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Introduction to Reproducible geospatial analysis and Figures in R: A Tutorial Article

data 2024年第4期9卷 58-58页

作者： Maesen, Philippe Salingros, Edouard Univ Liege Fac Gembloux Agrobio Tech BEAGx B-5030 Gembloux Belgium

The present article is intended to serve an educational purpose for data scientists and students who already have experience with the R language and which to start using it for geospatial analysis and map creation. The basic concepts of raster data, vector data, CRS and datum are first presented along with a basic workflow to conduct reproducible geospatial research in R. Examples of important types of maps (scatter, bubble, choropleth, hexbin and faceted) created from open-source environmental data are illustrated and their practical implementation in R is discussed. Through these examples, essential manipulations on geospatial vector data are demonstrated (reading, transforming CRS, creating geometries from scratch, buffer zones around existing geometries and intersections between geometries).

关键词： tutorial R geospatial data analysis maps reproducible research

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Collectively Learned Multi-level Spatial Embeddings for Residential Rental Price Prediction

Collectively Learned Multi-level Spatial Embeddings for Resi...

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9th IEEE International Conference on Big data (IEEE Bigdata)

作者： Wang, Wenlu Pan, Chen Texas A&M Univ Corpus Christi Dept Comp Sci Corpus Christi TX 78412 USA

ISBN: (纸本)9781665439022

geospatial Location is often treated as the golden thread of data analysis while heterogeneous data is connected through the locality. Heterogeneous data integration via location is challenging and very essential in data analysis. For example, a rental price of a residential property is determined by interior factors (e.g., area of the property and interior design) and also external factors related to locality. The key challenge is incorporating data from various sources connected by locality and modeling the joint decision-making process. We propose to use different embeddings to collectively learn the representations of different data jointly while preserving the rental price prediction. The benefit of our heterogeneous data integration design is to model the interactions among all the factors contributing to our predefined task and achieve different levels of abstraction using multi-level spatial representations.

关键词： geospatial data analysis Spatial Embedding

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Tuberculosis Prevention Model in Developing Countries based on geospatial, Cloud and Web Technologies

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2020年第1期11卷 219-232页

作者： Mwila, Innocent Phiri, Jackson Univ Zambia Dept Elect & Elect Engn Lusaka Zambia Univ Zambia Dept Comp Sci Lusaka Zambia

Information is important when making decisions. Decisions which are based on gut feeling and made in the absence of evidence always tend to be less effective in most situations. This is also the case when it comes to Tuberculosis (TB) disease control and prevention intervention planning and implementation. The lack of evidence-based information upon which decisions for action to help with the prevention of spread of TB has proved to be less effective in the prevention of the disease as TB keeps spreading. The aim of this paper was to design and develop a prototype system that would provide TB program managers with information and tools which can be used to make decisions which can effectively influence the fight against the spread of TB through the application of cloud computing, geospatial data analysis and web technologies. The system would improve disease monitoring and tracking through the use of the identified technologies, by displaying the geographical distribution of TB cases in the communities on a mapping application as well as providing reports which TB program managers can use to make decisions when planning and implementing disease control and prevention activities.

关键词： Evidence-based monitoring cloud computing geospatial data analysis mapping web technologies information decision-making tuberculosis prevention

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How much district heating in a future sector-coupled energy system? A comprehensive methodology for mapping and clustering the infrastructure costs on an entire territory

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Energy 2025年 330卷

作者： L.M. Hofmann A. Clerjon F. Perdu R. Bavière P. Azaïs CEA DES I-Tésé Université Paris Saclay Gif sur Yvette France Univ. Grenoble Alpes IMEP2 110 rue de la Chimie 38400 Saint-Martin-d'Hères France Univ. Grenoble Alpes CEA LITEN F-38000 Grenoble France DistrictLab 26 rue Gustave Eiffel 38000 Grenoble France Univ. Grenoble Alpes CEA DES DPE 17 rue des Martyrs 38054 Grenoble France

In the energy transition context, district heating have great potential for generating low-carbon and cost-effective heat. They can also provide flexibility to the electrical system thanks to sector coupling solutions and thermal energy storage allowing, for instance, better integration of intermittent renewable energy sources. Therefore, assessing the competitiveness of district heating would require a sector-coupled optimisation model with, as an input parameter, the costs of the district heating infrastructure estimated throughout the entire territory (a geographic zone of a given size) at a high spatial resolution, gathered in ready-to-implement clusters. Building on the work from Persson and Werner, we present a methodology to map and cluster district heating network costs on an entire territory. It relies on easy-to-access geospatial key variables such as heat demand, building density and winter temperatures. As a case study, we apply it to France and design two clustering approaches to gather the infrastructure costs: competitiveness-based and territory typology-based – to satisfy different model architectures. We observe, for instance, a 51 TWh annual heat supply potential for district heating in French urban areas for a total investment of 10 b€. With this comprehensive and replicable methodology, we aim to pave the way for a new and more accurate competitiveness assessment of district heating in sector-coupled models.

