scholarly journals Toward Measuring the Level of Spatiotemporal Clustering of Multi-Categorical Geographic Events

2020 ◽  
Vol 9 (7) ◽  
pp. 440
Author(s):  
Junfang Gong ◽  
Jay Lee ◽  
Shunping Zhou ◽  
Shengwen Li
Keyword(s):  
Human Activity ◽  
Simulated Data ◽  
Spatiotemporal Pattern ◽  
Time Period ◽  
Spatiotemporal Clustering ◽  
Categorical Attributes ◽  
Treat All ◽  
Clustering Patterns ◽  
2D To 3D

Human activity events are often recorded with their geographic locations and temporal stamps, which form spatial patterns of the events during individual time periods. Temporal attributes of these events help us understand the evolution of spatial processes over time. A challenge that researchers still face is that existing methods tend to treat all events as the same when evaluating the spatiotemporal pattern of events that have different properties. This article suggests a method for assessing the level of spatiotemporal clustering or spatiotemporal autocorrelation that may exist in a set of human activity events when they are associated with different categorical attributes. This method extends the Voronoi structure from 2D to 3D and integrates a sliding-window model as an approach to spatiotemporal tessellations of a space-time volume defined by a study area and time period. Furthermore, an index was developed to evaluate the partial spatiotemporal clustering level of one of the two event categories against the other category. The proposed method was applied to simulated data and a real-world dataset as a case study. Experimental results show that the method effectively measures the level of spatiotemporal clustering patterns among human activity events of multiple categories. The method can be applied to the analysis of large volumes of human activity events because of its computational efficiency.

scholarly journals Visualizing Spatiotemporal Epidemic Clusters on a Map-based Dashboard: A case study of early COVID-19 cases in Singapore

2021 ◽  
Vol 4 ◽  
pp. 1-5
Author(s):  
Hui Zhang ◽  
Chenyu Zuo ◽  
Linfang Ding
Keyword(s):  
Infectious Diseases ◽  
Spatiotemporal Distribution ◽  
Ministry Of Health ◽  
Test Dataset ◽  
Spatiotemporal Characteristics ◽  
Spatiotemporal Clustering ◽  
Interactive Map ◽  
Clustering Patterns

Abstract. Spatiotemporal distribution of the epidemic data plays an important role in its understanding and prediction. In order to understand the transmission patterns of infectious diseases in a more intuitive way, many works applied various visualizations to show the epidemic datasets. However, most of them focus on visualizing the epidemic information at the overall level such as the confirmed counts each country, while spending less effort on powering user to effectively understand and reason the very large and complex epidemic datasets through flexible interactions. In this paper, the authors proposed a novel map-based dashboard for visualizing and analyzing spatiotemporal clustering patterns and transmission chains of epidemic data. We used 102 confirmed cases officially reported by the Ministry of Health in Singapore as the test dataset. This experiment shown that the well-designed and interactive map-based dashboard is effective in shorten the time that users required to mine the spatiotemporal characteristics and transmission chains behind the textual and numerical epidemic data.

Depth-based Human Activity Recognition: vINCI Case Study

2020 ◽  
Author(s):  
Lidia Bajenaru ◽  
Ciprian Dobre ◽  
Radu-Ioan Ciobanu ◽  
Georgiana Dedu ◽  
Silviu-George Pantelimon ◽  
...  
Keyword(s):  
Activity Recognition ◽  
Human Activity ◽  
Human Activity Recognition

scholarly journals The reasons women choose and stay in a geology major: a qualitative multi-case analysis

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Ron E. Gray ◽  
Alexis T. Riche ◽  
Isabel J. Shinnick-Gordon ◽  
James C. Sample
Keyword(s):  
Role Models ◽  
Critical Incident ◽  
Earth Science ◽  
Time Period ◽  
The Usa ◽  
Data Source ◽  
Introductory Classes ◽  
Iterative Coding ◽  
As Relationship

