ABSTRACT Research has developed numerous algorithms to simplify building data. Each algorithm has strengths and weaknesses in addressing shape characteristics, but no single algorithm can appropriately simplify all buildings. This study proposes a hybrid approach that identifies the best simplified representation of a building among four existing algorithms. The proposed approach applies the four algorithms

ABSTRACT Traditional landscape photographs reaching back until the second half of the nineteenth century represent a valuable image source for the study of long-term landscape change. Due to the oblique perspective and the lack of geographical reference, landscape photographs are hardly used for quantitative research. In this study, oblique landscape photographs from the Norwegian landscape monitoring

ABSTRACT Though GPS-based human trajectory data have been commonly used in travel surveys and human mobility studies, missing data or data gaps that are intrinsically relevant to research reliability remain a critical and challenging issue. This study proposes a novel framework for imputing data gaps based on frequent-pattern mining and time geography, which allows for considering spatio-temporal travel

(2021). Multiple-aspect analysis of semantic trajectories(MASTER). International Journal of Geographical Information Science. Ahead of Print.

ABSTRACT Today, various methods are applied to analyze the data collected through participatory mapping, including public participation GIS (PPGIS), participatory GIS (PGIS), and collecting volunteered geographic information (VGI). However, these methods lack an organized framework to describe and guide their systematic applications. Majority of the published articles on participatory mapping apply

ABSTRACT In everyday communication, where-questions are answered by place descriptions. To answer where-questions automatically, computers should be able to generate relevant place descriptions that satisfy inquirers’ information needs. Human-generated answers to where-questions constructed based on a few anchor places that characterize the location of inquired places. The challenge for automatically

ABSTRACT Identifying urban boundaries involves analysing both the functional and the morphological aspects of urban systems. In this paper, we adopt a purely morphological approach and compare three methods for the morphological delineation of cities. Each method avoids using any predefined quantified threshold (size, distance, built density, etc.) to detect crucial discontinuities in space. The first

ABSTRACT In this paper, we represent (moving) point configurations along a curved directed line qualitatively by means of a system of relational symbols based on two distance descriptors: one representing distance along the curved directed line and the other representing signed orthogonal distance to the curved directed line. The curved directed line represents the direction of the movement of interest

ABSTRACT Natural disasters have caused substantial economic losses and numerous casualties. The demand analysis of relief supplies is the premise and basis for efficient relief operations after disasters. With the widespread use of social media, it has become a vital channel for people to report their demand for relief supplies and provides a way to obtain information on disaster areas. Therefore,

ABSTRACT Understanding the influence mechanisms of dockless bike-sharing usage is essential for land use planning and bike scheduling strategy implementation. Although various studies have been carried out to explore the impact of built environment (BE) factors on bike-sharing usage, few studies have examined the modifiable areal unit problem (MAUP). Moreover, previous studies mainly focused on the

ABSTRACT Map construction algorithms attempt to derive a spatial graph representing a road network from GPS-sampled movement trajectories. Existing methods commonly use trajectories without considering the specific sampling methodology. Hence, the movement information is not preserved in the map construction results. The proposed map-construction method considers the particularities of the sampling

ABSTRACT As the essence of urban spatiotemporal interaction systems, hubs and centers empower cities to enhance socioeconomic prosperity and sustainability. However, a city manifests a time-evolving spatial interaction network with latent temporal interactions and irregular spatial partitions. This phenomenon is termed the spatiotemporal inconsistency problem. The aggregate, single-layer network model

ABSTRACT This paper explores a class of qualitative-geometric relations between disjoint regions, embedded in the surface of a sphere or in the plane. These relations combine topological information about the configuration of the regions themselves as well as of the geometric Voronoi regions surrounding them. The method uses maptrees to construct a rigorous and exhaustive framework for n-ary relations

ABSTRACT The goal of this work was to evaluate if routinely collected but seldom used airborne lidar metadata – ‘point attribute data’ (PAD) – analyzed using machine learning/artificial intelligence can improve extraction of shallow-water (less than 20 m) bathymetry from lidar point clouds. Extreme gradient boosting (XGB) models relating PAD to an existing bathymetry/not bathymetry classification were

ABSTRACT Given a grid of cells, each having a value indicating its cost per unit area, a variant of the least-cost path problem is to find a corridor of a specified width connecting two termini such that its cost-weighted area is minimized. A computationally efficient method exists for finding such corridors, but as is the case with conventional raster-based least-cost paths, their incremental orientations

