scholarly journals A Bayesian Approach to Estimate the Spatial Distribution of Crowdsourced Radiation Measurements around Fukushima

2021 ◽  
Vol 10 (12) ◽  
pp. 822
Author(s):  
Carolynne Hultquist ◽  
Zita Oravecz ◽  
Guido Cervone
Keyword(s):  
Decision Making ◽  
Spatial Distribution ◽  
Bayesian Approach ◽  
Spatial Data ◽  
Situational Awareness ◽  
Probabilistic Approach ◽  
Spatial Uncertainty ◽  
Crowdsourced Data ◽  
Spatio Temporal ◽  
Radiation Measurements

Citizen-led movements producing spatio-temporal big data are potential sources of useful information during hazards. Yet, the sampling of crowdsourced data is often opportunistic and the statistical variations in the datasets are not typically assessed. There is a scientific need to understand the characteristics and geostatistical variability of big spatial data from these diverse sources if they are to be used for decision making. Crowdsourced radiation measurements can be visualized as raw, often overlapping, points or processed for an aggregated comparison with traditional sources to confirm patterns of elevated radiation levels. However, crowdsourced data from citizen-led projects do not typically use a spatial sampling method so classical geostatistical techniques may not seamlessly be applied. Standard aggregation and interpolation methods were adapted to represent variance, sampling patterns, and the reliability of modeled trends. Finally, a Bayesian approach was used to model the spatial distribution of crowdsourced radiation measurements around Fukushima and quantify uncertainty introduced by the spatial data characteristics. Bayesian kriging of the crowdsourced data captures hotspots and the probabilistic approach could provide timely contextualized information that can improve situational awareness during hazards. This paper calls for the development of methods and metrics to clearly communicate spatial uncertainty by evaluating data characteristics, representing observational gaps and model error, and providing probabilistic outputs for decision making.

Spatial Econometric Analysis of Cultivated Land Change and its Influencing Factors in the Poyang Lake Eco-Economics Zone

2013 ◽  
Vol 864-867 ◽  
pp. 2659-2664
Author(s):  
Peng Wang ◽  
Qu Liu ◽  
Hua Lin Xie
Keyword(s):  
Spatial Distribution ◽  
Influencing Factors ◽  
Spatial Data ◽  
Poyang Lake ◽  
Spatial Data Analysis ◽  
Cultivated Land ◽  
Land Change ◽  
Spatial Econometric ◽  
Agricultural Growth ◽  
Spatio Temporal

Spatio-temporal pattern of cultivated land change and its influencing factors in the Poyang Lake Ecological Economic Zone were conducted by exploratory spatial data analysis and spatial autocorrelation analysis. Results show that there is an obvious correlation for the spatial distribution of cultivated land in the Poyang Lake Eco-economics Zone. Its value of Morans I reduced from 0.4574 in 2002 to 0.4092 in 2008, and then increased to 0.4352 in 2009, which roughly presented a "U" type distribution. Total population is the most important factor that affecting the change of cultivated areas in the Poyang Lake Eco-economics Zone. Agricultural growth, average wage of urban residents and the fixed assets investment are also the main driving factors. Spatial auto-regression model is an effective tool for revaluating the spatial distribution of regional cultivated land, and revealing the evolution mechanisms of cultivated land.

GEOGRAPHIC COMMUNICATION FOR SUSTAINABLE DECISIONS / GEOGRAFINĖS INFORMACIJOS KOMUNIKAVIMO PRIEMONĖS IR TVARIOJI PLĖTRA

2010 ◽  
Vol 16 (4) ◽  
pp. 603-612 ◽  
Author(s):  
Giedrė Beconytė ◽  
Audrius Kryžanauskas
Keyword(s):  
Decision Making ◽  
Sustainable Development ◽  
Spatial Data ◽  
Information Science ◽  
Temporal Distribution ◽  
Geographic Information ◽  
Information Communication ◽  
Good Decision ◽  
Geographic Space ◽  
Spatio Temporal

