Physical Visualization of Geospatial Datasets

Geospatial datasets are too complex to easily visualize and understand on a computer screen. Combining digital fabrication with a discrete global grid system (DGGS) can produce physical models of the Earth for visualizing multiresolution geospatial datasets. This proposed approach includes a mechanism for attaching a set of 3D printed segments to produce a scalable model of the Earth. The authors have produced two models that support the attachment of different datasets both in 2D and 3D format.

A gridded inventory of Canada's anthropogenic methane emissions

Canada's anthropogenic methane emissions are reported annually to the United Nations Framework Convention on Climate Change (UNFCCC) through Canada's National Inventory Report (NIR). Evaluation of this policy-relevant inventory using observations of atmospheric methane requires prior information on the spatial distribution of emissions but that information is lacking in the NIR. Here we spatially allocate the NIR methane emissions for 2018 on a 0.1º x 0.1º grid (≈ 10 km x 10 km) for individual source sectors and subsectors, with further resolution by source type for the oil/gas sector, using an ensemble of national and provincial geospatial datasets and including facility-level information from Canada's Greenhouse Gas Reporting Program. The highest emissions are from oil/gas production and livestock in western Canada, and landfills in eastern Canada. We find 11 hotspots emitting more than 1 metric ton h-1 on the 0.1º x 0.1º grid. Oil sands mines in northeast Alberta contribute 3 of these hotspots even though oil sands contribute only 4% of national oil/gas emissions. Our gridded inventory shows large spatial differences with the EDGAR v5 inventory commonly used for inversions of atmospheric methane observations, which may reflect EDGAR's reliance on global geospatial datasets. Comparison of our spatially resolved inventory to atmospheric measurements in oil/gas production fields suggests that the NIR underestimates these emissions. We also find strong spatial overlap between oil/gas, livestock, and wetland emissions in western Canada that may complicate source attribution in inversions of atmospheric data.

Presentation of new geospatial datasets for renewable thermal energy systems modelling in Switzerland

Decarbonising heating and cooling energy buildings means going beyond individual buildings to geospatial analysis of regions and the country. This creates a need for higher resolution geospatial datasets to perform energy systems modelling. In this work we present open heating and cooling demand geospatial raster dataset produced as part of the FEEB&D research project. We discuss challenges in the production and sharing of such datasets and discuss future work towards more comprehensive databases for thermal energy modelling.

TOWARDS THE INTEGRATION OF AUTHORITATIVE AND OPENSTREETMAP GEOSPATIAL DATASETS IN SUPPORT OF THE EUROPEAN STRATEGY FOR DATA

Digital transformation is at core of Europe’s future and the importance of data is well highlighted by the recently published European strategy for data, which envisions the establishment of so-called European data spaces enabling seamless data flows across actors and sectors to ultimately boost the economy and generate innovation. Integrating datasets produced by multiple actors, including citizen-generated data, is a key objective of the strategy. This study focuses on OpenStreetMap (OSM), the most popular crowdsourced geographic information project, and is the first step towards an exploration of pros and cons of integrating its open-licensed data with authoritative geospatial datasets from European National Mapping Agencies. In contrast to previous work, which has only tested data integration at the local or regional level, an experiment was presented to integrate the national address dataset published by the National Land Survey (NLS) of Finland with the corresponding dataset from OSM. The process included the analysis of the two datasets, a mapping between their data models and a set of processing steps – performed using the open source QGIS software – to transform and finally combine their content. The resulting dataset confirms that, while addresses from the NLS are in general more complete across Finland, in some areas OSM addresses provide a higher detail and more up-to-date information to usefully complement the authoritative one. Whilst the analysis confirms that an integration between OSM and authoritative geospatial datasets is technically and semantically feasible, future work is needed to evaluate enablers and barriers that also exist at the legal and organisational level.

