cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14288/1.0396658
title: Are Past Wildfire Activities Correlated with the Frequency of Different Types of Post-Wildfire Geomorphic Events such as Landslides and Debris Flows

description: Around the world, the frequency and intensity of wildfire events are rapidly increasing. Such a trend increasingly exposes some communities to the risk of the secondary hazards of wildfire, such as post-wildfire geomorphic events like a landslide and debris flow. To better manage the risk imposed by the secondary hazards of wildfire, a better understanding of the relationship between wildfire activities and the geomorphic events related therewith is necessary. In this paper, the temporal relationship between past wildfire events and the frequency of two different types of geomorphic events (landslides and debris flow) was studied statistically through the conduction of a time series analysis. The analysis conducted using the data created by the construction of a geomorphic event inventory derived from a set of Landsat based land cover classification of the region of the Rocky and Omineca Mountains in the Canadian province of British Columbia ranging from 1986 to 2019, and the wildfire boundary data provided by the Federal Government of Canada. Both a simple linear regression and a Poisson regression were conducted to analyze the relationship between time and the frequency of geomorphic events, with the application of a slope-based stratification. The study has three key findings. The first finding is that overall, there exists a strong negative temporal correlation between the time elapsed since the most recent event of a wildfire and the frequency of post-wildfire geomorphic events. Second, slope appears to be an influential factor for the relationship between wildfire and the frequency of post-wildfire geomorphic events. Third, despite the presence of a strong correlation, time is a very poor variable for explaining the dynamics of the frequency of post-wildfire geomorphic events.
DOI: 10.14288/1.0396661
title: Accessibility Analysis and Mapping at the University of British Columbia

description: The purpose of this dataset is to allow for an accessibility analysis and mapping project to be conducted on the University of British Columbia (UBC), Vancouver Campus. In a university setting, campus navigation is a foundational part of seizing opportunities, networking with other scholars, and having an all-around positive student experience. Yet, inaccessible features of an urban landscape (like stairs, rough terrain, or steep slopes) often leave mobility-limited individuals at a great disadvantage or cut off from certain opportunities. The accessibility analysis and mapping project (AAMP) is geared to try and answer what and where barriers to wheelchair accessibility exist on the UBC campus. To do this, (1) two cost paths for accessible and inaccessible terrain were calculated and compared to identify barriers to accessibility, (2) a least-cost path analysis is conducted to test if wheelchair routes are statistically longer than walking routes, and (3) a wayfinding map geared toward wheelchair users is created with the intention of increasing campus navigation equity and as a visualization for urban planners to see where campus accessibility improvements need to be made. It was discovered that 10% of the total walkable path area was some sort of accessibility barrier to wheelchair users. Through a visual investigation and comparison with the previous literature, three main types of barriers were identified on the campus. Next, an online map was created of the study site which highlighted accessibility barriers and difficult terrain. Finally, the paper ends with a discussion around why certain types of accessibility barriers exist on the campus and what urban planners can do to fix these and create more equitable wayfinding experiences across urban landscapes.
DOI: 10.14288/1.0396662
title: Remote Sensing Seagrasses in Cambodia: Comparing Sentinel-2 and Planetscope for detecting and monitoring seagrasses in Cambodia’s Koh Rong and Koh Sdach Archipelagos

description: Tropical seagrass is an integral part of the world’s fisheries as it acts as a nursery for benthic reproduction, leading to it being the center of many conservation efforts. Monitoring seagrass by high resolution satellite is commonplace, but such data quality is often unavailable for many conservation groups, leading to a question of whether open-source satellite data is sufficient to meet the rigorous needs of seagrass patch detection. 10m images from the European Space Agency’s (ESA) Sentinel-2 and 3m images from Planet Labs’ Planetscope covering the Koh Sdach and Koh Rong Archipelagos in Cambodia were collected, processed, and classified, with outputs being compared for seagrass detection ability and suitability. Image scenes were merged and processed to produce depth invariant indexes using the Lyzenga algorithm. Random forest classification with ground truth data yielded accuracies of 79.5% for Sentinel and 79.7% for Planetscope using unprocessed rasters, while depth invariant rasters resulted in accuracies of 80.8% and 70.0% respectively. Sentinel-2 and Planetscope are qualitatively compared based on technical specifications and factors such as band wavelength, radiometric quality, and revisit time. Sentinel-2 shows that it is able to match the seagrass detection ability of the higher resolution Planetscope due to its additional blue band and deeper radiometric depth. Results of this analysis are placed in the context of wider research on detecting seagrass patches through satellite image classification.
DOI: 10.14288/1.0396663
title: Distribution of suitable habitat in winter and summer for plains bison (Bison bison bison) in the Pink Mountain Region of British Columbia

