18 papers · ranked by Valyu relevance
Md Mahbub Alam, Luı́s Torgo, Albert Bifet
Due to the surge of spatio-temporal data volume, the popularity of location-based services and applications, and the importance of extracted knowledge from spatio-temporal data to solve a wide range of real-world problems, a plethora of research and development work has been done in the area of spatial and…
Jiayang Wu, Wensheng Gan, Han‐Chieh Chao, Philip S. Yu
—In recent years, geospatial big data (GBD) has obtained attention across various disciplines, categorized into big earth observation data and big human behavior data. Identifying geospatial patterns from GBD has been a vital research focus in the fields of urban management and environmental sustainability. This paper…
Mohammed Eunus Ali, Muhammad Aamir Cheema, Tanzima Hashem, Anwaar Ulhaq + 1 more
'Anwaar Ulhaq' 'Muhammad Ali Babar'] A Digital Twin (DT) is a virtual replica of a physical object or system, created to monitor, analyze, and optimize its behavior and characteristics. A Spatial Digital Twin (SDT) is a specific type of digital twin that emphasizes the geospatial aspects of the physical entity…
Zhipeng Liu, Weihua Hua, Xiuguo Liu, Dong Liang + 3 more
'Manxing Shi' 'Thomas Udelhoven'] Geospatial three-dimensional (3D) raster data have been widely used for simple representations and analysis, such as geological models, spatio-temporal satellite data, hyperspectral images, and climate data. With the increasing requirements of resolution and accuracy, the amount of…
Luca Marconato, Giovanni Palla, Kevin A. Yamauchi, Isaac Virshup + 10 more
Spatially resolved omics technologies are transforming our understanding of biological tissues. However, handling uni- and multi-modal spatial omics datasets remains a challenge owing to large volumes of data, heterogeneous data types and the lack of unified spatially-aware data structures. Here, we introduce…
Zhongpu Chen, Wanjun Hao, Ziang Zeng, Long Shi + 3 more
'Zhi-Jie Wang' 'Yu Zhao'] Abstract—The efficient management of big spatial data is crucial for location-based services, particularly in smart cities. However, existing systems such as Simba and Sedona, which incorporate distributed spatial indexing, still incur substantial index construction overheads, rendering them…
Michael Dumelle, Matt Higham, Jay M. Ver Hoef, A. K. M. Anisur Rahman
'A. K. M. Anisur Rahman'] spmodel is an R package used to fit, summarize, and predict for a variety spatial statistical models applied to point-referenced or areal (lattice) data. Parameters are estimated using various methods, including likelihood-based optimization and weighted least squares based on variograms.…
Baiyou Qiao, Ling Ma, Linlin Chen, Bing Hu + 1 more
As a popular spatial operation, the k-Nearest Neighbors (kNN) query is widely used in various spatial application systems. How to efficiently process a kNN query on spatial big data has always been an important research topic in the field of spatial data management. The centralized solutions are not suitable for…
Isam Mashhour Al Jawarneh, Luca Foschini, Paolo Bellavista, Jose Manuel Molina López
'Jose Manuel Molina López'] The unprecedented availability of sensor networks and GPS-enabled devices has caused the accumulation of voluminous georeferenced data streams. These data streams offer an opportunity to derive valuable insights and facilitate decision making for urban planning. However, processing and…
Ralf Bill, Jörg Blankenbach, Martin Breunig, Jan-Henrik Haunert + 10 more
'Christian Heipke' 'Stefan Herle' 'Hans-Gerd Maas' 'Helmut Mayer' 'Liqui Meng' 'Franz Rottensteiner' 'Jochen Schiewe' 'Monika Sester' 'Uwe Sörgel' 'Martin Werner'] Geospatial information science (GI science) is concerned with the development and application of geodetic and information science methods for modeling…
Jocelyne Shimin Sze, Laura Aileen Sauls
Conservation has embraced advances in big data and related digital technologies as key to preventing biodiversity loss, especially in the identification of areas of conservation priority based on spatial data, which we call the big geospatial data turn. This turn has led to the proliferation of useful methods and…
Christoffer M. Langseth, Bastien Hervé, Hanna P. Piechaczyk, Yuk Kit Lor + 2 more
Spatial omics technologies enable high-resolution mapping of molecular and cellular organization within tissues, yet interactive exploration of these data remains challenging due to computational bottlenecks, and reliance on proprietary software infrastructures. We present KaroSpace, a framework for cell-centric…
Lambda Moses, Alik Huseynov, Joseph M Rich, Lior Pachter
SpatialFeatureExperiment is a Bioconductor package that leverages the versatility of Simple Features for spatial data analysis and SpatialExperiment for single-cell -omics to provide an expansive and convenient S4 class for working with spatial -omics data. SpatialFeatureExperiment can be used to store and analyze a…
Jinpu Li, Mauminah Raina, Yiqing Wang, Chunhui Xu + 7 more
Emerging spatial omics technologies empower comprehensive exploration of biological systems from multi-omics perspectives in their native tissue location in two and three- dimensional space. However, sparse sequencing capacity and growing spatial resolution in spatial omics present significant computational challenges…
Juexin Wang, Jinpu Li, Skyler T Kramer, Li Su + 4 more
Identifying spatially variable genes (SVGs) is critical in linking molecular cell functions with tissue phenotypes. Spatially resolved transcriptomics captures cellular-level gene expression with corresponding spatial coordinates in two or three dimensions and can be used to infer SVGs effectively. However, current…
Wei Wang
In order to improve the geometric form space composition and color planning analysis ability of smart city public buildings, a big data based smart city public building space design method is proposed. The method of combining computer vision detection and remote sensing detection is adopted to realize the detection of…
Ling Huang, Shannon Stokes, Qining Chen, Felipe Cardoso-Saldaña + 1 more
Total column loadings of methane measured by satellites are increasingly used to estimate methane emission rates, using inversion calculations. Forward calculations of methane column loadings, based on detailed emission inventories at fine spatial resolution, coupled with fine spatial scale gridded chemical transport…
Daniel Goldberg, Benjamin de Foy, M. Omar Nawaz, Jeremiah Johnson + 2 more
Air quality managers in areas exceeding air pollution standards are motivated to understand where there are further opportunities to reduce NOx emissions to improve ozone and PM2.5 air quality. In this project, we use a combination of aircraft remote sensing (i.e., GCAS), source apportionment models (i.e., CAMx), and…