ABSTRACT The growth of georeferenced data sources calls for advanced matching methods to improve the reliability of geospatial data processing, such as map conflation. Existing matching methods mainly focus on similarity measures at the entity scale or area scale. A measure that combines entity-scale and area-scale similarities can provide sound matching results under various circumstances. In this

ABSTRACT The past 25 years have seen a proliferation of interest in GIS among humanists and humanistic social scientists. Under various banners – historical GIS, qualitative and mixed methods GIS, spatial and digital history, digital humanities, spatial humanities or geohumanities – researchers have developed new ways to include qualitative data within the framework of GIS. At the same time, social

ABSTRACT Fine-grained inner-annual population data are instrumental in climate change response, resource allocation, and epidemic control. However, such data are currently scarce due to the lack of human-related indicators with both high temporal resolution and long-term coverage that can be used in the process of population spatialization. Here, we estimate monthly 1-km gridded population distribution

ABSTRACT Digital Elevation Models (DEMs) are important datasets for modelling the line of sight, such as radio signals, sound waves and human vision. These are commonly analyzed using rotational sweep algorithms. However, such algorithms require large numbers of memory accesses to 2D arrays which, despite being regular, result in poor data locality in memory. Here, we propose a new methodology called

ABSTRACT Cellular Automata (CA) models have become the most commonly used tool for simulating urban expansion. To improve the accuracy of CA models, various driving factors like spatial proximity and neighbourhood effects have been explored in previous studies, but the inclusion of these factors does not address the directional differences in urban expansion. To address this issue, this study develops

ABSTRACT The land-use optimization involves divisions of land into subregions to obtain spatial configuration of compact subregions and desired connections among them. Computational geometry-based algorithms, such as Voronoi diagram, are known to be efficient and suitable for iterative design processes to achieve land-use optimization. However, such algorithms assume that generating point positions

ABSTRACT The advent of GPS technologies generates location data-streams and accentuates the importance of developing practical tools that can process and analyze the vast amounts of location data at a given moment in a meaningful way. Profiling the trajectory of a moving object with respect to the trajectories of its surrounding objects, for example, can elicit its mobility behaviour and analyze it

ABSTRACT Regions of anomalous spatial co-locations (ROASCs) are regions where co-locations between two different features are significantly stronger or weaker than expected. ROASC discovery can provide useful insights for studying unexpected spatial associations at regional scales. The main challenges are that the ROASCs are spatially arbitrary in geographic shape and the distributions of spatial features

ABSTRACT Various methods have been proposed to detect the base locations of individuals, with their geo-tagged social media data. However, a common challenge relating to base-location detection methods (BDMs) is that, the rare availability of ground-truth data impedes the method assessment of accuracy and robustness, thus undermining research validity and reliability. To address this challenge, we

ABSTRACT Historical maps contain rich geographic information about the past of a region. They are sometimes the only source of information before the availability of digital maps. Despite their valuable content, it is often challenging to access and use the information in historical maps, due to their forms of paper-based maps or scanned images. It is even more time-consuming and labor-intensive to

ABSTRACT Indoor space, where humans spend 80% of their lives, is subject to frequent out-of-hospital cardiac arrest (OHCA). Optimizing the spatial deployment of automated external defibrillators (AEDs) has the potential to improve OHCA survival rate. Complex indoor space is typically divided by hard barriers into multiple discrete subspaces across floors. Commonly used distance measurements, such as

ABSTRACT Communicating and understanding climate induced environmental changes can be challenging, especially using traditional representations such as graphs, maps or photos. Immersive visualizations and experiences offer an intuitive, visceral approach to otherwise rather abstract concepts, but creating them scientifically is challenging. In this paper, we linked ecological modeling, procedural modeling

ABSTRACT The use of digital representations of physical objects allows to simulate phenomena and predict behaviours. The representativeness of a model is based on the congruency between the code, the survey and the modelling strategies. In terms of physical space, two important approaches are the Geographical Information Systems (GIS) and Building Information Modelling (BIM). GIS approach is intended

ABSTRACT As the number of vehicles and devices equipped with GPS technology has grown explosively, an urgent need has arisen for time- and space-efficient data structures to represent their trajectories. The most commonly desired queries are the following: queries about an object’s trajectory, range queries, and nearest neighbor queries. In this paper, we consider that the objects can move freely and

ABSTRACT Low-sampling-rate floating car data (FCD) are more challenging than those with high-sampling-rate FCD for map matching (MM) algorithms. Some MM algorithms for low-sampling-rate FCD lack sufficient efficiency nor accuracy, especially related to complex urban road networks. This paper proposes a new method named the trajectory restoration algorithm, which is based on geometry MM algorithms to

