Transit-oriented development (TOD) is among the most feasible strategies for relieving urban issues caused by the unbalanced development of transportation and land use. This study proposes a multiobjective TOD land use design framework for the optimi...
This research reports the ongoing design of the HISMACITY (Historical Small Smart City) Protocol, a planning tool with a certification system. The tool is designed for small municipalities in Europe. Through the award-winning certification system, th...
As a result of Earth observation (EO) entering the era of big data, a significant challenge relating to by the storage, analysis, and visualization of a massive amount of remote sensing (RS) data must be addressed. In this paper, we proposed a novel...
Wetlands are one of the most important ecosystems that provide a desirable habitat for a great variety of flora and fauna. Wetland mapping and modeling using Earth Observation (EO) data are essential for natural resource management at both regional a...
This study addressed a critical resource—soil—through the prism of processing big data at the continental scale. Rapid progress in technology and remote sensing has majorly improved data processing on extensive spatial and temporal scales...
The image of a city represents the sum of beliefs, ideas, and impressions that people have of that city. Mostly, city images are assessed through direct or indirect interviews and cognitive mapping exercises. Such methods consume more time and effort...
Without geospatial data management, today’s challenges in big data applications such as earth observation, geographic information system/building information modeling (GIS/BIM) integration, and 3D/4D city planning cannot be solved. Furthermore,...
Privacy Preserving and Anonymity have gained significant concern from the big data perspective. We have the view that the forthcoming frameworks and theories will establish several solutions for privacy protection. The k-anonymity is considered a key...
In the context of rural revitalization strategies and humans’ increasing leisure pursuit, leisure agriculture starts to act as a new engine of rural economic growth and industrial upgradation. Unraveling the agri-leisure developmental regularity from...
This study introduces a new automated system that blends multi-satellite information and citizen science data for reliable and timely observations of lake and river ice in under-observed northern regions. The system leverages the Google Earth Engine...
Google Earth Engine (GEE) has become one of the most widely used platforms for Land Use and Land Cover (LULC) research, offering cloud-based access to petabyte-scale datasets and scalable analytical tools. While earlier reviews provided valuable over...
Interventions implemented in geographic space (geo-interventions) have had success in reducing preventable deaths across the world. However, many studies supporting geo-interventions have focused on where to implement them rather than what they are....
In the era of big data, Internet-based geospatial information services such as various LBS apps are deployed everywhere, followed by an increasing number of queries against the massive spatial data. As a result, the traditional relational spatial dat...
Numerous studies have been devoted to uncovering the characteristics of resident density and urban mobility with multisource geospatial big data. However, little attention has been paid to the internal diversity of residents such as their occupations...
Seismic site effects are influenced mainly by geospatial uncertainties corresponding to geological or geotechnical spatial variance. Therefore, the development of a geospatial database is essential to characterize site-specific geotechnical informati...
With the recent increase in urban drift, which has led to an unprecedented surge in urban population, the smart city (SC) transportation industry faces a myriad of challenges, including the development of efficient strategies to utilize available inf...
An information content approach is taken to producing a ‘digital description’ of a landscape utilising georeferencing within Digital Earth. A general view of the geomorphology of ‘northern England’ is used as a discussion area...
In the past twenty years, we have witnessed an unprecedented production of data worldwide that has generated a growing demand for computing resources and has stimulated the design of computing paradigms and software tools to efficiently and quickly o...
Gossans are surficial deposits that form in host bedrock by the alteration of sulphides by acidic and oxidizing fluids. These deposits are typically a few meters to kilometers in size and they constitute important vectors to buried ore deposits. Hund...
Google Earth Engine (GEE) has become a central platform for planetary-scale geospatial analysis, but its rapid evolution in the last few years is not yet reflected in the existing review literature. Earlier reviews mainly describe the platform’...
Timely, region-based geo-maps like choropleths are essential for smart city applications like traffic monitoring and urban planning because they can reveal statistical patterns in geotagged data. However, because data overloading is brought on by the...
With the rapid development of big data, numerous industries have turned their focus from information research and construction to big data technologies. Earth science and geographic information systems industries are highly information-intensive, and...
In the big data era, the social media data that contain users’ geographical locations are growing explosively. These kinds of spatiotemporal data provide a new perspective for us to observe the human movement behavior. By mining such spatiotemporal d...
This narrative review examines how big data analytics supports geospatial decision-making in smart cities through the combined roles of spatial data foundations, GeoAI methods, and urban digital twins. Methodologically, the article follows a structur...
