A Spatial Hazard-Based analysis for modelling vehicle selection in station-based carsharing systems

2016 ◽  
Vol 72 ◽  
pp. 130-142 ◽  
Author(s):  
Sisi Jian ◽  
Taha Hossein Rashidi ◽  
Kasun P. Wijayaratna ◽  
Vinayak V. Dixit
Keyword(s):  
Spatial Hazard

Spatial hazard analysis and prediction on rainfall-induced landslide using GIS

2003 ◽  
Vol 48 (7) ◽  
pp. 703-708 ◽  
Author(s):  
Hengxing Lan ◽  
Faquan Wu ◽  
Chenghu Zhou ◽  
Lingjuan Wang
Keyword(s):  
Hazard Analysis ◽  
Spatial Hazard

scholarly journals Rapid Flood Progress Monitoring in Cropland with NASA SMAP

2019 ◽  
Vol 11 (2) ◽  
pp. 191 ◽  
Author(s):  
Md. Rahman ◽  
Liping Di ◽  
Eugene Yu ◽  
Li Lin ◽  
Chen Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Progress Monitoring ◽  
Soil Porosity ◽  
Optical Remote Sensing ◽  
Model Driven ◽  
Coarse Spatial Resolution ◽  
Direct Indication ◽  
Spatial Hazard ◽  
Flood Maps

Research in different agricultural sectors, including in crop loss estimation during flood and yield estimation, substantially rely on inundation information. Spaceborne remote sensing has widely been used in the mapping and monitoring of floods. However, the inability of optical remote sensing to cloud penetration and the scarcity of fine temporal resolution SAR data hinder the application of flood mapping in many cases. Soil Moisture Active Passive (SMAP) level 4 products, which are model-driven soil moisture data derived from SMAP observations and are available at 3-h intervals, can offer an intermediate but effective solution. This study maps flood progress in croplands by incorporating SMAP surface soil moisture, soil physical properties, and national floodplain information. Soil moisture above the effective soil porosity is a direct indication of soil saturation. Soil moisture also increases considerably during a flood event. Therefore, this approach took into account three conditions to map the flooded pixels: a minimum of 0.05 m3m−3 increment in soil moisture from pre-flood to post-flood condition, soil moisture above the effective soil porosity, and the holding of saturation condition for the 72 consecutive hours. Results indicated that the SMAP-derived maps were able to successfully map most of the flooded areas in the reference maps in the majority of the cases, though with some degree of overestimation (due to the coarse spatial resolution of SMAP). Finally, the inundated croplands are extracted from saturated areas by Spatial Hazard Zone areas (SHFA) of Federal Emergency Management Agency (FEMA) and cropland data layer (CDL). The flood maps extracted from SMAP data are validated with FEMA-declared affected counties as well as with flood maps from other sources.

scholarly journals Separating spatial search and efficiency rates as components of predation risk

2012 ◽  
Vol 279 (1747) ◽  
pp. 4626-4633 ◽  
Author(s):  
Nicholas J. DeCesare
Keyword(s):  
Predation Risk ◽  
Resource Selection ◽  
Population Level ◽  
Search Rate ◽  
Proportional Hazard ◽  
Predator Prey ◽  
Multiple Components ◽  
Predation Efficiency ◽  
Aggregative Response ◽  
Spatial Hazard

Predation risk is an important driver of ecosystems, and local spatial variation in risk can have population-level consequences by affecting multiple components of the predation process. I use resource selection and proportional hazard time-to-event modelling to assess the spatial drivers of two key components of risk—the search rate (i.e. aggregative response) and predation efficiency rate (i.e. functional response)—imposed by wolves ( Canis lupus ) in a multi-prey system. In my study area, both components of risk increased according to topographic variation, but anthropogenic features affected only the search rate. Predicted models of the cumulative hazard, or risk of a kill, underlying wolf search paths validated well with broad-scale variation in kill rates, suggesting that spatial hazard models provide a means of scaling up from local heterogeneity in predation risk to population-level dynamics in predator–prey systems. Additionally, I estimated an integrated model of relative spatial predation risk as the product of the search and efficiency rates, combining the distinct contributions of spatial heterogeneity to each component of risk.

scholarly journals Impact of information presentation on interpretability of spatial hazard information: Lessons from a study in avalanche safety

2021 ◽  
Author(s):  
Kathryn C. Fisher ◽  
Pascal Haegeli ◽  
Patrick Mair
Keyword(s):  
Online Survey ◽  
Linear Mixed Effects ◽  
Avalanche Hazard ◽  
Spatial Hazard ◽  
Generalized Linear Mixed Effects ◽  
Avalanche Warning ◽  
Ranking Tasks ◽  
Warning Services ◽  
The Impact ◽  
Completion Times

Abstract. Avalanche warning services publish avalanche condition reports, often called avalanche bulletins, to help backcountry recreationists make informed risk management decisions about when and where to travel in avalanche terrain. To be successful, the information presented in bulletins must be properly understood and applied prior to entering avalanche terrain. However, few avalanche bulletin elements have been empirically tested for their efficacy in communicating hazard information. The objective of this study is to explicitly test the effectiveness of three different graphics representing the aspect and elevation of avalanche problems on users’ ability to apply the information. To address this question, we conducted an online survey that presented participants with one of three graphic renderings of avalanche problem information and asked them to rank a series of route options in order of their exposure to the described hazard. Following completion of route ranking tasks, users were presented with all three graphics and asked to rate how effective they thought the graphics were. Our analysis dataset included responses from 3,056 backcountry recreationists with a variety of backgrounds and avalanche safety training levels. Using a series of generalized linear mixed effects models, our analysis shows that a graphic format that combines the aspect and elevation information for each avalanche problem is the most effective graphic for helping users understand the avalanche hazard conditions because it resulted in higher success in picking the correct exposure ranking, faster completion times, and was rated by users to be the most effective. These results are consistent with existing research on the impact of graphics on cognitive load and can be applied by avalanche warning services to improve the communication of avalanche hazard to readers of their avalanche bulletins.

