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Digital Property Maps, 2002
— 2002-04-02 <p>The format of these files is <b>AutoCAD DXF</b>. CARIS ASCII and NTX are also available upon request.</p> <p>This data is available subject to academic licence conditions.</p> <p>Current digital property maps are available from <a href="http://www.snb.ca/geonb1/e/DC/catalogue-E.asp">GeoNB</a>, via the GeoNB Open Data Licence.</p> <p>Historical snapshot of New Brunswick Digital Property Maps (DPM).</p> <p>"Approximate boundaries for all land parcels in New Brunswick. The boundaries are structured as Polygons. The Property Identifier number or PID is included for each parcel." </p> <p>The sources of digital property data are the original property manuscripts prepared by SNB at the following scales:</p> <p>1:1000, 1:1200, 1:2000, 1:2400, 1:4800, 1:5000, 1:10 000, 1:20 000</p> <p>Information is derived from registered survey plans, registered documents, return of surveys, and other related documents.</p> <p>All property lines, including rivers, lakes and streams which form property lines are captured. At the scale of 1:10 000, hydrographic features which form property boundaries are captured from the Digital Topographic Database.</p>
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Influencing the Optoelectronic Properties of a Heteroleptic Iridium Complex by Second-Sphere H-Bonding Interactions
— 2018-06-20 The use of a new second-sphere coordination methodology for emission color tuning of iridium complexes is presented. Using host-guest H-bonding interactions we demonstrate that a complimentary H-bonding guest molecule can induce a shift in the emission from green to blue without the need to alter the ligand structure around the metal centre, while simultaneously increasing the photoluminescence quantum yield in solution.
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Research Data Management (RDM) at UNB: Results of UNB Libraries’ 2019 Survey
— 2020-04-02 Research Data Management (RDM) refers to the processes that guide the collection, documentation, storage, sharing, and preservation of original research data. RDM is becoming increasingly important to academic researchers who are or may soon be required to submit research data and data management plans with their publication submissions or funding applications (see the Tri-Agency Statement of Principles on Digital Data Management- https://www.ic.gc.ca/eic/site/063.nsf/eng/h_83F7624E.html). In our efforts to guide and support RDM best practices, UNB Libraries conducted a survey to determine current practices, perceptions, and future needs for managing original research data. The survey questions were focused on collecting information on the extent and types of data generated by UNB researchers, current practices for managing research data, and perceptions of the evolving RDM landscape. The results of this survey help to support our research community by designing RDM services and infrastructure suitable for current and future research needs.
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Applications of big BAF Sampling in Mixed Forests of Atlantic Canada
— 2002 The data are a subsample of an intensification of the 100 m North-South/East-West permanent sampling grid on the Noonan Research Forest. The 100m grid was intensified into a 50m grid. Three grid intersections per stand polygon were randomly selected. If a stand had fewer than 3 intersections, all intersections were selected. The stand polygons were based on the New Brunswick Department of Natural Resources’ Forest Development Survey derived from aerial photography taken in 1999. Horizontal point samples using a 2-M BAF angle gauge were the basis for all tree and plot measurements. The data were collected in summer 2002.
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Characterization of Pore and Grain Size Distributions in Porous Geological Samples
— 2021-03-23 This dataset contains X-ray microtomography and Scanning Electron Microscopy (SEM) images of five sandstone samples, including Berea, Buff Berea, Castlegate, Bentheimer, and Nugget, and one carbonate sample, Indiana Limestone, all acquired from Kocurek Industries (Caldwell, TX, USA). The dataset includes both raw and segmented images of the pore and grain space in addition to their size information.
