scholarly journals Lattice Studies of Gerrymandering Strategies

2020 ◽  
pp. 1-26
Author(s):  
Kyle Gatesman ◽  
James Unwin
Keyword(s):  
Spatial Data ◽  
Lattice Models ◽  
Theoretical Method ◽  
Population Fluctuations ◽  
Monte Carlo Techniques ◽  
Voter Models ◽  
Novel Algorithms ◽  
The Impact ◽  
Equal Population ◽  
Isoperimetric Quotient

Abstract A new theoretical method for examining gerrymandering is presented based on lattice models of voters, in which districts are constructed by partitioning the lattice. We propose three novel algorithms for constructing equal-population, connected districts which favor the gerrymanderer and incorporate the spatial distribution of voters. Due to the probabilistic population fluctuations inherent to our voter models, Monte Carlo techniques can be applied to study the impact of gerrymandering. We use the method developed here to compare our different gerrymandering algorithms, show approaches which ignore spatial data lead to (legally prohibited) disconnected districts, and examine the effectiveness of isoperimetric quotient tests.

scholarly journals Leveraging Road Characteristics and Contributor Behaviour for Assessing Road Type Quality in OSM

2021 ◽  
Vol 10 (7) ◽  
pp. 436
Author(s):  
Amerah Alghanim ◽  
Musfira Jilani ◽  
Michela Bertolotto ◽  
Gavin McArdle
Keyword(s):  
Machine Learning ◽  
Spatial Data ◽  
Classification Accuracy ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Data Set ◽  
Semantic Inference ◽  
Road Type ◽  
The Impact

Volunteered Geographic Information (VGI) is often collected by non-expert users. This raises concerns about the quality and veracity of such data. There has been much effort to understand and quantify the quality of VGI. Extrinsic measures which compare VGI to authoritative data sources such as National Mapping Agencies are common but the cost and slow update frequency of such data hinder the task. On the other hand, intrinsic measures which compare the data to heuristics or models built from the VGI data are becoming increasingly popular. Supervised machine learning techniques are particularly suitable for intrinsic measures of quality where they can infer and predict the properties of spatial data. In this article we are interested in assessing the quality of semantic information, such as the road type, associated with data in OpenStreetMap (OSM). We have developed a machine learning approach which utilises new intrinsic input features collected from the VGI dataset. Specifically, using our proposed novel approach we obtained an average classification accuracy of 84.12%. This result outperforms existing techniques on the same semantic inference task. The trustworthiness of the data used for developing and training machine learning models is important. To address this issue we have also developed a new measure for this using direct and indirect characteristics of OSM data such as its edit history along with an assessment of the users who contributed the data. An evaluation of the impact of data determined to be trustworthy within the machine learning model shows that the trusted data collected with the new approach improves the prediction accuracy of our machine learning technique. Specifically, our results demonstrate that the classification accuracy of our developed model is 87.75% when applied to a trusted dataset and 57.98% when applied to an untrusted dataset. Consequently, such results can be used to assess the quality of OSM and suggest improvements to the data set.

scholarly journals Econometric Analysis of the Impact of Propensities on Economic Occurrences: A Macroeconomic Perspective

2012 ◽  
Vol 10 (2) ◽  
pp. 138-154 ◽  
Author(s):  
Mariusz Doszyń
Keyword(s):  
Spatial Data ◽  
Fixed Effects ◽  
Classical Model ◽  
Econometric Analysis ◽  
Dummy Variables ◽  
Macroeconomic Variables ◽  
Current State ◽  
Famous Book ◽  
Direct Models ◽  
The Impact

Econometric Analysis of the Impact of Propensities on Economic Occurrences: A Macroeconomic PerspectiveThe main aim of this article was the specification of problems connected with analysis of impact of human propensities on economic occurrences and also a proposition of econometric tools enabling the identification of this impact. According to the meaning of propensities in economics the current state of knowledge is mostly an effect of considerations presented by J.M. Keynes in his famous book "The General Theory of Employment, Interest and Money" where J.M. Keynes proposed such economic categories as the average and marginal propensities. One of the goals of the presented deliberations was to specify problems related with economic theory of propensities. Such propensities as a propensity to consume, to save, to invest and thesaurisation were particularly carefully analysed. The impact of these propensities on basic macroeconomic variables was considered with respect to the classical model, the neoclassical Solow-Swan model and theIS-LMscheme. In case of spatial data the effects of the impact of propensities could be analysed by means of models with dummy variables showing presence of given propensities. A procedure enabling the construction of such variables was proposed. In case of time series, conceptions delivered by the integration and cointegration theory could be applied. Especially such models as VAR and VECM could be useful. Models for panel data enable direct (models with fixed effects) or indirect (models with random effects) consideration of the impact of propensities on the analysed processes.

