Showing papers in "Computers, Environment and Urban Systems in 2021"

TL;DR: In this article, a patch-generating land use simulation (PLUS) model is proposed that integrates a land expansion analysis strategy and a cellular automata model based on multi-type random patch seeds to understand the drivers of land expansion and investigate the landscape dynamics in Wuhan, China.

TL;DR: In this paper, the authors analyzed the changes in micromobility usage before and during the lockdown period exploiting high-resolution micro-mobility trip data collected in Zurich, Switzerland, and evaluated and compared from the perspective of space, time and semantics.

TL;DR: A geo-semantic analysis framework was introduced in this study to model the relationship between traffic interaction and urban functions at the road segment level and shows that the proposed methods, with relative less loss and high accuracy, outperform other comparative methods for classifying urban functions in Beijing, China.

TL;DR: The results show that Chinese tourists visiting Nordic countries are often experienced in traveling, and Iceland showcases stronger, compared to the other Nordic countries, community independence and small world effect, while in cold season, they tend to choose destinations with higher chances for spotting the northern lights.

TL;DR: A deep neural network approach to detect submerged stop signs in photos taken from flooded roads and intersections is presented, coupled with Canny edge detection and probabilistic Hough transform to calculate pole length and estimate floodwater depth.

TL;DR: A Forward Feature Selection algorithm with Random Forest (FFS-RF) is couples a transition index map, which then guides the spatial allocation for the extrapolation of urban growth using a Cellular Automata model to extrapolate that Tehran, Karaj, and their adjacent cities will interconnect spatially to form a gigantic city-region.

TL;DR: There is evidence at the micro level that less place management and higher accessibility can increase the risk of drug activities, and street-view variables may be generally applicable to other types of crime research in the context of the micro built environment.

TL;DR: In this paper, the role of urban shading created by trees and buildings, focusing on the effects of shade extent and location on land surface temperature (LST) mitigation, is examined. But with little attention to the shading cast by 3D objects, such as buildings and trees, it is, however, known that shades are particularly relevant for controlling summertime temperatures.

TL;DR: A Geographic Data Science framework is developed that transforms the Foursquare check-in locations and user origin-destination flows data into knowledge about the emerging forms and characteristics of cities' neighbourhoods, and enables the profiling and comparison of functional neighbourhoods, based on human dynamics and their contexts, across the sample of global cities.

TL;DR: In this paper, the authors used thousands of pedestrian trajectories obtained from GPS signals to construct a desirability index for streets in Boston, which captures pedestrians' willingness to deviate from their shortest path and provides a measure of the scenic and experience value provided by different parts of the city.

TL;DR: In this paper, the authors review the common types of LocBigData: mobile phone network data, GPS data, location-based social media data, LBS usage/log data, smart card travel data, beacon log data (WiFi or Bluetooth), and camera imagery data.

TL;DR: The results support the feasibility of estimating congestion zones and time-varying TTIs on a large road network from FCD, with the application in urban planning andTime-dependent routing operations due to: significant reduction in the data volume without notable quality loss, and meaningful reduction inThe pre-processing computation time.

TL;DR: In this article, a 3D city model was used to identify suitable farming micro-locations (level and orientation) in residential buildings for growing vegetables in urban residential buildings, and the results showed that the vertical spaces of these buildings comprising outdoor corridors, facades and windows receive sufficient photosynthetically active radiation (PAR) for growing food crops.

TL;DR: An empirical assessment of the sensitivity of GSV-based streetscape measures and their variation patterns shows that the measurement outcomes can vary substantially with changes in GSV acquisition parameter settings, specifically spacing and direction.

TL;DR: The results suggest that among all measures under the three GIS-based approaches, the selection of distance thresholds and transport modes matter more to accessibility measures than the destination choices.

TL;DR: The proposed methodology described in this paper is transferable to other datasets, levels, and regions, due to the growing availability of open statistical and satellite data and derived products, and discusses the limitations and needed considerations when conducting such studies.

TL;DR: It is found that higher traffic speeds and crime rates are negatively associated with playability, while higher scores for perception of beauty are positively associated withPlayability.

TL;DR: A state-of-the-art tree ensemble model - extreme gradient boosting tree (XGBoost) - is applied to handle the large-scale features and hourly traffic volume samples and spatial dependency among road segments is taken into account in the proposed model using graph theory.

TL;DR: In this article, the authors propose an approach for delineating urban functional use at the scale of the Lower Layer Super Output Area (LSOA) in Greater London by integrating the Doc2Vec model, a neural network embedding method commonly used in natural language processing for vectoring words and documents from their context.

TL;DR: In this article, the authors used a detailed spatial metric-based approach and panel regression to quantify the relationships between urban development patterns and congestion in 98 US urban areas from 2001 to 2011, and found that the abundance and spatial configuration of urban land uses were correlated with traffic congestion.

TL;DR: This study presents a case study of how model transparency and explanation can be generated using the Local Interpretable Model-Agnostic Explanation (LIME) to support advanced machine learning techniques in the transportation energy field.

TL;DR: A Cellular Automata-based Dynamic Route Optimization (CADRO) algorithm is developed to identify the dynamic flood evacuation route (FER), where the hydrodynamics, topography and human response time are incorporated, and it is anticipated that the proposed CADRO can be greatly beneficial to the urban flooding risk management.

TL;DR: A novel multi-chain multi-objective MCMC (mc-MO-MCMC) CA model to simulate LUCC is introduced, which should efficiently help to simulate a trade-off among multiple and, possibly, conflicting land use change dynamics at once.

TL;DR: For portable sensing to become a prevalent and legitimate methodological approach, it is essential to have conceptually strong study designs that are grounded in suitable ethical procedures and comply with data protection regulations.

TL;DR: It was found that urban green spaces generally cool the environment, although, the cooling potential of the different green types differs and the spatial extension of detected cooling was found small, however, it would increase during the future, especially in the case of grasslands.

TL;DR: A series of quantitative evaluations based on a case study demonstrated the ability and potential of the framework for extracting bikeway road information to enrich the existing OSM cycling road data.

TL;DR: In this article, the authors proposed a workflow to simulate the urban spatial structure with spatial interaction as a part of the planning support system, which can help urban planners and governments understand their urban policy regarding urban polycentricity.

TL;DR: The ability to assess data quality enables the uncertainty associated with crowdsourced social media data to be estimated, which allows this type of data to supplement conventional observations, and hence improve flood management activities.

TL;DR: In this article, a space-time analytical framework is proposed to identify and describe 31 road-constrained AOIs in terms of their spatiotemporal distribution and contextual characteristics.

TL;DR: An assessment of current and future flood risk in five countries of mainland Southeast Asia, using a new modeling approach that accounts for differences in urban land systems shows that expected annual flood damage will increase in all countries and in both scenarios.