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Acadian Forest Volume Estimates Derived from Airborne LiDAR, Big BAF Sample Plots, and Fixed Area Plots on the Noonan Research Forest
— 2020-05-31 The data are located on a 100 m N-S/E-W grid on the 80-ha Femelschlag Research Site on the Noonan Research Forest in New Brunswick, Canada. “Femel_EFI_GTV” contains the gross total volume (GTV; m3ha-1) estimates derived from airborne LiDAR scanning as part of the government of New Brunswick’s Enhanced Forest Inventory program. “Noonan_FemelPlot_GTV” contains the GTV estimates using four different plot types: fixed area plots with all trees measured for height; fixed area plots with 3P subsampling of heights; horizontal point sampling with all trees measured; and big BAF sample plots. The fixed area plots were circular with an 11.28 m radius and all tree 6cm DBH and greater were identified by species and measured for DBH and height. The 3P subsampling was simulated using a Height – Diameter curve as prediction and a target subsample size of 100 trees across the 83 plots. The horizontal point samples used a 2-M BAF angle gauge to select count trees for measurement. All trees 6 cm DBH and greater and considered “in” were identified by species and DBH measured. Heights were imputed using a Height – Diameter curve and the heights measured on the big BAF plots. The big BAF plots had the same plot design as the horizontal point samples and a 27-M BAF angle gauge was used to select trees for height measurement. All four plot types were center of the 100 m grid intersections. Grids do not align with EFI cells because the 100 m grid was established independently and prior to the EFI cells. The X – Y variables are the locations (in m) of the cell center (for Femel_EFI_GTV) and the plot centers (for Noonan_FemelPlot_GTV) with {0,0} being the SW corner of the study area.
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Monthly temperature, precipitation and Climate Moisture Index (1900-2015).
— 2019-01-17 Spatial (netCDF4) climatic data (Taxmax= monthly average of daily tmax (K), Tasmin = monthly average of daily tmin (K), Pr = monthly total precipitation (mm), CMI = Climate Moisture Index (mm)) for all North America.ge of daily tmin (K), Pr = monthly total precipitation (mm), CMI = Climate Moisture Index (mm)) for all North America.
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Simulated Mapped Plots Derived from NL Spacing Trials for Sector Subsampling Study
— 2020-12-01 The base data were collected from 3 early spacing trials located in western Newfoundland, Canada and established in the early 1980s. The dominant species was balsam fir with minor components of black spruce and white birch. Five spacing treatments were applied in this study areas using a randomized complete block design: control, or no spacing, (S00), 1.2m spacing (S12), 1.8m spacing (S18), 2.4m spacing (S24) and 3.0m spacing (S30). Each treatment was repeated 3 times per site (3×3×5 = 45 PSPs in this study). Treatments were applied to a 0.25 ha block (50m × 50m), and a circular permanent sample plot (PSP) was established near the center of each block. Plot sizes varied so that there were approximately 100 trees per plot following treatment. All trees 1.3 m and taller were identified by species and measured for diameter at breast height (DBH, nearest 0.01cm, BH = 1.3 m) and total height (HT, nearest 0.01 m). PSPs were remeasured at 3 to 5–year intervals but only the last measurements were used here. Stemwood, bark, branch, and foliage biomass (kg) was estimated for each tree using the Canadian national biomass equations. Total above-ground biomass (BM, kg) was estimated by summing these components.
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English East India Company 1st Voyage Crew List (1601-3)
— 2020-02-18 Using shipboard wills and Company documents, I have tried to determine the identities of those who sailed on the English East India Company’s first voyage in 1601-3 and get a more accurate idea of the mortality rate on this dangerous, foundational voyage.
