scholarly journals Geo-referencing bird-window collisions for targeted mitigation

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4215 ◽  
Author(s):  
R. Scott Winton ◽  
Natalia Ocampo-Peñuela ◽  
Nicolette Cagle
Keyword(s):  
Spatial Analysis ◽  
Urban Areas ◽  
Complex Geometries ◽  
Gps Data ◽  
University Campus ◽  
Compass Direction ◽  
Bird Mortality ◽  
Conservation Concern ◽  
Large Building ◽  
Bird Collisions

Bird collisions with windows are an important conservation concern. Efficient mitigation efforts should prioritize retrofitting sections of glass exhibiting the highest mortality of birds. Most collision studies, however, record location meta-data at a spatial scale too coarse (i.e., compass direction of facing façade) to be useful for large buildings with complex geometries. Through spatial analysis of three seasons of survey data at a large building at a university campus, we found that GPS data were able to identify collision hotspots while compass directions could not. To demonstrate the broad applicability and utility of this georeferencing approach, we identified collision hotspots at two additional urban areas in North America. The data for this latter exercise were collected via the citizen science database, iNaturalist, which we review for its potential to generate the georeferenced data necessary for directing building retrofits and mitigating a major source of anthropogenic bird mortality.

scholarly journals Prediction of Socio-Economic Indicators for Urban Planning Using VHR Satellite Imagery and Spatial Analysis

2020 ◽  
Vol 12 (11) ◽  
pp. 1730 ◽  
Author(s):  
Gebhard Warth ◽  
Andreas Braun ◽  
Oliver Assmann ◽  
Kevin Fleckenstein ◽  
Volker Hochschild
Keyword(s):  
Spatial Analysis ◽  
Urban Planning ◽  
Urban Areas ◽  
Residential Buildings ◽  
Dynamic Change ◽  
Training Data ◽  
Infrastructure Planning ◽  
Economic Point ◽  
Steady Growth ◽  
Building Typology

Ongoing urbanization leads to steady growth of urban areas. In the case of highly dynamic change of municipalities, due to the rates of change, responsible administrations often are challenged or struggle with capturing present states of urban sites or accurately planning future urban development. An interest for urban planning lies on socio-economic conditions, as consumption and production of disposable goods are related to economic possibilities. Therefore, we developed an approach to generate relevant parameters for infrastructure planning by means of remote sensing and spatial analysis. In this study, the single building defines the spatial unit for the parameters. In the case city Belmopan (Belize), based on WorldView-1 data we manually define a city covering building dataset. Residential buildings are classified to eight building types which are locally adapted to Belmopan. A random forest (RF) classifier is trained with locally collected training data. Through household interviews focusing on household assets, income and educational level, a socio-economic point (SEP) scaling is defined, which correlates very well with the defined building typology. In order to assign socio-economic parameters to the single building, five socio-economic classes (SEC) are established based on SEP statistics for the building types. The RF building type classification resulted in high accuracies. Focusing on the three categories to describe residential socio-economic states allowed high correlations between the defined building and socio-economic points. Based on the SEP we projected a citywide residential socio-economic building classification to support supply and disposal infrastructure planning.

Pollinator gardens more than triple in visitation rate and diversity of flower-visiting insects than other ornamental plantings in Kingston, Ontario

2018 ◽  
Author(s):  
Marika Vogelzang
Keyword(s):  
Urban Areas ◽  
Unit Area ◽  
The Other ◽  
Individual Plant ◽  
University Campus ◽  
Pollinator Visitation ◽  
Visitation Rate ◽  
Queen's University ◽  
Flower Visiting ◽  
Pollinator Populations

In this study I determined the effectiveness of pollinator gardens by testing if visitation rate and diversity of flower-visiting insects is higher in pollinator gardens compared to other ornamental plantings. I observed pollinator visitation for individual plant taxa, per unit area, in three different pollinator gardens, eight ornamental gardens and eight ornamental planters on the Queen’s University campus in Kingston, Ontario, Canada. Visitation was about 4- times higher in pollinator gardens compared to the other two ornamental garden types and visitor richness (the number of types of pollinators) in pollinator gardens was about 6- times higher compared to ornamental gardens, and about 3- times higher compared toornamental planters. The results of this study conclude that the planting of pollinator gardens is an effective way of supporting pollinator populations in urban areas.

scholarly journals CIM-Powered Multi-Hazard Simulation Framework Covering both Individual Buildings and Urban Areas

2020 ◽  
Vol 12 (12) ◽  
pp. 5059
Author(s):  
Xinzheng Lu ◽  
Donglian Gu ◽  
Zhen Xu ◽  
Chen Xiong ◽  
Yuan Tian
Keyword(s):  
Urban Areas ◽  
Hazard Analysis ◽  
Practical Method ◽  
High Fidelity ◽  
University Campus ◽  
Simulation Framework ◽  
Multi Scale ◽  
Scientific Simulations ◽  
Improve Analysis ◽  
Disaster Scenario

To improve the ability to prepare for and adapt to potential hazards in a city, efforts are being invested in evaluating the performance of the built environment under multiple hazard conditions. An integrated physics-based multi-hazard simulation framework covering both individual buildings and urban areas can help improve analysis efficiency and is significant for urban planning and emergency management activities. Therefore, a city information model-powered multi-hazard simulation framework is proposed considering three types of hazards (i.e., earthquake, fire, and wind hazards). The proposed framework consists of three modules: (1) data transformation, (2) physics-based hazard analysis, and (3) high-fidelity visualization. Three advantages are highlighted: (1) the database with multi-scale models is capable of meeting the various demands of stakeholders, (2) hazard analyses are all based on physics-based models, leading to rational and scientific simulations, and (3) high-fidelity visualization can help non-professional users better understand the disaster scenario. A case study of the Tsinghua University campus is performed. The results indicate the proposed framework is a practical method for multi-hazard simulations of both individual buildings and urban areas and has great potential in helping stakeholders to assess and recognize the risks faced by important buildings or the whole city.