AbstractDespite earning half of all science and engineering undergraduate degrees between 2007 and 2016 in the USA, women were awarded only 39% of earth science degrees in the same time period. In order to better understand why women are both choosing and staying in geology programs, we conducted a multi-case study of nine current female undergraduate geology majors at a large public university in the USA within a department that is at gender parity among its undergraduate majors. The main data source was audio-recorded critical incident interviews of each participant. Data from the interviews were analyzed through an iterative coding process using codes adapted from previous studies that focused on factors both internal and external to the department. The students said that personal interests, influence by others outside of the department, and introductory classes attracted them to the geology program, but once declared, departmental factors such as relationship with faculty caused them to stay. We also found an emphasis on female role models, especially those teaching introductory courses. We believe this study offers important insights into the ways in which factors leading to recruitment and retention play out in the lived experiences of female geology majors.

scholarly journals Constructing Damage Indices Based on Publicly Available Spatial Data: Exemplified by Earthquakes and Volcanic Eruptions in Indonesia

2021 ◽  
Author(s):  
Emmanuel Skoufias ◽  
Eric Strobl ◽  
Thomas Tveit
Keyword(s):  
Spatial Data ◽  
Volcanic Ash ◽  
Satellite Images ◽  
Fragility Curves ◽  
Volcanic Eruptions ◽  
Damage Indices ◽  
Damage Indicator ◽  
Time Period ◽  
Peak Ground Motion

AbstractThis article demonstrates the construction of earthquake and volcano damage indices using publicly available remote sensing sources and data on the physical characteristics of events. For earthquakes we use peak ground motion maps in conjunction with building type fragility curves to construct a local damage indicator. For volcanoes we employ volcanic ash data as a proxy for local damages. Both indices are then spatially aggregated by taking local economic exposure into account by assessing nightlight intensity derived from satellite images. We demonstrate the use of these indices with a case study of Indonesia, a country frequently exposed to earthquakes and volcanic eruptions. The results show that the indices capture the areas with the highest damage, and we provide overviews of the modeled aggregated damage for all provinces and districts in Indonesia for the time period 2004 to 2014. The indices were constructed using a combination of software programs—ArcGIS/Python, Matlab, and Stata. We also outline what potential freeware alternatives exist. Finally, for each index we highlight the assumptions and limitations that a potential practitioner needs to be aware of.

Hydrological changes in the Rzecin peatland (Puszcza Notecka, Poland) induced by anthropogenic factors: Implications for mire development and carbon sequestration

The Holocene ◽  
2016 ◽  
Vol 27 (5) ◽  
pp. 651-664 ◽  
Author(s):  
Krystyna Milecka ◽  
Grzegorz Kowalewski ◽  
Barbara Fiałkiewicz-Kozieł ◽  
Mariusz Gałka ◽  
Mariusz Lamentowicz ◽  
...  
Keyword(s):  
Carbon Sequestration ◽  
Plant Communities ◽  
Human Activity ◽  
Accumulation Rate ◽  
Carbon Accumulation ◽  
Anthropogenic Factors ◽  
Poor Fen ◽  
History Of ◽  
Carbon Accumulation Rates

Wetlands are very vulnerable ecosystems and sensitive to changes in the ground water table. For the last few thousand years, hydrological balance has also been influenced by human activity. To improve their cropping features, drainage activity and fertilizing were applied. The drainage process led to an abrupt change of environment, the replacement of plant communities and the entire ecosystem. The problem of carbon sequestration is very important nowadays. A higher accumulation rate is related to higher carbon accumulation, but the intensity of carbon sequestration depends on the type of mire, habitat, and climatic zone. The main aim of this article was an examination of the changes in poor-fen ecosystem during the last 200 years in relation to natural and anthropogenic factors, using paleoecological methods (pollen and macrofossils). The second aim was a detailed investigation of the sedimentary record to aid our understanding of carbon sequestration in the poor fen of temperate zone. This case study shows that fens in temperate zones, in comparison with boreal ones, show higher carbon accumulation rates which have been especially intensive over the last few decades. To reconstruct vegetation changes, detailed palynological and macrofossil analyses were done. A 200-year history of the mire revealed that it was influenced by human activity to much degree. However, despite the nearby settlement and building of the drainage ditch, the precious species and plant communities still occur.

