26 papers · ranked by Valyu relevance
Maria Goreti Rosa-Freitas, Nildimar Alves Honório, Cláudia Torres Codeço, Guilherme Loureiro Werneck + 1 more
Visual inspection of spatial distribution of data allows apprehending existing patterns. The translation of these patterns into a system of theoretical significance is an important tool in the investigation of the disease process. Currently, spatial studies of disease and vectors involve the use of computational…
Joshua A. Bull, Joshua W. Moore, Eoghan J. Mulholland, Simon J. Leedham + 1 more
The generation of spatial data in biology has been transformed by multiplex imaging and spatial-omics technologies, such as single cell spatial transcriptomics. These approaches permit a detailed mapping of cell populations and phenotypes within the tissue context, which reveals that tissues are complex ecosystems that…
Samuel Manda, Ndamonaonghenda Haushona, Robert Bergquist
Spatial analysis has become an increasingly used analytic approach to describe and analyze spatial characteristics of disease burden, but the depth and coverage of its usage for health surveys data in Sub-Saharan Africa are not well known. The objective of this scoping review was to conduct an evaluation of studies…
Munazza Fatima, Kara J. O’Keefe, Wenjia Wei, Sana Arshad + 4 more
'Oliver Gruebner' 'Thomas Krafft' 'Mark Rosenberg' 'Paula Santana'] The outbreak of SARS-CoV-2 in Wuhan, China in late December 2019 became the harbinger of the COVID-19 pandemic. During the pandemic, geospatial techniques, such as modeling and mapping, have helped in disease pattern detection. Here we provide a…
Amaryllis Mavragani, Au Vo, Maryam Nasiri, Janmilli da Costa Dantas + 4 more
Background Latin America, Africa, and Asia have high incidences of syphilis. New approaches are needed to understand and reduce disease transmissibility. In health care, spatial analysis is important to map diseases and understand their epidemiologic aspects. Objective The proposed scoping review will identify and map…
Tobias Rüttenauer
This handbook chapter provides an essential introduction to the field of spatial econometrics, offering a comprehensive overview of techniques and methodologies for analysing spatial data in the social sciences. Spatial econometrics addresses the unique challenges posed by spatially dependent observations, where…
Yanguang Chen
Geographical phenomena fall into two categories: scaleful phenomena and scale-free phenomena. The former bears characteristic scales, and the latter has no characteristic scale. The conventional quantitative and mathematical methods can only be effectively applied to scaleful geographical phenomena rather than the…
Xiao Li
Understanding the spatial dynamics within tissue microenvironments is crucial for deciphering cellular interactions and molecular signaling in living systems. These spatial characteristics govern cell distribution, extracellular matrix components, and signaling molecules, influencing local biochemical and biophysical…
Ke Hu, Chaojie Li, Xingjin Yang, Shuiping Ou + 3 more
Spatial epidemiology, as an important branch of epidemiology, has undergone a significant paradigm shift from infectious disease prevention and control to chronic disease management. This paper systematically reviews the application progress of spatial epidemiology in the study of infectious diseases (e.g., malaria…
Hongyan Cao, Gaiqin Liu, Jingyi Xia, Runle Chen + 8 more
Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we…
Kaushi S. T. Kanankege, Julio Alvarez, Lin Zhang, Andres M. Perez
Spatiotemporal visualization and analytical tools (SATs) are increasingly being applied to risk-based surveillance/monitoring of adverse health events affecting humans, animals, and ecosystems. Different disciplines use diverse SATs to address similar research questions. The juxtaposition of these diverse techniques…
Holger Engleitner, Ashwani Jha, Marta Suárez‐Pinilla, Amy Nelson + 5 more
'Daniel M. Herron' 'Geraint Rees' 'Karl Friston' 'Martin N. Rossor' 'Parashkev Nachev'] The characteristics and determinants of health and disease are often organised in space, reflecting our spatially extended nature. Understanding the influence of such factors requires models capable of capturing spatial relations.…
Niklas Kleinenkuhnen, David Köhler, Till Baar, Chrysa Nikopoulou + 4 more