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Digital Property Maps, 2001
— 2001-04-09 <p>The format of these files is <b>AutoCAD DXF</b>. CARIS ASCII and NTX are also available upon request.</p> <p>This data is available subject to academic licence conditions.</p> <p>Current digital property maps are available from <a href="http://www.snb.ca/geonb1/e/DC/catalogue-E.asp">GeoNB</a>, via the GeoNB Open Data Licence.</p> <p>Historical snapshot of New Brunswick Digital Property Maps (DPM).</p> <p>"Approximate boundaries for all land parcels in New Brunswick. The boundaries are structured as Polygons. The Property Identifier number or PID is included for each parcel." </p> <p>The sources of digital property data are the original property manuscripts prepared by SNB at the following scales:</p> <p>1:1000, 1:1200, 1:2000, 1:2400, 1:4800, 1:5000, 1:10 000, 1:20 000</p> <p>Information is derived from registered survey plans, registered documents, return of surveys, and other related documents.</p> <p>All property lines, including rivers, lakes and streams which form property lines are captured. At the scale of 1:10 000, hydrographic features which form property boundaries are captured from the Digital Topographic Database.</p>
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Biomass Data from Sector Subsampling of 360˚ Spherical Images
— 2021-03-30 The base data were collected from 3 early spacing trials located in western Newfoundland, Canada (Cormack, Pasadena, Roddickton) and established in the early 1980s (Donnelly et al. 1986; Fig.1). All trees 1.3 m and taller were identified by species and measured for diameter at breast height and total height periodically since the time of treatment. Using the most recent measurement at each trial, stemwood, bark, branch, and foliage biomass (kg) was estimated for each tree using the Canadian national biomass equations. Total above-ground biomass was estimated by summing these components. Total basal area was estimated by calculating tree cross-sectional area, multiplying by the appropriate plot expansion factor, and summing across all live trees. Spherical photos were obtained at three photo sample points located at half the plot radius and at azimuths of 0˚, 120˚, and 240˚. Spherical photos were obtained a 1.6m and 2.6m above the ground. Photo horizontal point sampling (Wang et al. 2020) using a 2 M photo basal angle gauge was used to estimate basal area at each sample point using the 1.6m spherical photo. Sector subsampling was then used to select measure trees using a randomly generated sector azimuth and a sector angle of 7.2˚ (2% of 360˚). All visible trees within each sector were then measured for total height and diameter at breast height using the spherical stereographic techniques. Biomass was then estimated using the Canadian National Biomass Equations, assuming all sector-selected trees were balsam fir. The plot-level data and measure-tree data were used to estimate aboveground biomass (BM, tonnes∙ha-1) using simulated resampling of the photo sample point data and ratio estimation.
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UNB Libraries: LibQUAL
— 2018-02-08 LibQUAL is a survey offered by the Association of Research Libraries to assess library services. The web-based survey instrument measures library users' minimum, perceived, and desired levels of service quality across three dimensions: Affect of Service, Information Control, and Library as Place. From 2007 to 2013, UNB Libraries participated as part of a nationwide consortium directed by the Canadian Association of Research Libraries (CARL) to encourage and support LibQUAL participation across Canada, and to provide national benchmarks for library service quality.
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Digital Property Maps, 2003
— 2003-04-01 <p>The format of these files is <b>AutoCAD DXF</b>. CARIS ASCII and NTX are also available upon request.</p> <p>This data is available subject to academic licence conditions.</p> <p>Current digital property maps are available from <a href="http://www.snb.ca/geonb1/e/DC/catalogue-E.asp">GeoNB</a>, via the GeoNB Open Data Licence.</p> <p>Historical snapshot of New Brunswick Digital Property Maps (DPM).</p> <p>"Approximate boundaries for all land parcels in New Brunswick. The boundaries are structured as Polygons. The Property Identifier number or PID is included for each parcel." </p> <p>The sources of digital property data are the original property manuscripts prepared by SNB at the following scales:</p> <p>1:1000, 1:1200, 1:2000, 1:2400, 1:4800, 1:5000, 1:10 000, 1:20 000</p> <p>Information is derived from registered survey plans, registered documents, return of surveys, and other related documents.</p> <p>All property lines, including rivers, lakes and streams which form property lines are captured. At the scale of 1:10 000, hydrographic features which form property boundaries are captured from the Digital Topographic Database.</p>

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