scholarly journals Convex hull as a heuristic

2018 ◽  
Author(s):  
Naama Katzin
Keyword(s):  
Computer Simulation ◽  
Convex Hull ◽  
Physical Properties ◽  
Spatial Data ◽  
Good Predictor ◽  
Numerical Cognition ◽  
Numerical Estimation ◽  
Geometrical Properties ◽  
Numerical Discrimination ◽  
The Impact

Recent studies in the field of numerical cognition quantify the impact of physical properties of an array on its enumeration, demonstrating that enumeration relies on the perception of these properties. This paper marks a shift in reasoning as it changes the focus from demonstrating this effect to explaining it. Interestingly, we were inspired by one of the very first articles in the field, “The power of numerical discrimination” by Stanley Jevons that was published in Nature in 1871. In his report, Jevons attempts to answer the question of how many objects can be perceived in “a single mental beat of attention”. We relate directly to Jevons’s records, putting forward a plausible heuristic mechanism that relies on the physical geometrical properties of the arrays to be enumerated. We use a mathematical theorem and computer simulation to show that the shape of the convex hull, the smallest polygon containing all dots in an array, is a good predictor of numerosity. We show that convex hull downsamples the spatial data, allowing quick and fairly accurate numerical estimation. Moreover, convex hull predictability changes as numerosity grows, corresponding to the psychophysical curve of enumeration shown by Jevons and many others that followed.

scholarly journals Przyszłość systemów rejestracji nieruchomości wobec rozwoju inteligentnych technologii. Wybrane problemy prawne na tle wniosków z konferencji „Common Vision Conference 2016. Migration to a Smart World”, Amsterdam, 5–7 czerwca 2016 roku

2017 ◽  
Vol 15 (2) ◽  
pp. 301-320
Author(s):  
Maria Kaczorowska
Keyword(s):  
Spatial Data ◽  
Data Exchange ◽  
Spatial Information ◽  
Smart Cities ◽  
Information Service ◽  
Advanced Technology ◽  
Technological Advancement ◽  
Land Registration ◽  
The Impact ◽  
Common Vision

The development of information technologies offers new possibilities of use of information collected in public registers, such as land registers and cadastres, which play a significant role in establishing the infrastructure for spatial information. Efficient use of spatial information systems with the purpose of a sustainable land management shall be based on en suring the interconnection of different information resources, data exchange, as well as a broad access to data. The role of land registration systems in the context of technological advancement was the subject of the Common Vision Conference 2016. Migration to a Smart World, held on 5–7 June 2016 in Amsterdam. The conference was organized by Europe’s five leading mapping, cadastre and land registry associations, cooperating within a “Common Vision” agreement: EuroGeographics, Permanent Committee on Cadastre, European Land Registries Association, European Land Information Service and Council of European Geodetic Surveyors. The discussion during the conference focused on topics regarding the idea of smart cities, marine cadastre, interoperability of spatial data, as well as the impact of land registers and cadastres on creating the infrastructure for spatial information and developing e-government, at both national and European levels. The paper aims to present an overview of issues covered by the conference and also to highlight some important problems arising from implementing advanced technology solutions in the field of land registration.

scholarly journals Well Water Site Selection at Local Scale Using Geographical Information System for Flood Victim in Malaysia

2018 ◽  
Vol 50 (2) ◽  
pp. 205
Author(s):  
Koh Liew See ◽  
Nayan Nasir ◽  
Saleh Yazid ◽  
Hashim Mohmadisa ◽  
Mahat Hanifah ◽  
...  
Keyword(s):  
Water Supply ◽  
Spatial Data ◽  
Water Sources ◽  
Geographical Information ◽  
Well Water ◽  
Clean Water ◽  
Flood Events ◽  
Field Methods ◽  
The Impact ◽  
Area Data