ABSTRACT Virtual scenes can present rich and clear disaster information, which can significantly improve the level of public disaster perception. However, existing methods for constructing scenes of debris flow disasters have some deficiencies. First, the construction process does not consider public knowledge, which makes it difficult for the constructed scenes to meet the requirements of the public

ABSTRACT Understanding the characteristics of the rapidly evolving geospatial software ecosystem in the United States is critical to enable convergence research and education that are dependent on geospatial data and software. This paper describes a survey approach to better understand geospatial use cases, software and tools, and limitations encountered while using and developing geospatial software

ABSTRACT The automatic generation of road networks from GPS tracks is a challenging problem that has been receiving considerable attention in the last years. Although dozens of methods have been proposed, current techniques suffer from two main shortcomings: the quality of the produced road networks is still far from those produced manually, and the methods are slow, making them not scalable to large

ABSTRACT Land-use maps are instrumental to inform urban planning and environmental research. Street view images (SVIs) have shown great potential for automated land-use classification for land-use mapping. However, previous studies overlooked SVI-derived location contextual information that may help improve land-use classification. This study proposes a novel land-use classification method that synthesizes

ABSTRACT The majority of spatial data provided as Volunteered Geographic Information (VGI) are roads and other linear map features. Such data have been widely used in routing and navigation, road network update, emergency response, urban planning and more. Due to the lack of cartographic standards and issues with volunteer credibility, the quality of VGI linear features remains a concern and could

ABSTRACT The search for the most appropriate GIS data model to integrate, manipulate and analyse spatio-temporal data raises several research questions about the conceptualisation of geographic spaces. Although there is now a general consensus that many environmental phenomena require field and object conceptualisations to provide a comprehensive GIS representation, there is still a need for better

ABSTRACT Modelling movement uncertainty is of profound significance in promoting effective trajectory analysis and mining. However, classic uncertainty models are limited by rigid assumptions on moving speed and distance, which ignores the stochastic nature of individual’s travel behaviour. This study introduces a novel method using adaptive ellipses to represent the movement uncertainty in a planar

ABSTRACT Increasing intensity and frequency of hurricane events underscores the need for efficient and inclusive evacuation plans, particularly for carless and disabled populations. Hurricane evacuation intrinsically involves both social and spatial processes. People’s decision to evacuate spreads over social networks; once their decisions are made, they flee through spatial transportation networks

ABSTRACT We collected 92,832 user-contributed and publicly available family trees from rootsweb.com, including 250 million individuals who were born in North America and Europe between 1630 and 1930. We cleaned and connected the family trees to create a population-scale and longitudinal family tree dataset using a workflow of data collection and cleaning, geocoding, fuzzy record linkage and a relation-based

Digital billboards, as a new form of outdoor advertising, has gained popularity in recent years per its revolutionized way to control when and where the specific ads appear. However, this development also demands more complicated optimization for strategic deployments: the advertisers have to not only decide on a set of locations to display their ads, but also when to display them. The existing static

Online navigation systems assume a person can follow a given route from origin to destination. Nonetheless, spatial cognition studies show that wayfinding is a complex, highly adaptive process and that route planning is incremental rather than prescriptive. Indeed, people may deviate from their originally chosen route for a number of reasons including navigation errors, especially when the environment

ABSTRACT Legacy ecoregion maps contain knowledge on relationships between eco-region units and their environmental factors. This study proposes a method to extract knowledge from legacy area-class maps to formulate a set of fuzzy membership functions useful for regionalization. We develop a buffer zone approach to reduce the uncertainty of boundaries between eco-region units on area-class maps. We

ABSTRACT This study introduces four heterogeneous ensemble-learning techniques, that is, stacking, blending, simple averaging, and weighted averaging, to predict landslide susceptibility in Yanshan County, China. These techniques combine several state-of-the-art classifiers of convolutional neural network, recurrent neural network, support vector machine, and logistic regression in specific ways to

Several works in GIScience propose approaches to identify general motion patterns through the analysis of objects’ trajectories. However, they are not suitable to identify functional relationships in scenarios where domain-dependent motion behaviors exist. In this work, we explore the identification of a particular pattern found in team-based invasion sports. We propose a method to identify defensive

ABSTRACT The spatial pattern of urban growth determines how the physical, socio-economic and environmental characteristics of urban areas change over time. Monitoring urban areas for early identification of spatial patterns facilitates assuring their sustainable growth. In this paper, we assess the use of spatio-temporal metrics from land-use/land-cover (LULC) maps to identify growth patterns. We applied

