Spatial knowledge, i.e., knowledge about space and place, is commonly used by stakeholders during the deliberative process of public participation practice. The goal of this article is to examine to what extent spatial knowledge exists and is used in...
The size, volume, variety, and velocity of geospatial data collected by geo-sensors, people, and organizations are increasing rapidly. Spatial Data Infrastructures (SDIs) are ongoing to facilitate the sharing of stored data in a distributed and homog...
The prevalent use of GPS-based navigation systems impairs peoples’ ability to orient themselves. This paper investigates whether wayfinding maps that accentuate different types of environmental features support peoples’ spatial learning....
The knowledge economy plays a leading role in current socioeconomic development and has changed industrial development. This study addresses whether changes in industrial development have improved the knowledge innovation, technical level, and produc...
Geospatial data is urgently needed in decision-making processes to achieve Sustainable Development Goals (SDGs) at global, national, regional and local scales. While the advancement of geo-technologies to obtain or produce geospatial data has become...
Lane boundary detection technology has progressed rapidly over the past few decades. However, many challenges that often lead to lane detection unavailability remain to be solved. In this paper, we propose a spatial-temporal knowledge filtering model...
Smartphone map-based pedestrian navigation is known to have a negative effect on the long-term acquisition of spatial knowledge and memorisation of landmarks. Landmark-based navigation has been proposed as an approach that can overcome such limitatio...
The reasonable spatial planning of primary and secondary schools is an important factor in education development. In spatial planning, there are many models for the locations of primary and secondary schools; however, few quantitative evaluation mode...
This paper proposes a two-step pseudo-maximum likelihood estimator of a spatial autoregressive exponential model for counts and other nonnegative variables; it is particularly useful for dealing with zeros. It considers a model specification allowing...
Knowledge tracing (KT) serves as a primary part of intelligent education systems. Most current KTs either rely on expert judgments or only exploit a single network structure, which affects the full expression of learning features. To adequately mine...
Under emergencies such as floods and fires or during indoor navigation where cues from local landmarks and a Global Positioning System (GPS) are no longer available, the acquisition of comprehensive environmental representation becomes particularly i...
With the growth of the internet and popularity of mobile devices, propagating rumors on social media has become increasingly easy. Widespread rumors may cause public panic and have adverse effects on individuals. Recently, researchers have found that...
Spatial management consists of land property and land use management, both on land and in the ocean. From the perspective of ‘social-ecological systems’, local spatial management represented the resilience of adaptation that indigenous knowledge and...
In this paper, we propose an efficient knowledge distillation method to train light networks using heavy networks for semantic segmentation. Most semantic segmentation networks that exhibit good accuracy are based on computationally expensive network...
The pixel-based semantic segmentation methods take pixels as recognitions units, and are restricted by the limited range of receptive fields, so they cannot carry richer and higher-level semantics. These reduce the accuracy of remote sensing (RS) sem...
Decisions are a key element of spatial planning processes and in the face of increasing public participation in local governance, they become even more complex. The diversity of stakeholders in planning processes causes a significant increase in the...
To accurately assess students’ cognitive state of knowledge points in the learning process within the smart classroom, a knowledge tracing (KT) model based on classroom network characteristic learning engagement and temporal-spatial feature fus...
Many documents contain vague location descriptions of observed objects. To represent location information in geographic information systems (GISs), these vague location descriptions need to be transformed into representable fuzzy spatial regions, and...
The outbreak of COVID-19 (coronavirus disease 2019) has generated a large amount of spatiotemporal data. Using a knowledge graph can help to analyze the transmission relationship between cases and locate the transmission path of the pandemic, but res...
The technical advances in navigation systems should enhance the driving experience, supporting drivers’ spatial decision making and learning in less familiar or unfamiliar environments. Furthermore, autonomous driving systems are expected to take ove...
Spatial planning has become an important measure for countries and regions to promote sustainable development. However, there remains a lack of systematic and quantitative research on spatial planning worldwide. In this study, CiteSpace was used to p...
The aim of personalized maps is to help individual users to read maps and focus on the most task-relevant information. Several approaches have been suggested to develop personalized maps for cities, but few consider the spatial knowledge of its users...
A seemingly unresolved debate in urban planning is the call for compactness and the provision of intra-urban green spaces. This article defines a multi-scalar spatial planning model for peri-urban areas and urban voids able to reconcile medium to hig...
Considering the evolution of the spatial pattern of regional economic growth in China, this paper analyzes whether environmental regulation (ER) and environmental knowledge spillover (EKS) contribute to regional economic growth using panel data and t...
Accurately forecasting demand for intermittent items is essential for effective inventory control, improved service levels, and cost reduction. This study focuses on highly sparse, irregular, and volatile demand patterns and proposes a generalizable...