The Racially Unequal Impacts of Disasters and Federal Recovery Assistance on Local Self-Employment Rates

2021 ◽  
pp. 232949652110288
Author(s):  
Asia Bento ◽  
James R. Elliott
Keyword(s):  
Local Property ◽  
The United States ◽  
Change Score ◽  
Census Bureau ◽  
Racial Inequalities ◽  
Self Employment ◽  
Spatial Hazard ◽  
Employment Rates ◽  
Social Vulnerabilities ◽  
White Workers

This study examines racial inequalities in changing self-employment rates associated with natural hazard impacts and federal recovery assistance in ethnoracially diverse metropolitan counties between 2000 and 2010. It advances the viewpoint that such inequalities can stem from hoarded opportunities tied to white privilege in addition to commonly highlighted social vulnerabilities tied to racial inequities and exclusion. To test that proposition, we conduct change-score analyses using county-level data from the US Census Bureau, the Spatial Hazard Events and Losses Database for the United States, and the Federal Emergency Management Agency. Results indicate that (a) overall, self-employment rates increase with local property damages from natural hazards, especially among white and Latino workers; (b) those increases are largely explained by the amount of federal public assistance received for disaster recovery, not property damages themselves; and (c) white workers experience the most positive and consistent increases in self-employment from federal recovery assistance. Implications for understanding racial inequities stemming from current and future disasters and government assistance are discussed.

scholarly journals Creating Immersive Virtual Environments Based on Open Geospatial Data and Game Engines

2021 ◽  
Author(s):  
Julian Keil ◽  
Dennis Edler ◽  
Thomas Schmitt ◽  
Frank Dickmann
Keyword(s):  
Dimensional Space ◽  
Three Dimensional ◽  
Geospatial Data ◽  
Game Engine ◽  
Advantages And Disadvantages ◽  
Elevation Data ◽  
Game Engines ◽  
3D Environments ◽  
Spatial Hazard ◽  
Game Developers

AbstractModern game engines like Unity allow users to create realistic 3D environments containing terrains as well as natural and artificial objects easily and swiftly. In addition, recent advances of game engine capabilities enable effortless implementation of virtual reality (VR) compatibility. 3D environments created with VR compatibility can be experienced from an egocentric and stereoscopic perspective that surpasses the immersion of the ‘classical’ screen-based perception of 3D environments. Not only game developers benefit from the possibilities provided by game engines. The ability to use geospatial data to shape virtual 3D environments opens a multitude of possibilities for geographic applications, such as construction planning, spatial hazard simulations or representation of historical places. The multi-perspective, multimodal reconstruction of three-dimensional space based on game engine technology today supports the possibility of linking different approaches of geographic work more closely. Free geospatial data that can be used for spatial reconstructions is provided by numerous national and regional official institutions. However, the file format of these data sources is not standardized and game engines only support a limited number of file formats. Therefore, format transformation is usually required to apply geospatial data to virtual 3D environments. This paper presents several workflows to apply digital elevation data and 3D city model data from OpenStreetMap and the Open.NRW initiative to Unity-based 3D environments. Advantages and disadvantages of different sources of geospatial data are discussed. In addition, implementation of VR compatibility is described. Finally, benefits of immersive VR implementation and characteristics of current VR hardware are discussed in the context of specific geographic application scenarios.

scholarly journals On the relevance of extremal dependence for spatial statistical modelling of natural hazards

2018 ◽  
Author(s):  
Laura C. Dawkins ◽  
David B. Stephenson
Keyword(s):  
Turbulent Flows ◽  
Extreme Values ◽  
Heat Waves ◽  
Statistical Modelling ◽  
Asymptotic Dependence ◽  
Efficient Simulation ◽  
Geostatistical Models ◽  
Spatial Hazard ◽  
Spatial Locations ◽  
Extremal Properties

Abstract. Natural hazard loss portfolios with exposure over a region are sensitive to the dependency between extreme values of the key hazard variable at different spatial locations. It is therefore important to correctly identify and quantify dependency to avoid poor quantification of risk. This study demonstrates how bivariate extreme value tail dependency methods can be used together in a novel way to explore and quantify extremal dependency in spatial hazard fields. A relationship between dependency and loss is obtained by deriving how the probability distribution of conceptual loss depends on the tail dependency coefficient. The approaches are illustrated by applying them to 6103 historical European windstorm footprints (spatial maps of 3-day maximum gust speeds). We find there is little evidence of asymptotic extremal dependency in windstorm footprints. Furthermore, empirical extremal properties and conceptual loss distributions between pairs of locations are shown to be well reproduced using Gaussian copulas but not by extremally-dependent models such as Gumbel copulas. It is conjectured that the lack of asymptotic dependence is a generic property of turbulent flows, which may extend to other spatially continuous hazards such as heat waves and air pollution. These results motivate the potential of using Gaussian process (geostatistical) models for efficient simulation of hazard fields.

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