁷) suggested reduced canopy coverage in areas further away from green spaces. Additionally, green space diversity analysis showed that high-traffic areas like the academic zones are dominated by homogenized lawns, whereas peripheral areas such as those near the UBC Farm exhibit greater diversity. These findings highlight environmental inequities where EIZs may experience diminished access to ecosystem benefits, emphasizing the need for targeted interventions such as tree planting or the creation of pocket parks to promote a sustainable and inclusive campus environment.

In the face of rapidly declining biodiversity and the increasing fragmentation of habitats, identifying and prioritizing conservation areas have become crucial challenges for environmental sustainability. This study seeks to address these challenges by leveraging the power of citizen science data from iNaturalist and integrating it with GIS technology to assess conservation priorities in Campbell River, British Columbia. By integrating species occurrence data, conservation status, and cultural value, we have used GIS tools to assess conservation priority land parcels visually. Species occurrence data from iNaturalist Meticulous collection and validation of data emphasizes research-grade observations to reduce identification errors and ensure reliability. We integrated species conservation status from CDC-iMap and cultural value from IMPRESS and applied a tiered scoring system to quantify Species Importance Scores (IV). Through GIS analysis, the spatial visualization of species distribution can be realized and the corresponding land parcel Importance Score (LPIS) calculation can be obtained by summing up each land parcel based on IV. The results demonstrate significant differences in species importance across land cover types, identify several higher-value conservation land parcels in the Campbell River region, and highlight key conservation values that emphasize certain types of land cover habitat. The results showed that the riparian area along the Elk Falls Provincial Park and nearby urban and coastal areas of Campbell River tend to contain the highest conservation value. We also discussed potential limitations, mainly caused by the species occurrence data selectivity bias, and species identification accuracy. This approach would guide species and biodiversity conservation and land management planning in the Campbell River region.

Usage notes

The Census of Turin, Italy, 1705 [ICPSR 3577] collection includes eight AtlasGIS files that produce maps of Turin when used with the AtlasGIS mapping software package. These files are found in Dataset 0002, Map Files, and are provided in a PKZip archive. Please note that the archive file should be treated as a binary file. For more information about AtlasGIS and how to use the GIS files go to http://support.esri.com.

Usage notes

Zipped files (.zip) are stored in an ESRI geodatabase (.gdb) and can be accessed through open-souce GIS software (e.g., QGIS)

Over the course of 50 years the Ontario Ministry of Natural Resources and Forestry (OMNRF) has captured bathymetry data for over 10,000 lakes across Ontario. In 1968 the Department of Lands and Forests initiated the Aquatic Habitat Inventory Program to collect information for Ontario’s inland water data. One product was a series of contour maps showing lake depth. In many cases, these maps still represent the only authoritative source of bathymetry data for lakes in Ontario. These maps have been converted to digital GIS data which has resulted in the vast majority of the current data in the Bathymetry Line data class. More recent bathymetric data has been collected using sonar and GPS technology. This modern technique creates lake depth points (spot depths) rather than contours. This point data is stored in the Bathymetry Point data class. Bathymetry Line contains lines of constant depth called depth contours or isobars. Depth contours are used to describe the terrain relief below the surface of the water. The data used to derive the depth contours are always spot depths but the density and positional accuracy of these spot depths vary depending on the survey style and parameters. Before GPS data was available, spot depth locations were derived by straight line transects across a water body which were then plotted on a map. The time consuming nature of this method limited the number of transects collected. Now GPS data collection is not limited to transects and therefore spot depth collections tend to be far denser with greater horizontal accuracy. Depth contours have been derived in one of two ways: Visually interpreted and drawn by hand based on transects of the water body Interpolated using GIS processes such as Kriging or Natural Neighbours Vertical accuracy of the data varies greatly depending on the density of spot depth collected for each lake. Horizontal accuracy will also vary greatly on older transect based collections but will be within 5m for GPS based collections. Bathymetry point and line data should not be used for navigational purposes.

The population of Metro Vancouver (20110729Regional Growth Strategy Projections Population, Housing and Employment 2006 – 2041 File) will have increased greatly by 2040, and finding a new source of reservoirs for drinking water (2015_ Water Consumption_ Statistics File) will be essential. This issue of drinking water needs to be optimized and estimated (Data Mining file) with the aim of developing the region. Three current sources of water reservoirs for Metro Vancouver are Capilano, Seymour, and Coquitlam, in which the treated water is being supplied to the customer. The linear optimization (LP) model (Optimization, Sensitivity Report File) illustrates the amount of drinking water for each reservoir and region. In fact, the B.C. government has a specific strategy for the growing population till 2040, which leads them toward their goal. In addition, another factor is the new water source for drinking water that needs to be estimated and monitored to anticipate the feasible water source (wells) until 2040. As such, the government will have to make a decision on how much groundwater is used. The goal of the project is two steps: (1) an optimization model for three water reservoirs, and (2) estimating the new source of water to 2040.

The process of data analysis for the project includes: the data is analyzed with six software—Trifacta Wrangler, AMPL, Excel Solver, Arc GIS, and SQL—and is visualized in Tableau. 1. Trifacta Wrangler Software clean data (Data Mining file). 2. AMPL and Solver Excel Software optimize drinking water consumption for Metro Vancouver (data in the Optimization and Sensitivity Report file). 3. ArcMap collaborates the raw data and result of the optimization water reservoir and estimating population till 2040 with the ArcGIS software (GIS Map for Tableau file). 4. Visualizing, estimating, and optimizing the source of drinking water for Metro Vancouver until 2040 with SQL software in Tableau (export tableau data file).