Information communication technologies are widely used to support sustainable development. As both nature and society exist and develop in the geographic space, a good decision making can hardly be imagined without a prior thorough analysis of spatio‐temporal distribution and spatial correlation of diverse ecological, economical and social parameters. Wherever such geospatial relationships are concerned, the methods of geography as of a geographic information science are commonly applied, among which cartography is the most efficient information communication method. Different levels of representation of geographic information, such as databases, geographic information systems (GIS), maps, atlases and Spatial Data Infrastructures can be easily and conveniently used for different steps of planning. More than that, maps have a hidden potential to reveal unknown spatial patterns and trends and the process does not require any specific technological skills from the user. Therefore it is very important to include geographic/cartographic dimension into regional and national sustainable development strategies, so that spatial structures, diversities, similarities and geographic determination are always taken into account. To facilitate the process of geographic decision making, we develop a uniform model of description of geographic methods that could be used online and provide suggestions on which of the known methods could be efficiently applied. Santrauka Tvarioji plėtra nebūtų įmanoma be informacijos komunikavimo priemonių ir technologijų. Ir gamta, ir visuomenė egzistuoja ir vystosi erdvėje, tad neįmanoma įsivaizduoti tinkamu planavimo sprendimų, kurie nebūtų pagristi išankstine išsamia dalykinės srities erdvės ir laiko ryšių analize, neįvertintų erdvinių sąsajų tarp ekologinių, ekonominių ir socialinių parametrų. Visur, kur svarbus objektų išsidėstymas ir jų tarpusavio ryšiai geografinėje erdvėje ir laike, yra taikomi geografinės informacijos mokslo (šiuolaikines geografijos) metodai. Vienas efektyviausių yra kartografinis metodas, leidžiantis intuityviai pastebėti erdvinius ryšius. Galima nagrinėti skirtingus geografines informacijos organizavimo lygmenis, tokius kaip duomenų bazes, geografines informacijos (GIS) sistemos, žemėlapiai, atlasai bei erdvinių duomenų infrastruktūros. Visas šias sistemas galima patogiai ir nesunkiai naudoti įvairiuose planavimo etapuose. Be to, žemėlapiai turi paslėpta potencialą atskleisti iš anksto nežinomus erdvinius ryšius bei tendencijas. Šis procesas yra intuityvus ir nereikalauja iš naudotojo jokiu specialių technologijų žinių ar įgūdžiu. Todėl labai svarbu į nacionalines ir regionines plėtros strategijas įtraukti ir geografini/kartografini matmenį, atsižvelgti į erdvinio išsidėstymo struktūras, skirtumus, panašumas ir galimus geografinius apribojimus. Straipsnio autoriai pasiūlė ir šiuo metu Vilniaus universitete plėtoja universalų geografinių uždavinių aprašymu modelį, kuris padėtu geografines informacijos naudotojams be specialiu žinių pasirinkti tinkama sprendimų seką ir metodus.

scholarly journals Geosmartness for Personalized and Sustainable Future Urban Mobility

2021 ◽  
pp. 59-83
Author(s):  
Martin Raubal ◽  
Dominik Bucher ◽  
Henry Martin
Keyword(s):  
Decision Making ◽  
Spatial Data ◽  
Information Technologies ◽  
Large Scale ◽  
Smart Cities ◽  
Mobile Technologies ◽  
Urban Mobility ◽  
Mobility Patterns ◽  
Movement Data ◽  
Spatio Temporal

AbstractUrban mobility and the transport of people have been increasing in volume inexorably for decades. Despite the advantages and opportunities mobility has brought to our society, there are also severe drawbacks such as the transport sector’s role as one of the main contributors to greenhouse-gas emissions and traffic jams. In the future, an increasing number of people will be living in large urban settings, and therefore, these problems must be solved to assure livable environments. The rapid progress of information and communication, and geographic information technologies, has paved the way for urban informatics and smart cities, which allow for large-scale urban analytics as well as supporting people in their complex mobile decision making. This chapter demonstrates how geosmartness, a combination of novel spatial-data sources, computational methods, and geospatial technologies, provides opportunities for scientists to perform large-scale spatio-temporal analyses of mobility patterns as well as to investigate people’s mobile decision making. Mobility-pattern analysis is necessary for evaluating real-time situations and for making predictions regarding future states. These analyses can also help detect behavioral changes, such as the impact of people’s travel habits or novel travel options, possibly leading to more sustainable forms of transport. Mobile technologies provide novel ways of user support. Examples cover movement-data analysis within the context of multi-modal and energy-efficient mobility, as well as mobile decision-making support through gaze-based interaction.

