Although spatial prediction is a versatile tool for urban and environmental monitoring, the predictive accuracy is often unsatisfactory when limited samples are available from the study area. The present study was conducted to improve the accuracy in such cases through transfer learning, which uses larger datasets from external areas. Specifically, we proposed the SpTrans method...
While, many of the machine learning (ML) and artificial intelligence (AI) methods that are now commonly being used to answer questions across scientific disciplines have been around for some time, their widespread application to spatial data and spatially-explicit research questions is much more recent. The large number of excellent review papers and special issues in leading...
This paper proposes a new method of point cluster analysis. There are at least three important points that we need to consider in the evaluation of point clusters. The first is spatial inhomogeneity, i.e., the inhomogeneity of locations where points can be located. The second is aspatial inhomogeneity, which indicates the inhomogeneity of point characteristics. The third is an...
Recent studies on green space exposure have argued that overlooking human mobility could lead to erroneous exposure estimates and their associated inequality. However, these studies are limited as they focused on single cities and did not investigate multiple cities, which could exhibit variations in people’s mobility patterns and the spatial distribution of green spaces...
Accessing massive datasets can be challenging for users unfamiliar with programming codes. Combining Konstanz Information Miner (KNIME) and MySQL tools on standard configuration equipment allows for addressing this issue. This research proposal aims to present a methodology that describes the necessary configuration steps in both tools and the required manipulation in KNIME to...
The passing of Professor Arthur Getis in May of 2022 initiated a number of events to both reflect on and remember the tremendous contributions he has made over his career to geographical systems more broadly, but also spatial analysis, spatial statistics, regional science, geography and GIScience, among others. This began with a series of sessions at the North American Regional...
This paper quantifies and graphically illustrates the distance decay effect and spatial reach of spillover effects derived from a spatial Durbin (SD) model with parameterized spatial weight matrices. Building on attributes of the concept of spatial autocorrelation developed by Arthur Getis, we adopt a distance-based negative exponential spatial weight matrix and parameterize it...
In today's era, the address plays a crucial role as one of the key components that enable mobility in daily life. Address data are used by global map platforms and location-based services to pinpoint a geographically referenced location. Geocoding provided by online platforms is useful in the spatial tracking of reported cases and controls in the spatial analysis of infectious...
This paper develops a new method for analyzing the relationship between a set of points and another single point, the latter of which we call a reference point. This relationship has been discussed in various academic fields, such as geography, criminology, and epidemiology. Analytical methods, however, have not yet been fully developed, which has motivated this paper. Our method...
This study proposes a sequence of methods to obtain geolocated estimates of primary school provision, costs, and access. This sequence entails: (1) location-allocation, an approach that mimics school location patterns in case of decentralised governance, such as exists in the EU and UK; (2) balanced floating catchment areas, an approach to assign pupils to schools assuming free...
The lineaments are linear features reflecting mountain ridges or discontinuities in the geological structure. Lineament extraction is not an easy problem. Recently, an automatic approach based on multi-hillshade hierarchic clustering (MHHC) has been developed; the approach is based on line extraction from a raster image. An essential part of this approach is spatial line segment...
There is an on-going challenge to describe, analyse and visualise the actual and potential extent of human spatial behaviour. The concept of an activity space has been used to examine how people interact with their environment and how the actual or potential spatial extent of individual spatial behaviour can be defined. In this paper, we introduce a new method for measuring...
In the past ten years, cities have experienced a burst of micromobility services as they offer a flexible transport option that allows users to cover short trips or the first/last mile of longer trips. Despite their potential impacts on mobility and the fact that they offer a cleaner, more environmentally friendly alternative to private cars, few efforts have been devoted to...
The development of the “causal” forest by Wager and Athey (J Am Stat Assoc 113(523): 1228–1242, 2018) represents a significant advance in the area of explanatory/causal machine learning. However, this approach has not yet been widely applied to geographically referenced data, which present some unique issues: the random split of the test and training sets in the typical causal...
The increase in physical inactivity prevalence in the USA has been associated with neighborhood characteristics. While several studies have found an association between neighborhood and health, the relative importance of each component related to physical inactivity or how this value varies geographically (i.e., across different neighborhoods) remains unexplored. This study ranks...
Time geography was conceptualized in the 1960s when the technology was very different from what we have today. Conventional time-geographic concepts therefore were developed with a focus on human activities and interactions in physical space. We now live in a smart, connected, and dynamic world with human activities and interactions increasingly taking place in virtual space...
Object matching is a key technology for map conflation, data updating, and data quality assessment. This article proposed a new Voronoi diagram-based approach for matching multi-scale road networks (VAMRN). Using this method, we first created Voronoi diagrams of the road network using the strategy of discretizing road lines into points and adding dense points to special road...
During the COVID-19 pandemic, e-commerce’s market share has increased dramatically, a phenomenon attributable to not only lockdowns but to voluntary changes in shopping behavior as well. The current study examines the main determinants driving shopping behavior in the context of both physical and online store availability, and investigates whether specific drivers have changed...
Time geography is widely used by geographers as a model for understanding accessibility. Recent changes in how access is created, an increasing awareness of the need to better understand individual variability in access, and growing availability of detailed spatial and mobility data have created an opportunity to build more flexible time geography models. Our goal is to outline a...
This paper contributes to the existing literature on the explanation of housing prices. First, our proposed methodology accounts for cross-sectional dependence, both locally and globally, using individual data of more than 200,000 transactions in the three most northern provinces of the Netherlands over the period 1993–2014. Second, the selection of houses within each focal house...
The visible landscape represents an important consideration within landscape management activities, forming an inhabitants’ perception of their overall surroundings and providing them with a sense of landscape connection, sustainability and identity. The historical satellite imagery archive can provide key knowledge of the overall change in land use and land cover (LULC), which...