We introduce a multivariate statistical approach for pattern recognition in spatial transcriptomics data. Our algorithm (SPACO) constructs a low-dimensional projection of the data maximising Moran’s I, which mitigates non-spatial variation and outperforms PCA for pre-processing. Our method also provides a calibrated…
Qi Liu, Chih-Yuan Hsu, Yu Shyr
The expeditious growth in spatial omics technologies enable profiling genome-wide molecular events at molecular and single-cell resolution, highlighting a need for fast and reliable methods to characterize spatial patterns. We developed SpaGene, a model-free method to discover any spatial patterns rapidly in large…
Lee Mason, Blánaid Hicks, Jonas S. Almeida
of Spatial Clusters Over Time Authors: Lee Mason, Blánaid Hicks, Jonas S. Almeida Title: ClusterRadar: an Interactive Web-Tool for the Multi-Method Exploration of Spatial Clusters Over Time Authors: Lee Mason, Blánaid Hicks, Jonas S. Almeida Content: # 2.1 Geospatial data Geospatial data comprises data points…
Guoxin Cai, Yichang Chen, Xun Gu, Zhan Zhou
Spatial transcriptomics enables the depiction of in situ gene expression and could further be applied to infer the mechanism of cell functions. In this study, we present Spanve (Spatial Neighborhood Variably Expressed Genes), a statistic based approach to detect space-dependent expressed genes from spatial…
Yalin Li, John Trimmer, Steven Hand, Xinyi Zhang + 6 more
The pursuit of sustainability has catalyzed broad investment in the research, development, and deployment (RD&D) of innovative water, sanitation, and resource recovery technologies, yet the lack of transparent and agile methodologies to navigate the expansive landscape of technology development pathways remains a…
Arun Sharma, Zhe Jiang, Shashi Shekhar
Spatiotemporal data mining aims to discover interesting, useful but non-trivial patterns in big spatial and spatiotemporal data. They are used in various application domains such as public safety, ecology, epidemiology, earth science etc. This problem is challenging because of the high societal cost of spurious…
Authors not listed
In software maintenance work, software architects and programmers need to identify modules that require modification or deletion. Whilst user requests and bug reports are utilised for this purpose, evaluating the execution status of modules within the software is also crucial. This paper, therefore, applies spatial…
Kori Khan, Candace Berrett
In the last two decades, considerable research has been devoted to a phenomenon known as spatial confounding. Spatial confounding is thought to occur when there is multicollinearity between a covariate and the random effect in a spatial regression model. This multicollinearity is considered highly problematic when the…
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…
Mei Tessum, Susan Anenberg, Zoe Chafe, Daven Henze + 4 more
To improve air quality, knowledge of the sources and locations of air pollutant emissions is critical. However, for many global cities, no previous estimates exist of how much exposure to fine particulate matter (PM2.5), the largest environmental cause of mortality, is caused by emissions within the city vs. outside…
Marcos O. Prates, Érica Castilho Rodrigues, Renato Assunção
Spatial confounding between the spatial random effects and fixed effects covariates has been recently discovered and showed that it may bring misleading interpretation to the model results. Solutions to alleviate this problem are based on decomposing the spatial random effect and fitting a restricted spatial…
Sarah Chambliss, Carlos Pinon, Kyle Messier, Brian LaFranchi + 5 more
Disparity in air pollution exposure arises from variation at multiple spatial scales: along urbanto-rural gradients, between individual cities within a metropolitan region, within individual neighborhoods, and between city blocks. Here, we improve on existing capabilities to systematically compare urban variation at…
Authors not listed
People of color in the United States are disproportionately and unfairly exposed to air pollution. Equity-oriented scientific evaluations quantifying these disparities often use population-average exposure metrics to capture the overall inequality within a system. Utilizing these metrics involves choices about the…
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…