Clean water supply is a major problem among flood victims during flood events. This article aims to determine the sites of well water sources that can be utilised during floods in the District of Kuala Krai, Kelantan. Field methods and Geographic Information Systems (GIS) were applied in the process of selecting flood victim evacuation centres and wells. The data used were spatial data obtained primarily, namely the well data, evacuation centre data and flood area data. The well and evacuation centre data were obtained by field methods conducted to determine the position of wells using global positioning system tools, and the same for the location of the evacuation centres. Information related to evacuation centres was obtained secondarily from multiple agencies and gathered into GIS as an evacuation centre attribute. The flood area data was also obtained via secondary data and was digitised using the ArcGIS software. The data processing was divided into two stages, namely the first stage of determining the flood victim evacuation centres to be used in this research in a structural manner based on two main criteria which were the extent to which an evacuation centre was affected by the flood and the highest capacity of victims for each district with the greatest impact to the flood affected population. The second stage was to determine the location of wells based on three criteria, namely i) not affected by flood, ii) the closest distance to the selected flood victim evacuation centre and iii) located at different locations. Among the main GIS analyses used were locational analysis, overlay analysis, and proximity analysis. The results showed that four (4) flood evacuation centres had been chosen and matched the criteria set, namely SMK Sultan Yahya Petra 2, SMK Manek Urai Lama, SMK Laloh and SK Kuala Gris. While six (6) wells had been selected as water sources that could be consumed by the flood victims at 4 evacuation centres in helping to provide clean water supply, namely Kg. Keroh 16 (T1), Kg. Batu Mengkebang 10 (T2), Lepan Meranti (T3), Kg. Budi (T4), Kg. Jelawang Tengah 2 (T5) and Kg. Durian Hijau 1 (T6). With the presence of the well water sources that can be used during flood events, clean water supply can be distributed to flood victims at the evacuation centres. Indirectly, this research can reduce the impact of floods in the future, especially in terms of clean water supply even during the hit of a major flood.

scholarly journals Integration of Environmental Information in a Mining Region Using a Geoportal

2021 ◽  
Vol 278 ◽  
pp. 01013
Author(s):  
Svetlana Ivanova ◽  
Elena Sant’eva ◽  
Maxim Bakanov ◽  
Leszek Sobik ◽  
Leonid Lopukhinsky
Keyword(s):  
Spatial Data ◽  
Environmental Information ◽  
Environmental Data ◽  
Information Support ◽  
Direct Access ◽  
Complex Nature ◽  
Mining Operations ◽  
Technological Support ◽  
Multidimensional Information ◽  
The Impact

At present, the complex nature of the impact on the ecosystem in regions with intensive mining creates a multidimensional information “plume” consisting of data on mineral reserves, the state of mining operations, accumulated, current and future environmental pollution. The transition to the lean use of the subsoil and the reasonable disposal of mining waste requires fundamentally new forms of environmental information accumulation and processing during designing new enterprises and regulating the activities of existing ones. The most promising form of information support for the greening of mining is a geoportal. It is a complex of software and technological support for working with spatial data. Its key task is to provide the users with tools and services for storing and cataloging, publishing and loading spatial and environmental data, searching and filtering by metadata, interactive web visualization, direct access to geodata based on map web services.

Formation of High-Quality Solutions In The Construction of Aeromonitoring Data Banks

2021 ◽  
Author(s):  
Hlib Nekrasov ◽  
Alexander Vostrikov ◽  
Ekaterina Prokofeva ◽  
Nashon Adero
Keyword(s):  
Spatial Data ◽  
Carbon Dioxide Emissions ◽  
Geographic Area ◽  
Subject Area ◽  
Web Gis ◽  
Stable Operation ◽  
Additional Information ◽  
Methods Of Evaluation ◽  
Processing And Storage ◽  
The Impact

Abstract Background: This article discusses the approach to the implementation of the project for the extraction and the methodology of preliminary processing of the obtained data with the aim of centralized accumulation for collective multipurpose use of the databank on the example of carbon dioxide emissions into the atmosphere by air transport for a given territory. It should be noted that on the basis of morphological analysis, processing, as well as the classification of spatial objects of the geodatabase and additional information, it is subsequently possible to organize, for example, a system of geoecological monitoring.Methods: At the fundamental level, the research used integration and process-based approaches, the method of extrapolation, expert methods of evaluation, random selection and analytical comparisons, a set of methods of spatial analysis based on various instruments and sources. In this study are used of open standards OGC, web, GIS technologies and the Internet for the formation, processing and storage of spatial data, their unambiguous geolocation, the implementation of territorial selections and visualization of results.Results: The set of data, which was organized according to the proposed and defined rules, made it possible to assess the structural processing of geospatial data, and to prepare a visual representation of the impact of aviation on the environmental situation over the designated geographic area.Conclusions: The transport industry was chosen as the object of research, but this solution can also be successfully applied to other logistics and industrial areas. During the implementation of the project, the analysis of the subject area was carried out, the architecture of the future prototype of the databank was designed, the accumulated data from the sources was structured, and a database was selected for storing them, taking into account the provision of high availability and ensuring stable operation under high loads. For the convenience of displaying data, an interactive visualization tool with a convenient and friendly user interface has been developed.