description: The plains bison (Bison bison bison) is threatened in Canada, with the biggest threat to their recovery being a lack of habitat in which they are considered compatible. Although the Pink Mountain, British Columbia, bison herd currently has about 1,000 individuals, there has never been a formal study of the suitability of the area to sustain the herd. Therefore, this study was performed to determine if the Pink Mountain region contains plains bison suitable habitat based on guiding principles for developing a Habitat Suitability Index. Data used for analysis was aggregated from Landsat8, Canadian Digital Elevation Model, Daymet, and the Freshwater Data Atlas of British Columbia. The final habitat suitability index combined a value for slope, distance to water, landcover, aspect, and snow depth. Separate calculations were performed for summer and winter. Based on the habitat suitability model conducted, there appears to be significant habitat of sufficient quality to support a population of plains bison year-round in the Halfway River drainage. Areas with acceptable habitat were predominately in the river bottoms or valleys and the far eastern section of the study area. In the summer, approximately 60% of the area was categorized as a habitat suitability index of at least six. In winters with maximum snow coverage, only 17% was similarly categorized. Despite this, it is my impression that the area acceptable as habitat is sufficient for a considerable population of bison. Extending the area under study and creating estimates of forage production could lead to a more detailed assessment of carrying capacity for bison in the region, leading to improved management of this iconic species.
DOI: 10.14288/1.0396722
title: Examining the relationship between Landsat-derived spectral reflectance and multispectral Light Detection and Ranging (LiDAR)-derived intensity in Petawawa Research Forest, Ontario, Canada

description: Traditionally, Light Detection and Ranging (LiDAR) was used for forest structure analysis rather than capturing spectral information. A variety of studies were conducted to investigate the spectral characteristics of multispectral LiDAR but relatively few ones have integrated it with Landsat imageries. To compare their recorded reflectance and explore the prediction potential, we evaluated two series of regression modules measuring forest reflected energy with Landsat-derived reflectance and multispectral LiDAR-derived intensity, collected over 85 plots with the same area of 1000 m2 in Petawawa Research Forest, Ontario. The raw datasets were filtered, classified and the invalid plots were removed in the pre-processing step with three spectral bands, Green, NIR, and SWIR. Due to the value range differences of two sensors, limited and whole-area scaling algorithms were applied for subsequent comparisons. Following this, we used a dummy variable and further filtrations considering the reflectance differentiation by softwood and hardwood-dominated plots, and the effect of spatial autocorrelation. The histogram results showed no excessive change from the original datasets for all three spectral bands after scaling, and the limited scaling performed better with slightly higher root mean square errors (RMSE = 0.599 – 0.6815) and lower p-values (p = 0.005649 – 0.04193). A clear separation was demonstrated between softwood and hardwood reflectance capabilities in all three bands, suggesting influences of chlorophyll, spongy mesophyll structure, and water content in three spectral ranges respectively. Compared with hardwood-dominated plots, softwoods showed significantly higher correlation coefficients, especially in the SWIR band (r = 0.82). These results demonstrated a connection between Landsat- and multispectral LiDAR-derived outputs and offered the potential of using one sensor instead of two, suggesting the prospect of time and investment saving for further forest investigation and management.
DOI: 10.14288/1.0396743
title: Monitor Forest height growth using Light Detection and Ranging (LiDAR) canopy height models from 2005 to 2018 at the Petawawa Research Forest

description: Monitoring the growth of trees is important for sustainable forest management. The traditional method of monitoring forest growth at a broad level is timber cruising by humans, while modern remote sensing technology, especially Lidar, is usually used for monitoring at the single-tree level or stand-level. This paper uses airborne Light Detection and Ranging (airborne LiDAR, i.e. airborne laser scanning (ALS)) data from 2005, 2012, 2016, and 2018 and forest survey data in 2007 from the Petawawa research forest (Ontario, Canada) to monitor the tree height growth through a time series and build relationships between stand ages and dominant tree heights (DHs). On the area covered by all the data obtained, the entire forest can be divided into 4 landcover types (Early Seral, Mid-Seral, Mature and Old Growth) based on stand ages and 3 classification types (Grown, Disturbed, and Misclassified) based on the variation of DHs in the time series. 61% of the forest is grown and only 0.97% is misclassified, which proves this methodology a valid tool for land cover classification. The relationships between stand ages and DH for each landcover type and the whole grown forest are very reliable because their adjusted R2s are greater than 0.88.
DOI: 10.5281/zenodo.15277608
title: TABLE 1 in Discovery and formal description of the female of Microphotina Beier, 1935 (Mantodea: Photinaidae), with an updated key to species and remarks on the role of Citizen Science in advancing Mantodea biodiversity studies