Improving spatial data in health geographics: a practical approach for testing data to measure children’s physical activity and food environments using Google Street View

Background Geographic information systems (GIS) are often used to examine the association between both physical activity and nutrition environments, and children’s health. It is often assumed that geospatial datasets are accurate and complete. Furthermore, GIS datasets regularly lack metadata on the temporal specificity. Data is usually provided ‘as is’, and therefore may be unsuitable for retrospective or longitudinal studies of health outcomes. In this paper we outline a practical approach to both fill gaps in geospatial datasets, and to test their temporal validity. This approach is applied to both district council and open-source datasets in the Taranaki region of Aotearoa New Zealand. Methods We used the ‘streetview’ python script to download historic Google Street View (GSV) images taken between 2012 and 2016 across specific locations in the Taranaki region. Images were reviewed and relevant features were incorporated into GIS datasets. Results A total of 5166 coordinates with environmental features missing from council datasets were identified. The temporal validity of 402 (49%) environmental features was able to be confirmed from council dataset considered to be ‘complete’. A total of 664 (55%) food outlets were identified and temporally validated. Conclusions Our research indicates that geospatial datasets are not always complete or temporally valid. We have outlined an approach to test the sensitivity and specificity of GIS datasets using GSV images. A substantial number of features were identified, highlighting the limitations of many GIS datasets.

University of Manitoba GISHub

This review provides an outline of the solution the University of Manitoba Libraries has implemented to integrate their ESRI Educational Site License. In looking at the tools available the project came to encompass the following:1. Semi-automated management and integration of UM ESRI site license using campus authentication methods2. Discovery and access point for proprietary and open researcher data3. Secure local environment for active-use geospatial datasets using ArcGIS EnterpriseThe following discusses the software specifics, use cases, and lessons learned in a Canadian academic library context.

Modeling Streamflow and Sediment Loads with a Photogrammetrically Derived UAS Digital Terrain Model: Empirical Evaluation from a Fluvial Aggregate Excavation Operation

Soil erosion monitoring is a pivotal exercise at macro through micro landscape levels, which directly informs environmental management at diverse spatial and temporal scales. The monitoring of soil erosion can be an arduous task when completed through ground-based surveys and there are uncertainties associated with the use of large-scale medium resolution image-based digital elevation models for estimating erosion rates. LiDAR derived elevation models have proven effective in modeling erosion, but such data proves costly to obtain, process, and analyze. The proliferation of images and other geospatial datasets generated by unmanned aerial systems (UAS) is increasingly able to reveal additional nuances that traditional geospatial datasets were not able to obtain due to the former’s higher spatial resolution. This study evaluated the efficacy of a UAS derived digital terrain model (DTM) to estimate surface flow and sediment loading in a fluvial aggregate excavation operation in Waukesha County, Wisconsin. A nested scale distributed hydrologic flow and sediment loading model was constructed for the UAS point cloud derived DTM. To evaluate the effectiveness of flow and sediment loading generated by the UAS point cloud derived DTM, a LiDAR derived DTM was used for comparison in consonance with several statistical measures of model efficiency. Results demonstrate that the UAS derived DTM can be used in modeling flow and sediment erosion estimation across space in the absence of a LiDAR-based derived DTM.

Geospatial Open Data Usage and Metadata Quality

The Open Government Data portals (OGD), thanks to the presence of thousands of geo-referenced datasets, containing spatial information are of extreme interest for any analysis or process relating to the territory. For this to happen, users must be enabled to access these datasets and reuse them. An element often considered as hindering the full dissemination of OGD data is the quality of their metadata. Starting from an experimental investigation conducted on over 160,000 geospatial datasets belonging to six national and international OGD portals, this work has as its first objective to provide an overview of the usage of these portals measured in terms of datasets views and downloads. Furthermore, to assess the possible influence of the quality of the metadata on the use of geospatial datasets, an assessment of the metadata for each dataset was carried out, and the correlation between these two variables was measured. The results obtained showed a significant underutilization of geospatial datasets and a generally poor quality of their metadata. In addition, a weak correlation was found between the use and quality of the metadata, not such as to assert with certainty that the latter is a determining factor of the former.