Robust Positioning and Navigation of a Mobile Robot in an Urban Environment Using a Motion Estimator

Robotica ◽  
2019 ◽  
Vol 37 (08) ◽  
pp. 1320-1331 ◽  
Author(s):  
Jongwoo An ◽  
Jangmyung Lee
Keyword(s):  
Mobile Robot ◽  
Urban Environment ◽  
Global Positioning System ◽  
Short Term Memory ◽  
Fault Detection And Isolation ◽  
Gps Data ◽  
University Campus ◽  
Short Term ◽  
Global Positioning ◽  
Minimum Number

SummaryRobust positioning and navigation of a mobile robot in an urban environment is implemented by fusing the Global Positioning System (GPS) and Inertial Navigation System (INS) data with the aid of a motion estimator. To select and isolate malicious satellite signals and guarantee the minimum number of GPS signals for the localization, an enhanced fault detection and isolation (FDI) algorithm with a short-term memory has been developed in this research. When there are sufficient satellite signals for positioning, the horizontal dilution of precision (HDOP) has been applied for selecting the best four satellite signals to localize the mobile robot. Then, the GPS data are fused with INS data by a Kalman filter (KF) for a straight path and a curved motion estimator (CME) for a curved path. That is, the INS data are properly fused to the GPS data through the KF or CME process. To verify the effectiveness of the proposed algorithm, experiments using a mobile robot have been carried out on a university campus.

scholarly journals Geovisualization and Spatial Analysis of Infant Mortality and Preterm Birth in Ohio, 2008-2015: Opportunities to Enhance Spatial Thinking

2020 ◽  
Vol 135 (4) ◽  
pp. 472-482
Author(s):  
Elisabeth Dowling Root ◽  
Emelie D. Bailey ◽  
Tyler Gorham ◽  
Christopher Browning ◽  
Chi Song ◽  
...  
Keyword(s):  
Public Health ◽  
Preterm Birth ◽  
Spatial Analysis ◽  
Infant Mortality ◽  
Spatial Patterns ◽  
Urban Areas ◽  
Vital Statistics ◽  
Infant Mortality Rate ◽  
Spatial Inequalities ◽  
Geographic Clustering

Objectives Geovisualization and spatial analysis are valuable tools for exploring and evaluating the complex social, economic, and environmental interactions that lead to spatial inequalities in health. The objective of this study was to describe spatial patterns of infant mortality and preterm birth in Ohio by using interactive mapping and spatial analysis. Methods We conducted a retrospective cohort study using Ohio vital statistics records from 2008-2015. We geocoded live births and infant deaths by using residential address at birth. We used multivariable logistic regression to adjust spatial and space–time cluster analyses that examined the geographic clustering of infant mortality and preterm birth and changes in spatial distribution over time. Results The overall infant mortality rate in Ohio during the study period was 6.55 per 1000 births; of 1 097 507 births, 10.3% (n = 112 552) were preterm. We found significant geographic clustering of both infant mortality and preterm birth centered on large urban areas. However, when known demographic risk factors were taken into account, urban clusters disappeared and, for preterm birth, new rural clusters appeared. Conclusions Although many public health agencies have the capacity to create maps of health outcomes, complex spatial analysis and geovisualization techniques are still challenging for public health practitioners to use and understand. We found that actively engaging policymakers in reviewing results of the cluster analysis improved understanding of the processes driving spatial patterns of birth outcomes in the state.

Investigating the Potential of Urban Land Uses to Support Sustainable Energy Principles Using a Spatial Analysis Model

2015 ◽  
Author(s):  
Sherika Gibson
Keyword(s):  
Land Use ◽  
Spatial Analysis ◽  
Urban Areas ◽  
Sustainable Energy ◽  
Global Scale ◽  
Economic Security ◽  
Sustainable Communities ◽  
Renewable Energy Resources ◽  
Analysis Model ◽  
Essential Components

The underpinning elements of sustainable communities are centered on economic security, renewable energy resources, reliable infrastructure, and ecological protection. The geomorphology of urban areas is altered due to human activity leading to change in land use characteristics and resources availability. Research has shown that global population has increased drastically over the last three decades resulting in depleted efficiency of regional resources. Because of this, obtaining sustainable energy platforms is a world-wide concern. In evaluating the ability of urban communities to support sustainable elements, both spatial and temporal influences must be considered. As a result a spatial analysis model will be used to assess the geomorphological and land use aspects of urban watersheds to support sustainable communities’ platform. These data will provide insight in essential components in need of environmental restoration that contribute to future renewable resources which can then be applied on a global scale.

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