scholarly journals Event Detection and Spatio-temporal Analysis of Low-Altitude Unstable Approach

2020 ◽  
Vol 10 (14) ◽  
pp. 4934
Author(s):  
Huabo Sun ◽  
Jiayi Xie ◽  
Yang Jiao ◽  
Rongshun Huang ◽  
Binbin Lu
Keyword(s):  
Spatial Distribution ◽  
Correlation Coefficient ◽  
Spatial Data ◽  
Mainland China ◽  
Temporal Analysis ◽  
Spatial Data Analysis ◽  
Technical Program ◽  
Low Altitude ◽  
Spatio Temporal ◽  
Bad Weather

Low-altitude unstable approach (UA) is one of the crucial risks that threaten flight safety. In this study, we proposed a technical program for detecting low-altitude UA events. The detection logic was to optimize the step-wise regression model with iterative surveys with more than 20 experienced pilots. Accordingly, the frequencies of UA events occurring around each airport in January 2018 were calculated for all the airports within mainland China. Finally, the spatial distribution characteristics of UA events were analyzed via exploratory spatial data analysis. In addition, Pearson’s correlation coefficient and the geographically weighted correlation coefficient were used to explore the correlations between UA frequency and the altitude elevation, wind level, and bad weather. The experimental results revealed that the proposed method can accurately detect the occurrence of low-altitude UA and quantitatively characterize risks. It was found that UA exhibits obvious differences in spatial distribution. Moreover, significantly strong correlations were found between UA and altitude elevation, wind level, and bad weather, and correlation differences were also reflected in different regions in China.

Application of PCA with georeferenced data in the tourism industry: A case study in the province of Córdoba, Argentina

2021 ◽  
pp. 135481662098768
Author(s):  
Laura I Luna
Keyword(s):  
Decision Making ◽  
Principal Components ◽  
Spatial Data ◽  
Local Development ◽  
Value Added ◽  
Tourism Industry ◽  
Methodological Innovation ◽  
Spatial Principal Components ◽  
Components Analysis

The spatial analysis of tourism industries provides information about their structure, which is necessary for decision-making. In this work, tourism industries in the departments of Córdoba province, Argentina, for the 2001–2014 period were mapped. Multivariate methods with and without spatial restrictions (spatial principal components (sPCs) analysis, MULTISPATI-PCA, and principal components analysis (PCA), respectively) were applied and their performance was compared. MULTISPATI-PCA yielded a higher degree of spatial structuring of the components that summarize tourism activities than PCA. The methodological innovation lies in the generation of statistics for multidimensional spatial data. The departments were classified according to the participation of tourism activities in the value added of tourism using the sPCs obtained as input of the cluster fuzzy k-means analysis. This information provides elements necessary for appropriately defining local development strategies and, therefore, is useful to improve decision-making.

scholarly journals Spatio-temporal distribution patterns of Plutella xylostella (Lepidoptera: Plutellidae) in a fine-scale agricultural landscape based on geostatistical analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jian-Yu Li ◽  
Yan-Ting Chen ◽  
Meng-Zhu Shi ◽  
Jian-Wei Li ◽  
Rui-Bin Xu ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Plutella Xylostella ◽  
Agricultural Landscape ◽  
Seasonal Pattern ◽  
Distribution Patterns ◽  
Geostatistical Analysis ◽  
Distribution Model ◽  
Detailed Knowledge ◽  
Fine Scale ◽  
Spatio Temporal