Locating populations in rural areas of developing countries has attracted the attention of humanitarian mapping projects since it is important to plan actions that affect vulnerable areas. Recent efforts have tackled this problem as the detection of buildings in aerial images. However, the quality and the amount of rural building annotated data in open mapping services like OpenStreetMap (OSM) is not

Uneven distributions of population and service providers lead to geographic disparity in access for residents and varying workload for staff in facilities. The former can be captured by spatial accessibility in the traditional two-step floating catchment area (2SFCA) method; and the latter can be measured by potential crowdedness in the newly developed inverted 2SFCA (or i2SFCA) method. Residents-based

Location prediction based on spatio-temporal footprints in social media is instrumental to various applications, such as travel behavior studies, crowd detection, traffic control, and location-based service recommendation. In this study, we propose a model that uses geotags of social media to predict the potential area containing users’ next locations. In the model, we utilize HiSpatialCluster algorithm

ABSTRACT Fuzzy geographically weighted clustering has been proposed as an approach for improving fuzzy c-means algorithm when applied to geodemographic analysis. This clustering method allows a spatial entity to belong to more than one cluster with varying degrees, namely, membership values. Although fuzzy geographically weighted clustering attempts to create geographically aware clusters, it partially

The focus of this work is general methods for prioritization or screening of project sites based on the favorability of multiple spatial criteria. We present a threshold-based transformation of each underlying spatial favorability factor into a continuous scale with a common favorability interpretation across all criteria. We compare several methods of computing site favorability and propagating uncertainty

Big geo-data are often aggregated according to spatio-temporal units for analyzing human activities and urban environments. Many applications categorize such data into groups and compare the characteristics across groups. The intergroup differences vary with spatio-temporal units, and the essential is to identify the spatio-temporal units with apparently different data characteristics. However, spatio-temporal

ABSTRACT Big geo-data are often aggregated according to spatio-temporal units for analyzing human activities and urban environments. Many applications categorize such data into groups and compare the characteristics across groups. The intergroup differences vary with spatio-temporal units, and the essential is to identify the spatio-temporal units with apparently different data characteristics. However

Polygon similarity can play an important role in geographic information retrieval, map matching and updating, and spatial data mining applications. Geographic information science (GIS) represents various spatial objects as polygons, including simple polygons and polygons with holes, as well as multipolygons. Spatial objects of multipolygons possess complex structure which makes it difficult to assess

A cornerstone of the scientific method, the ability to reproduce and replicate the results of research has gained widespread attention across the sciences in recent years. A corresponding burst of energy into how to make research more reproducible and replicable has led to numerous innovations. This article outlines some of the opportunities for geospatial researchers to contribute to and learn from

ABSTRACT Trajectory segmentation is a fundamental issue in GPS trajectory analytics. The task of dividing a raw trajectory into reasonable sub-trajectories and annotating them based on moving subject’s intentions and application domains remains a challenge. This is due to the highly dynamic nature of individuals’ patterns of movement and the complex relationships between such patterns and surrounding

In geographic information science and technology, various methods and studies exist to characterize the linearity, rectangularity, convexity, circularity or compactness, sinuosity or tortuosity of a given spatial shape. Although there is much work on ellipticity in image processing, we do not address, in geomatics, the issue of matching to a reference elliptical shape. Regarding this issue, this article

ABSTRACT Understanding population distribution has excellent applications for planning and provision of municipal services. This study aims to explore the space-time structure of population distribution with area-level mobile phone data. We discuss a kind of Bayesian hierarchical models, fitted by Markov chain Monte Carlo simulation, that combines the overall spatial pattern and temporal trends as

ABSTRACT Ecological niche models (ENMs) are widely used statistical methods to estimate various types of species niches. After lecturing several editions of introductory courses on ENMs and reviewing numerous manuscripts on this subject, we frequently faced some recurrent mistakes: 1) presence-background modelling methods, such as Maxent or ENFA, are used as if they were pseudo-absence methods; 2)

ABSTRACT Large-area land cover maps are produced to satisfy different information needs. Land cover maps having partial or complete spatial and/or temporal overlap, different legends, and varying accuracies for similar classes, are increasingly common. To address these concerns and combine two 30-m resolution land cover products, we implemented a harmonization procedure using a Latent Dirichlet Allocation

In this work, a synthesis of the Bayesian maximum entropy (BME) and the Kalman filter (KF) methods, which enhances their individual strengths and overcomes certain of their weaknesses for spatiotemporal mapping purposes, is proposed in a spatiotemporal disease mapping context. The proposed BME-Kalman synthesis allows BME to use information from both parametric regression modeling and KF estimation