关键词： District heating District heating network Clustering Investment cost assessment geospatial data analysis Heat-and-electricity coupling Energy system modelling

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Modeling women's perceived level of safety at night in Milan☆

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JOURNAL OF TRANSPORT GEOGRAPHY 2025年 127卷

作者： Messa, Federico Scarponi, Lily Abdelfattah, Lamia Carpentieri, Gerardo Martinelli, Valerio Stiuso, Tonia Gorrini, Andrea Fdn Transform Transport ETS Via Lovanio 8 I-20121 Milan Italy Univ Napoli Federico II Dipartimento Ingn Civile Edile & Ambientale TeMA Lab Naples Italy

This article outlines the data analysis and modeling processes of the perceived level of safety for women at night time in the city of Milan. This research effort consists of the final phase of the STEP UP project, which was aimed to assess walkability for women in Milan using geospatial data analysis methods and involved three phases: literature review, data collection, and data analysis. The modeling of perceived safety proposed in this paper takes into consideration a wide set of geospatial data, acquired from open data and proprietary platforms, quantifying factors identified in the literature review, and the Wher app data, a crowdsourced dataset of women's self-disclosed perceived safety on the street network. These two sets of information are used to explore the relationship between the built environment and safety perception. Moreover, this article covers the processes of filtering the factors emerged from scientific literature, and the translation from concepts into operationalizable quantitative indicators. The process of identifying the relations between the safety factors and the perceived safety consisted in testing several statistical models, ultimately leading to the implementation of a Geographically Weighted Regression (GWR) model, which appeared as the most suitable for capturing the spatial heterogeneity of the factors. The results of the project showed the presence of three statistically significant indicators, namely Public Lighting, Public Transport, and Food & Beverage, and include the spatial variation of Local R2 and Beta coefficient values, allowing for the inference of site-specific phenomena and complexities. Overall, the approach proposed in this article aims to bridge the gap between subjective crowdsourced data and city characteristics data, proposing a layered methodology to fine-tune the association between factors relevant to safety and geospatial data. It also proposed a quantitative approach to model the nighttime safety perception

关键词： Gendered walkability geospatial data analysis Geographically weighted regression model Safety perception in public spaces

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Multiscale Graph Theoretical Tools Reveal Subtle Patterns in Big geospatial data 5

Multiscale Graph Theoretical Tools Reveal Subtle Patterns in...

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IEEE International Conference on Big data (IEEE Big data)

作者： Hagan, Ronald D. Phillips, Charles A. Langston, Michael A. Rhodes, Bradley J. BAE Syst Burlington MA 01803 USA Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN 37996 USA

ISBN: (纸本)9781538627150

This paper describes a framework combining graph theoretical tools and metrics with machine learning to analyze big geospatial data. By combining multiple methods targeted to different levels of resolution, this approach detects subtle normalcy patterns that would otherwise remain hidden to any single approach. Initial feasibility testing shows the applicability of the proposed methods to data from trip records of New York City taxis.

关键词： geospatial data analysis graph theory normalcy modeling

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Assessment of the Spatial Distribution of Wild and Cultivated Ensete ventricosum in Ethiopia Using geospatial Tools

Assessment of the Spatial Distribution of Wild and Cultivate...

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作者： Awoke, Meron Addis Ababa University

学位级别：硕士

Ensete ventricosum varieties are important for agricultural and economic developments of Ethiopia. However, little information is documented on the existing characteristics of ensete and distribution of different ensete verities across different agro-ecological zones. Hence, analyzing the spatial distribution of these species at spatial and temporal scale is of great importance for resource management and conservation planning. This study is attempted to identify, map and model the distribution of wild and cultivated Ensete ventricosum (ensete) with respective to land cover, climate, natural vegetation cover and agroecological zones. For this purpose, geospatial data analysis and MaxEnt modeling techniques were used to map the probabilistic distribution of both wild and cultivated verities. About 26 environmental factors were utilized as variables for distribution and modeling these includes 19 bioclimatic variables, DEM, LU/LC, vegetation, agro-ecology and soil type, and 192 cultivated and 20 wild ensete species records. Besides, Pearson correlation analyses were undertaken for 26 environmental variables to reduce highly correlated variables. The MaxEnt modeling has proven to be very effective at determining habitat use and species distributions for a variety of species and localities. The average test Area under curve (AUC) for the replicate runs was 0.842, and the standard deviation was, 0.046 and AUC 0.760 with standard deviation of 0.101 for cultivated ensete and wild ensete, respectively. Out of the determinants, the annual rainfall (15.7%) and LU/LC (53.7%) were the most important environmental variables that highly affected the distribution of cultivated and wild ensete, respectively. In addition, about 1.55% of the study area was covered by primarily hotpot areas of cultivated and 3.6% is for wild ensete. The probabilistic distribution of cultivated ensete is higher in the southern region, some part of Oromia region, and little areas of southern and eastern