AbstractA detailed knowledge on the spatial distribution of pests is crucial for predicting population outbreaks or developing control strategies and sustainable management plans. The diamondback moth, Plutella xylostella, is one of the most destructive pests of cruciferous crops worldwide. Despite the abundant research on the species’s ecology, little is known about the spatio-temporal pattern of P. xylostella in an agricultural landscape. Therefore, in this study, the spatial distribution of P. xylostella was characterized to assess the effect of landscape elements in a fine-scale agricultural landscape by geostatistical analysis. The P. xylostella adults captured by pheromone-baited traps showed a seasonal pattern of population fluctuation from October 2015 to September 2017, with a marked peak in spring, suggesting that mild temperatures, 15–25 °C, are favorable for P. xylostella. Geostatistics (GS) correlograms fitted with spherical and Gaussian models showed an aggregated distribution in 21 of the 47 cases interpolation contour maps. This result highlighted that spatial distribution of P. xylostella was not limited to the Brassica vegetable field, but presence was the highest there. Nevertheless, population aggregations also showed a seasonal variation associated with the growing stage of host plants. GS model analysis showed higher abundances in cruciferous fields than in any other patches of the landscape, indicating a strong host plant dependency. We demonstrate that Brassica vegetables distribution and growth stage, have dominant impacts on the spatial distribution of P. xylostella in a fine-scale landscape. This work clarified the spatio-temporal dynamic and distribution patterns of P. xylostella in an agricultural landscape, and the distribution model developed by geostatistical analysis can provide a scientific basis for precise targeting and localized control of P. xylostella.

scholarly journals The INUS Platform: A Modular Solution for Object Detection and Tracking from UAVs and Terrestrial Surveillance Assets

Computation ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 12
Author(s):  
Evangelos Maltezos ◽  
Athanasios Douklias ◽  
Aris Dadoukis ◽  
Fay Misichroni ◽  
Lazaros Karagiannidis ◽  
...  
Keyword(s):  
Decision Making ◽  
Object Detection ◽  
Situational Awareness ◽  
Machine Learning Techniques ◽  
Measurement Instruments ◽  
Time Data ◽  
Modular Architecture ◽  
Seamless Integration ◽  
Object Detection And Tracking ◽  
Detection And Tracking

Situational awareness is a critical aspect of the decision-making process in emergency response and civil protection and requires the availability of up-to-date information on the current situation. In this context, the related research should not only encompass developing innovative single solutions for (real-time) data collection, but also on the aspect of transforming data into information so that the latter can be considered as a basis for action and decision making. Unmanned systems (UxV) as data acquisition platforms and autonomous or semi-autonomous measurement instruments have become attractive for many applications in emergency operations. This paper proposes a multipurpose situational awareness platform by exploiting advanced on-board processing capabilities and efficient computer vision, image processing, and machine learning techniques. The main pillars of the proposed platform are: (1) a modular architecture that exploits unmanned aerial vehicle (UAV) and terrestrial assets; (2) deployment of on-board data capturing and processing; (3) provision of geolocalized object detection and tracking events; and (4) a user-friendly operational interface for standalone deployment and seamless integration with external systems. Experimental results are provided using RGB and thermal video datasets and applying novel object detection and tracking algorithms. The results show the utility and the potential of the proposed platform, and future directions for extension and optimization are presented.

Attention Allocation to Physically Separate Task and Situation Displays in a Command and Control Setting

2020 ◽  
Vol 64 (1) ◽  
pp. 1130-1134
Author(s):  
H. Golan ◽  
A. Parush ◽  
E. Jaffe
Keyword(s):  
Decision Making ◽  
Emergency Medical Services ◽  
Situational Awareness ◽  
Command And Control ◽  
Attention Allocation ◽  
Incident Management ◽  
Allocation Strategy ◽  
Individual Task ◽  
Improved Performance ◽  
And Control

Using a simulated Emergency Medical Services (EMS) dispatch center during multi-casualty incident management, this study explored whether the presence of a separate situation display in a Command and Control (C2) setting might require attention at the expense of attending an individual task display, and how it influenced performance and situational awareness. Overall, participants always attended the task display more than the situation display. However, the situation display drew attention at the expense of attending less the task display. The presence of the situation display was related to improved performance and better situational awareness (SA), particularly in the projection level of the SA, which could account also for the better decision-making performance. Participants may have developed an attention allocation strategy to effectively utilize the information of the situation display and execute their tasks on the task display.

Sign in / Sign up

Export Citation Format

Share Document