Improving Operational Efficiency Using Automated Time Analysis for Multi-Well Pad Fracturing

2021 ◽  
Author(s):  
Fahd Siddiqui ◽  
Mohammadreza Kamyab ◽  
Michael Lowder
Keyword(s):  
Real Time ◽  
Operational Efficiency ◽  
Permian Basin ◽  
Potential Cost ◽  
Time Period ◽  
Cloud Server ◽  
The Us ◽  
Single Well ◽  
Complete Automation

Abstract The economic success of unconventional reservoirs relies on driving down completion costs. Manually measuring the operational efficiency for a multi-well pad can be error-prone and time-prohibitive. Complete automation of this analysis can provide an effortless real-time insight to completion engineers. This study presents a real-time method for measuring the time spent on each completion activity, thereby enabling the identification and potential cost reduction avenues. Two data acquisition boxes are utilized at the completion site to transmit both the fracturing and wireline data in real-time to a cloud server. A data processing algorithm is described to determine the start and end of these two operations for each stage of every well on the pad. The described method then determines other activity intervals (fracturing swap-over, wireline swap-over, and waiting on offset wells) based on the relationship between the fracturing and wireline segments of all the wells. The processed data results can be viewed in real-time on mobile or computers connected to the cloud. Viewing the full operational time log in real-time helps engineers analyze the whole operation and determine key performance indicators (KPIs) such as the number of fractured stages per day, pumping percentage, average fracture, and wireline swap-over durations for a given time period. In addition, the performance of the day and night crews can be evaluated. By plotting a comparison of KPIs for wireline and fracturing times, trends can be readily identified for improving operational efficiency. Practices from best-performing stages can be adopted to reduce non-pumping times. This helps operators save time and money to optimize for more efficient operations. As the number of wells increases, the complexity of manual generation of time-log increases. The presented method can handle multi-well fracturing and wireline operations without such difficulty and in real-time. A case study is also presented, where an operator in the US Permian basin used this method in real-time to view and optimize zipper operations. Analysis indicated that the time spent on the swap over activities could be reduced. This operator set a realistic goal of reducing 10 minutes per swap-over interval. Within one pad, the goal was reached utilizing this method, resulting in reducing 15 hours from the total pad time. The presented method provides an automated overview of fracturing operations. Based on the analysis, timely decisions can be made to reduce operational costs. Moreover, because this method is automated, it is not limited to single well operations but can handle multi-well pad completion designs that are commonplace in unconventionals.

scholarly journals Evaluation of Integrated Assessment Model hindcast experiments: A case study of the GCAM 3.0 land use module

2017 ◽  
Author(s):  
Abigail C. Snyder ◽  
Robert P. Link ◽  
Katherine V. Calvin
Keyword(s):  
Integrated Assessment ◽  
Structural Changes ◽  
Spatial Scales ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Land Allocation ◽  
Time Period ◽  
Skill Scores ◽  
Performance Benchmarks

Abstract. Hindcasting experiments (conducting a model forecast for a time period in which observational data is available) are rarely undertaken in the Integrated Assessment Model (IAM) community. When they are undertaken, the results are often evaluated using global aggregates or otherwise highly aggregated skill scores that mask deficiencies. We select a set of deviation based measures that can be applied at different spatial scales (regional versus global) to make evaluating the large number of variable-region combinations in IAMs more tractable. We also identify performance benchmarks for these measures, based on the statistics of the observational dataset, that allow a model to be evaluated in absolute terms rather than relative to the performance of other models at similar tasks. This is key in the integrated assessment community, where there often are not multiple models conducting hindcast experiments to allow for model intercomparison. The performance benchmarks serve a second purpose, providing information about the reasons a model may perform poorly on a given measure and therefore identifying opportunities for improvement. As a case study, the measures are applied to the results of a past hindcast experiment focusing on land allocation in the Global Change Assessment Model (GCAM) version 3.0. We find quantitative evidence that global aggregates alone are not sufficient for evaluating IAMs, such as GCAM, that require global supply to equal global demand at each time period. Additionally, the deviation measures examined in this work successfully identity parametric and structural changes that may improve land allocation decisions in GCAM. Future work will involve implementing the suggested improvements to the GCAM land allocation system identified by the measures in this work, using the measures to quantify performance improvement due to these changes, and, ideally, applying these measures to other sectors of GCAM and other land allocation models.

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