关键词： MaxEnt modeling AUC Ensete ventricosum geospatial data analysis

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A general theory of spatial relations to support a graphical tool for visual information extraction

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JOURNAL OF VISUAL LANGUAGES AND COMPUTING 2013年第2期24卷 71-87页

作者： Della Penna, Giuseppe Magazzeni, Daniele Orefice, Sergio Univ Aquila Dept Comp Sci I-67100 Laquila Italy Kings Coll London Dept Informat London WC2R 2LS England

In this paper we present a general spatial composition framework which allows one to model the graphical objects and the spatial relations of a large class of visual languages. The new formalism has been implemented within the SRQ tool, a software system for the Visual Information Extraction, enabling it to work on a wider range of domains. In particular, in the paper we describe the application of SRQ to geospatial data. (c) 2012 Elsevier Ltd. All rights reserved.

关键词： Information extraction Visual information search Spatial relations geospatial data analysis

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Movement of trichloroethene in a discontinuous permafrost zone

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JOURNAL OF CONTAMINANT HYDROLOGY 2011年第1-4期124卷 1-13页

作者： Carlson, Andrea E. Barnes, David L. Univ Alaska Fairbanks Civil & Environm Engn Water & Environm Res Ctr Fairbanks AK 99775 USA Shannon & Wilson Inc Fairbanks AK USA

At a site with discontinuous permafrost in Fairbanks, Alaska, releases of trichloroethene (TCE), an industrial solvent, have caused contamination of the groundwater. The objective of this study was to investigate the relationship between the migration pathway of the TCE groundwater plume and the distribution of the discontinuous permafrost at the site. The ICE plume configuration is substantially different than what regional hydrology trends would predict. Using GIS, we conducted a geostatistical analysis of field data collected during soil-boring installations and groundwater monitoring well sampling. With the analysis results, we constructed maps of the permafrost-table elevation (top of permafrost) and of the groundwater gradients and ICE concentrations from multiyear groundwater sampling events. The plume concentrations and groundwater gradients were overlain on the permafrost map to correlate permafrost locations with groundwater movement and the spatial distribution of ICE moving with groundwater. Correlation of the overlay maps revealed converging and diverging groundwater flow in response to the permafrost-table distribution, the absence of groundwater contamination in areas with a high permafrost-table elevation, and channeling of contaminants and water between areas of permafrost. In addition, we measured groundwater elevations in nested wells to quantify vertical gradients affecting ICE migration. At one set of nested wells down gradient from an area of permafrost we measured an upward vertical gradient indicating recharge of groundwater from the subpermafrost region of the aquifer causing dilution of the plume. The study indicates that the variable distribution of the permafrost is affecting the way groundwater and ICE move through the aquifer. Consequently, changes to the permafrost configuration due to thawing would likely affect both groundwater movement and TCE migration, and areas that were contaminant-free may become susceptible to contamination. (

关键词： Discontinuous permafrost Trichloroethene Vertical groundwater gradients geospatial data analysis

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Density Equalizing Distortion of Large Geographic Point Sets

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CARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE 2009年第3期36卷 237-250页

作者： Bak, Peter Schaefer, Matthias Stoffel, Andreas Keim, Daniel A. Omer, Itzhak Univ Konstanz D-7750 Constance Germany Tel Aviv Univ Tel Aviv Israel

Visualizing large geo-demographical datasets Using pixel-based techniques involves mapping the geospatial dimensions of a data point to screen coordinates and appropriately encoding its statistical value by color. The analysis of such data presents a great challenge. General tasks involve clustering, categorization, and searching for patterns of interest for sociological or economic research. Available visual encodings and screen space limitations lead to over-plotting and hiding of patterns and clusters in (tensely populated areas, while sparsely populated areas waste space and draw the attention away from the areas of interest. In this paper, two new approaches (RadialScale and AngularScale) are introduced to create density-equalized maps, while preserving recognizable features and neighborhoods in the visualization. These approaches build the core of a multi-scaling technique based oil local features of the data described its local minima and maxima of point density. Scaling is conducted several times around these features, Which leads to more homogeneous distortions. Results are illustrated using several real-world datasets. Our evaluation shows that the proposed techniques outperform traditional techniques as regard the homogeneity of the resulting data distributions and therefore build a more appropriate basis For analytic purposes.

关键词： geospatial data analysis geographic visualization point density distortions and scaling

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