description: TABLE 1. Measurements of studied females (mm).
SpecimenFemale 1 cFemale 2 dFemale 3Female 4Female 5Body lengtha2934323129Head Length3.633.753.713.743.45Head Width5.565.75.775.695.35Lower Frons width2.242.252.282.362.07Lower Frons length0.410.410.410.40.39Pronotal length (prozona + metazona)9.6910.1010.3310.519.37Prozona2.792.892.922.982.65Metazona6.97.217.417.536.72Pronotal width2.732.772.822.82.54Ratio metazona/prozona2.472.492.532.532.54Forewing Length14.3714.615.2415.3413.99Hindwing Length12.29----Hindwig Width8.11----Forecoxal Length6.586.966.927.086.6Forecoxal Width1.021.341.041.12-Forefemoral Length8.428.738.478.97.89Forefemoral Width1.832.001.971.661.51Foretibia Lengthb3.894.074.154.264.14Foretibia Length (with tibial spur)5.15.355.675.795.02Mesofemur Length8.38.478.448.967.67Mesotibia Length6.246.796.947.246.38Mesotarsus Length3.96----Metafemur Length-9.189.199.458.52Metatibia Length9.9110.5110.3210.899.66
aApproximated; body length measurements may vary due to the non-rigid nature of the abdomen.
bAs measured from the proximal bend of the tibia to the metatarsal insertion.
cSpecimen portrayed in Fig. 1C
dSpecimen portrayed in Fig. 1D
description: Published as part of Rivera, Julio, Hausherr, Nicolas & Lanna, Leonardo Moutinho, 2025, Discovery and formal description of the female of Microphotina Beier, 1935 (Mantodea: Photinaidae), with an updated key to species and remarks on the role of Citizen Science in advancing Mantodea biodiversity studies, pp. 234 in Zootaxa 5621 (2) on page 234, DOI: 10.11646/zootaxa.5621.2.4, http://zenodo.org/record/15262552
DOI: 10.14288/1.0398194
title: Revisiting the Role of Mountains in the Northern Hemisphere Winter Atmospheric Circulation

description: Supporting data for Revisiting the Role of Mountains in the Northern Hemisphere Winter Atmospheric Circulation published in the Journal of Atmospheric Sciences. Data includes December-February (DJF) and June-August (JJA) climatological averages of four WACCM (Whole Atmosphere Community Climate Model) simulations with altered topography. See the publication for full details of the experiments. Data are converted from model levels to pressure levels using NCL vinth2p function. A jupyter notebook using this data to produce many of the figures in the publication can be found here: https://github.com/rhwhite/SupportingInformation/blob/main/JASStatationaryWaves2021.ipynb. For daily output data please contact the author.
DOI: 10.14288/1.0396657
title: Relating Forest Fire Occurrences to Diurnal Land Surface Temperature Anomalies in Victoria, Australia from 2001 to 2019

description: Victoria, Australia has suffered from forest fire for a long period, and forest cover account for almost 25% of land cover. Therefore, it is significant to control fire events especially predict the fire burning effectively. Land surface temperature (LST) anomaly, as an important index, may build a relationship with fire occurrences to help fire management. In this dataset, the range is from 2001 to 2019 in January, the fire season peak, of LST anomaly. Through analysis of time series of LST anomaly, fire events occurred frequency as well as causes of fire, more spatiotemporal information was provided. Results have shown that there is no linear relationship between LST anomaly and fire occurrences, but time series of LST anomaly before fire events show a significant trend.
DOI: 10.6084/m9.figshare.28855181
title: Panel Dataset on Biofuel Production and Social Development Indicators (2002–2021)

description: Ferraz.It contains panel data from 50 countries between 2002 and 2021, focusing on the relationship between liquid biofuel production and key social indicators related to the Sustainable Development Goals (SDGs). The dataset includes variables on biofuel production, poverty, education, life expectancy, government effectiveness, and others relevant to social development.Most variables were collected from publicly available sources such as the FAOStat, UNDP, World Bank, and the Harvard Atlas of Economic Complexity. All values have been cleaned, harmonized, and prepared for econometric analysis, including transformation for panel regression models.The dataset is provided in Excel format (<code>.xlsx</code>) and includes a detailed <code>README.txt</code> file with descriptions and sources for each variable, as well as the R script used to perform the analysis.
DOI: 10.14288/1.0396724
title: Autocorrelation between Fuel Type Fragmentation and Fire Severity at the Elephant Hill wildfire in British Columbia