scholarly journals An Integrated GIS Methodology to Assess the Impact of Engineering Maintenance Activities: A Case Study of Dredging Projects

2020 ◽  
Vol 8 (3) ◽  
pp. 186
Author(s):  
Pedro Magaña ◽  
Miguel Á. Reyes-Merlo ◽  
Ángela Tintoré ◽  
Carmen Zarzuelo ◽  
Miguel Ortega-Sánchez
Keyword(s):  
Spatial Data ◽  
Methodological Approach ◽  
Decision Making Process ◽  
Regional Government ◽  
Fully Integrated ◽  
Maintenance Activities ◽  
Social Environmental ◽  
Design Databases ◽  
The Impact

Engineering infrastructures require regular maintenance and/or repair activities that have important social, environmental, and economic impacts. Despite their growing importance, few studies have focused on fully integrated analyses. This work presents a general methodological approach to design databases of engineering maintenance activities for their assessment. This methodology was applied to the case of dredging projects in the ports managed by the Andalusian Regional Government (Spain). The resulting database contains 87 fields of information obtained from the analysis of 70 activities performed between 1993 and 2015. This database is free, public, and available to the scientific community, and it was implemented in PostgreSQL using the PostGIS extension for spatial data; therefore, it can be integrated in a GIS. The assessment of deviations from the initial projects and the comparison between locations enhanced our methodology, which represents a valuable tool not only for scientists and managers to improve the decision-making process when planning future strategies, but also to evaluate the environmental impacts.

scholarly journals Spatial-Temporal Characteristics in Grain Production and Its Influencing Factors in the Huang-Huai-Hai Plain from 1995 to 2018

2020 ◽  
Vol 17 (24) ◽  
pp. 9193
Author(s):  
Chunshan Zhou ◽  
Rongrong Zhang ◽  
Xiaoju Ning ◽  
Zhicheng Zheng
Keyword(s):  
Influencing Factors ◽  
Spatial Data ◽  
Spatial Data Analysis ◽  
Grain Production ◽  
Temporal Characteristics ◽  
Spatial Panel ◽  
Geographically Weighted Regression Model ◽  
Northern Areas ◽  
Spatial Panel Data ◽  
The Impact

The Huang-Huai-Hai Plain is the major crop-producing region in China. Based on the climate and socio-economic data from 1995 to 2018, we analyzed the spatial–temporal characteristics in grain production and its influencing factors by using exploratory spatial data analysis, a gravity center model, a spatial panel data model, and a geographically weighted regression model. The results indicated the following: (1) The grain production of eastern and southern areas was higher, while that of western and northern areas was lower; (2) The grain production center in the Huang-Huai-Hai Plain shifted from the southeast to northwest in Tai’an, and was distributed stably at the border between Jining and Tai’an; (3) The global spatial autocorrelation experienced a changing process of “decline–growth–decline”, and the area of hot and cold spots was gradually reduced and stabilized, which indicated that the polarization of grain production in local areas gradually weakened and the spatial difference gradually decreased in the Huang-Huai-Hai Plain; (4) The impact of socio-economic factors has been continuously enhanced while the role of climate factors in grain production has been gradually weakened. The ratio of the effective irrigated area, the amount of fertilizer applied per unit sown area, and the average per capita annual income of rural residents were conducive to the increase in grain production in the Huang-Huai-Hai Plain; however, the effect of the annual precipitation on grain production has become weaker. More importantly, the association between the three factors and grain production was found to be spatially heterogeneous at the local geographic level.

The Fifth Troll Prerequisite

Cyberwar ◽  
2020 ◽  
pp. 141-154
Author(s):  
Kathleen Hall Jamieson
Keyword(s):  
Social Media ◽  
Organic Content ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Social Media Platforms ◽  
Voter Models ◽  
The Impact ◽  
The U.S

Chapter 8 focuses on the fifth troll prerequisite which needed to be met if hacked and Russian-generated content were to influence the U.S. election: was it targeted to reach the desired constituencies? The chapter contends that, despite some arguments against the impact of the Russian troll messaging, the trolls targeted audiences needed to influence the election in both battleground and nonbattleground states, through the use of organic content and paid advertisements. The trolls had access to multiple sources of information about how to reach voters susceptible to mobilizing or demobilizing appeals, including publicly accessible analyses of the candidates’ objectives and tactics, stolen voter models hacked from the Democratic Congressional Campaign Committee, and toolkits offered by social media platforms to help identify desired audience members.

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