The use of advanced adaptive algorithms in Augmented Reality (AR) systems works to advance spatial skills with valuable relevance in many professional spheres by providing personalized feedback in an immersive environment. This study combines Bayesia...
Knowledge-intensive business services (KIBSs) are key links in leading the sustainable development of cities. Studying the spatial pattern and influencing factors of urban KIBSs can help improve the utilization of KIBS resources. Taking the Wuhan met...
Accurate and efficient sorting of diverse magnetic tiles during manufacturing is vital. However, challenges arise due to visual similarities among types, necessitating complex computer vision algorithms with large sizes and high computational needs....
This paper uses the technology acceptance model (TAM) framework for the research of economic and geography students’ attitudes towards interdisciplinary knowledge. Based on the SmartPLS Structural equation modelling SEM variance-based method, r...
The concept of ecosystem services (ES) arises as a formal outcome of historical processes of understanding and interpreting settlements as complex ecological systems. Because of a straightforward, bottom-up demand for environment enhancement, this co...
Sensory augmentation provides novel opportunities to broaden our knowledge of human perception through external sensors that record and transmit information beyond natural perception. To assess whether such augmented senses affect the acquisition of...
Restricted by the small screen size, it is challenging for users to obtain all the wayfinding content they need when utilizing mobile devices. This study investigated the effects of map size and interactive interface on users’ wayfinding performance...
This article discusses the convenience of adopting an approach of Collective Spatial Analysis in the P/PGIS processes, with the aim of improving the collection and integration of knowledge and local expertise in decision-making, mainly in the fields...
The term “crowdsourcing” was initially introduced by Howe in his article “The Rise of Crowdsourcing” [1]. During the last few years, crowdsourcing has become popular among companies, institutions and universities, as a crowd-centered modern “tool” fo...
Sustainable development has to be based on scientific knowledge, social agreements, and political decisions. This study aimed to analyse the implementation of the ecosystem services approach (ESA) in the spatial planning of the Basque Country, via th...
Amid climate change, biodiversity loss and food insecurity, there is the growing need to draw synergies between micro-scale environmental processes and practices, and macro-level ecosystem dynamics to facilitate conservation decision-making. Adopting...
Recent advances in knowledge graphs show great promise to link various data together to provide a semantic network. Place is an important part in the big picture of the knowledge graph since it serves as a powerful glue to link any data to its georef...
This article explores the relationship between knowledge sources at different levels and corporate innovation from the perspective of urban cluster, with a focus on enterprises. This paper conducted an empirical analysis of 375 listed companies in 27...
Knowledge representation learning is representing entities and relations in a knowledge graph as dense low-dimensional vectors in the continuous space, which explores the features and properties of the graph. Such a technique can facilitate the compu...
We compare intra-urban localization patterns of advertising and IT companies in three large Czech cities. The main aim of our analysis is an empirically-based contribution to the question to what extent do knowledge bases affect the spatial distribut...
Natural ventilation is a critical method for reducing energy consumption for heating, cooling, and ventilating buildings. Recent research has focused on utilizing environmental IoT data from both inside and outside buildings for NVR prediction based...
Knowledge graph embedding has been identified as an effective method for node-level classification tasks in directed graphs, the objective of which is to ensure that nodes of different categories are embedded as far apart as possible in the feature s...
Descriptions of the spatial locations of disappeared objects are often recorded in eyewitness records, travel notes, and historical documents. However, in geographic information system (GIS), the observer-centered and vague nature of the descriptions...
Geospatial knowledge graphs provide critical technology for integrating geographic information and semantic knowledge, which are very useful for geographic data analysis. As the scale of geospatial knowledge graphs continues to grow, the distributed...
With the boom in online information, knowledge graphs like Freebase, Wikidata, and YAGO have emerged, thanks to the introduction of the RDF (Resource Description Framework). As RDF data grew, more and more spatial data was incorporated into it. While...
The increasing availability of satellite data at different spatial resolutions offers new opportunities for environmental monitoring, highlighting the limitations of medium-resolution products for fine-scale territorial analysis. However, it also rai...
Buildings with spatially complex interiors poise unique challenges during operations and maintenance. A complex interior makes wayfinding difficult, which can inhibit daily occupants from finding their desired location. Additionally, it can hamper em...
The Geographic Knowledge Graph (GeoKG) serves as an effective method for organizing geographic knowledge, playing a crucial role in facilitating semantic interoperability across heterogeneous data sources. However, existing GeoKGs are limited by a la...
Resource conflicts constitute a major global issue in areas rich in natural resources. The modeling of factors influencing natural resource conflicts (NRCs), including environmental, health, socio-economic, political, and legal aspects, presents a si...
Personalized urban services are becoming increasingly significant in smart city systems. This shift from intelligent transportation to smart cities broadens the scope of personalized services, encompassing not just travel but a wide range of urban ac...
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