description: Geospatial analyses focused on quantifying fuel types fragmentation and its autocorrelation with megafire severity inform decision making in contexts such as forest management and human activities regulation. Fuel type fragmentation plays a crucial role in fire severity contribution. I evaluated the landscape and class level fragmentation of fuel types in two maps: FuelSat (derived from remote sensing) and a completely randomized map. Specifically, the C-2 (Boreal Spruce), C-3 (Mature Pine), slash, and standing grass were targeted for class level metrics calculation. Fire behavior could be described in two terms – burn probability and fire intensity. Flammability (burn probability) represent the likelihood of a given location on landscape burning, while the fire intensity is the rate of heat energy released by the fire. Burn probability and fire intensity of those four target classes were extracted from landscapes (FuelSat and Random). Boxplots were created to visualize the difference between burn probability and fire intensity of four classes from FuelSat and Random, respectively. Results indicated higher fragmentated fuel types would lower the fire intensity generally, but resulted in more extreme events. It was not evident that fuel type fragmentation has significant impacts on burn probability. Moran’s I was computed and did indicate there was autocorrelation between fuel fragmentation and fire intensity. It helps fill the gap in forest fire prediction by considering effects of fuel fragmentation.
DOI: 10.14288/1.0396742
title: Linking spectral recovery from remote sensing to ground observations at the Elephant Hill wildfire

description: The 2017 Elephant Hill wildfire is considered as one of the most destructive fires in Canada. Wildfires are a major ecosystem disturbance which also causes residential displacement and financial loss. Monitoring vegetation recovery following wildfires becomes crucial to rebuilding the local community and ecological system. Since recovery rates may have discrepancies between ground data and remote sensing data, this project aimed to investigate if the post-fire spectral recovery based on Landsat time series analysis can accurately capture vegetation recovery as ground plots indicate. A total of 20 Landsat scenes with the 30-meter resolution from a year before to three years after the fire event were used to analyze the spectral recovery at the Elephant Hill region. Two spectral indicators were calculated in the analysis including normalized difference vegetation index (NDVI) and normalized burn ratio (NBR). Clear spectral recovery patterns were observed from resulting maps and time series scatterplots while there was a significant decline of NDVI and NBR in the year of 2017. NDVI and NBR values have been gradually increasing after the fire and reached pre-fire pixel values by the year 2020. However, the results did not find any significant relationships between the NDVI / NBR values and vegetation cover percentage. Since this research focused on understory recovery with almost half of the plots having greater than 30% of crown closure, it is challenging to evaluate ground vegetation types and coverage in detail with 30-meter-spatial-resolution data. Therefore, the future study can consider sampling ground data with low canopy cover every year.
DOI: 10.15468/dl.54xjjv
title: Occurrence Download

description: A dataset containing 991 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Poecile carolinensis (Audubon, 1834)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen",
 "Year is greater than or equal to 1810",
 "Year is less than or equal to 2019",
 "Month is greater than or equal to April",
 "Month is less than or equal to September",
 "EventDate is not null",
 "Country is United States of America",
 "Geometry POLYGON((-63 22, -63 51, -126 51, -126 22, -63 22))"
 ]
}

 The dataset includes 991 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011029-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.23729/fd-5dc01c67-bd41-365d-9233-897229cc705a
title: Ethical Teachings from World Religions for AI Conscience Design

description: This dataset contains a selection of ethical guidelines and moral principles extracted from the scriptures of four major world religions: Christianity, Islam, Hinduism, and Buddhism. Each entry includes a quotation from the sacred text, a simplified principle, thematic tags, and additional interpretive context.

The dataset is intended to support research and design in conscience modeling for Artificial Intelligence (AI), Human-Computer Interaction (HCI), and value-sensitive technology. It is also relevant to interdisciplinary studies in ethics, philosophy, and comparative religion.

The dataset is designed to be open and expandable. Future versions may include additional religious traditions, teachings, and ethical frameworks. Published under the CC BY 4.0 license to support open access, reuse, and collaboration.
DOI: 10.15468/dl.m7xqgx
title: Occurrence Download

description: A dataset containing 10855 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Stomoxys calcitrans (Linnaeus, 1758)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 10855 records from 156 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008245-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dvzs9b
title: Occurrence Download

description: A dataset containing 549 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leontopodium pusillum"
 ]
}

 The dataset includes 549 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035822-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tbsdeu
title: Occurrence Download

description: A dataset containing 378 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Reseda crystallina"
 ]
}

 The dataset includes 378 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035823-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d3mqqe
title: Occurrence Download

description: A dataset containing 592 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leontopodium nanum"
 ]
}

 The dataset includes 592 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035824-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t57kbf
title: Occurrence Download

description: A dataset containing 35203 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Aquilegia canadensis"
 ]
}

 The dataset includes 35203 records from 172 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035821-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.27gzvb
title: Occurrence Download

description: A dataset containing 1076 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Phalaris minor",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1076 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035825-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.