An area of interest (AOI) refers to an urban area that attracts people’s attention within different urban functions through cities. The wide availability of big geo-data that are able to capture human activities and environmental socioeconomics...
This study aimed to evaluate the relationships between different groups of explanatory variables (i.e., dynamic human activity variables, static variables of social disorganisation and crime generators, and combinations of both sets of variables) and...
Computational science simulations produce huge volumes of data for scientific research organizations. Often, this data is shared by data centers distributed geographically for storage and analysis. Data corruption in the end-to-end route of data tran...
Technological advances have led to numerous developments in data sources. Geo-tagged photo metadata has provided a new source of mass research data for tourism studies. A series of data processing methods centering on the various types of information...
Many cities face health issues that result from ineffective urban planning strategies. The chances of doing exercises in sportive venues implicate public health and citizen quality of life. With the advent of the geo-big data era, it is crucial to ex...
The integration of heterogeneous spatio-temporal datasets presents a critical challenge in geospatial data science, particularly when combining large-scale, passively collected “big” data with precise but sparse “small” data....
As the amount of collected spatial information (2D/3D) increases, the real-time processing of these massive data is among the urgent issues that need to be dealt with. Discretizing the physical earth into a digital gridded earth and assigning an inte...
Density-based clustering algorithms have been the most commonly used algorithms for discovering regions and points of interest in cities using global positioning system (GPS) information in geo-tagged photos. However, users sometimes find more specif...
Urban parks play an essential role in mitigating the effects of air pollution on human health in a healthy city construction process. However, due to the data limitations, little is known about the spatial distribution of real-time expressed air poll...
The convergence of big data and geospatial computing has brought challenges and opportunities to GIScience with regards to geospatial data management, processing, analysis, modeling, and visualization. This special issue highlights recent advancement...
Groundwater resources, unlike surface water, are more vulnerable to disturbances and contaminations, as they take a very long time and significant cost to recover. So, predictive modeling and prevention strategies can empower policymakers for efficie...
Tweet My Street is a cross-disciplinary project exploring the extent to which data derived from Twitter can reveal more about spatial and temporal behaviours and the meanings attached to these locally. This is done with a longer-term view to supporti...
One longstanding complication with Earth data discovery involves understanding a user’s search intent from the input query. Most of the geospatial data portals use keyword-based match to search data. Little attention has focused on the spatial and te...
In grapevine research the acquisition of phenotypic data is largely restricted to the field due to its perennial nature and size. The methodologies used to assess morphological traits and phenology are mainly limited to visual scoring. Some measureme...
The Space-time prism (STP) is a key concept in time geography for analyzing human activity-travel behavior under various Space-time constraints. Most existing time-geographic studies use a straightforward algorithm to construct STPs in road networks...
All over the world, the rapid urbanization process is challenging the sustainable development of our cities. In 2015, the United Nation highlighted in Goal 11 of the SDGs (Sustainable Development Goals) the importance to “Make cities inclusive,...
This paper presents BSTwin, a computational workflow and application for the automatic generation of multi-level-of-detail building models and semantically enriched building stock records in urban areas of Slovakia. Its outputs are positioned as the...
As a distinct species in the Tianshan Mountains (TS) of Central Asia (CA), Picea schrenkiana plays a significant role in water purification, soil and water conservation, and climate regulation. In the context of climate change, rapidly and accurately...
Mass remote sensing data management and processing is currently one of the most important topics. In this study, we introduce ScienceEarth, a cluster-based data processing framework. The aim of ScienceEarth is to store, manage, and process large-scal...
With the advance of the World-Wide Web (WWW) technology, people can easily share content on the Web, including geospatial data and web services. Thus, the “big geospatial data management” issues start attracting attention. Among the big geospatial da...
Source–sink zones refer to aggregated adjacent origins/destinations with homogeneous trip flow characteristics. Current relevant studies mostly detect source–sink zones based on outflow/inflow volumes without considering trip routes. Neve...
The integrity of point cloud is the basis for smoothly ensuring subsequent data processing and application. For “Smart City” and “Scan to Building Information Modeling (BIM)”, complete point cloud data is essential. At present...
This paper investigates recent research on active learning for (geo) text and image classification, with an emphasis on methods that combine visual analytics and/or deep learning. Deep learning has attracted substantial attention across many domains...
The borehole log image contains valuable text information, encompassing key geological data such as structural composition, orebody distribution, and lithological characteristics. These data are important for mineral prediction, GeoBigData, and GeoMo...
Numerous real-life smart city application scenarios require joint analytics on unified views of georeferenced mobility data with environment contextual data including pollution and meteorological data. particularly, future urban planning requires res...
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