scholarly journals Towards an Improved Large-Scale Gridded Population Dataset: A Pan-European Study on the Integration of 3D Settlement Data into Population Modelling

2022 ◽  
Vol 14 (2) ◽  
pp. 325
Author(s):  
Daniela Palacios-Lopez ◽  
Thomas Esch ◽  
Kytt MacManus ◽  
Mattia Marconcini ◽  
Alessandro Sorichetta ◽  
...  
Keyword(s):  
Large Scale ◽  
Classification Method ◽  
Future Research ◽  
Population Modelling ◽  
High Rise ◽  
Continental Scale ◽  
Misclassification Errors ◽  
Scale Population ◽  
Building Footprint ◽  
First Time

Large-scale gridded population datasets available at the global or continental scale have become an important source of information in applications related to sustainable development. In recent years, the emergence of new population models has leveraged the inclusion of more accurate and spatially detailed proxy layers describing the built-up environment (e.g., built-area and building footprint datasets), enhancing the quality, accuracy and spatial resolution of existing products. However, due to the consistent lack of vertical and functional information on the built-up environment, large-scale gridded population datasets that rely on existing built-up land proxies still report large errors of under- and overestimation, especially in areas with predominantly high-rise buildings or industrial/commercial areas, respectively. This research investigates, for the first time, the potential contributions of the new World Settlement Footprint—3D (WSF3D) dataset in the field of large-scale population modelling. First, we combined a Random Forest classifier with spatial metrics derived from the WSF3D to predict the industrial versus non-industrial use of settlement pixels at the Pan-European scale. We then examined the effects of including volume and settlement use information into frameworks of dasymetric population modelling. We found that the proposed classification method can predict industrial and non-industrial areas with overall accuracies and a kappa-coefficient of ~84% and 0.68, respectively. Additionally, we found that both, integrating volume and settlement use information considerably increased the accuracy of population estimates between 10% and 30% over commonly employed models (e.g., based on a binary settlement mask as input), mainly by eliminating systematic large overestimations in industrial/commercial areas. While the proposed method shows strong promise for overcoming some of the main limitations in large-scale population modelling, future research should focus on improving the quality of the WFS3D dataset and the classification method alike, to avoid the false detection of built-up settlements and to reduce misclassification errors of industrial and high-rise buildings.

scholarly journals Negative emissions and international climate goals—learning from and about mitigation scenarios

2019 ◽  
Vol 157 (2) ◽  
pp. 189-219 ◽  
Author(s):  
Jérôme Hilaire ◽  
Jan C. Minx ◽  
Max W. Callaghan ◽  
Jae Edmonds ◽  
Gunnar Luderer ◽  
...  
Keyword(s):  
Large Scale ◽  
Scale Up ◽  
Paris Agreement ◽  
Future Research ◽  
Climate Feedbacks ◽  
Systematic Assessment ◽  
Net Uptake ◽  
Development Goals ◽  
Near Term ◽  
First Time

Abstract For aiming to keep global warming well-below 2 °C and pursue efforts to limit it to 1.5 °C, as set out in the Paris Agreement, a full-fledged assessment of negative emission technologies (NETs) that remove carbon dioxide from the atmosphere is crucial to inform science-based policy making. With the Paris Agreement in mind, we re-analyse available scenario evidence to understand the roles of NETs in 1.5 °C and 2 °C scenarios and, for the first time, link this to a systematic review of findings in the underlying literature. In line with previous research, we find that keeping warming below 1.5 °C requires a rapid large-scale deployment of NETs, while for 2 °C, we can still limit NET deployment substantially by ratcheting up near-term mitigation ambition. Most recent evidence stresses the importance of future socio-economic conditions in determining the flexibility of NET deployment and suggests opportunities for hedging technology risks by adopting portfolios of NETs. Importantly, our thematic review highlights that there is a much richer set of findings on NETs than commonly reflected upon both in scientific assessments and available reviews. In particular, beyond the common findings on NETs underpinned by dozens of studies around early scale-up, the changing shape of net emission pathways or greater flexibility in the timing of climate policies, there is a suite of “niche and emerging findings”, e.g. around innovation needs and rapid technological change, termination of NETs at the end of the twenty-first century or the impacts of climate change on the effectiveness of NETs that have not been widely appreciated. Future research needs to explore the role of climate damages on NET uptake, better understand the geophysical constraints of NET deployment (e.g. water, geological storage, climate feedbacks), and provide a more systematic assessment of NET portfolios in the context of sustainable development goals.

Application of GIS in Rainwater Harvesting Research: A Scoping Review

2021 ◽  
Vol 18 (4) ◽  
pp. 29-35
Author(s):  
Preeti Preeti ◽  
Ataur Rahman
Keyword(s):  
Spatial Data ◽  
Large Scale ◽  
Rainwater Harvesting ◽  
Model Development ◽  
Future Research ◽  
Spatial And Temporal Variability ◽  
Full Potential ◽  
Quality Of Water ◽  
Building Footprint ◽  
Development Goals

The spatial and temporal variability of quantity and quality of water are important aspects of water resources management. Water demand has been increasing across the globe, but the fresh water supply is limited. Rainwater harvesting (RWH) systems are increasingly being embraced as an alternative freshwater source. This study reviews the dynamics of global research on RWH that utilises geographic information systems (GIS). It is found that the interest and use of RWH utilising GIS have increased over the recent years. However, the full potential of GIS in large scale RWH is yet to be untapped. We make recommendations for future research on RWH based on GIS. This includes new software and model development that links RWH with GIS to plan and design large scale RWH and automated building footprint extraction for estimating RWH potential. GIS can play a bigger role in achieving Sustainable Development Goals (SDGs) by incorporating GIS with RWH since GIS can handle large spatial data efficiently, which can help in locating areas that are suitable for rainwater harvesting.

A large-scale population-based epidemiological study on the prevalence of central sensitization syndromes in Japan

2021 ◽  
Author(s):  
Yasuo Haruyama ◽  
Toshimi Sairenchi ◽  
Koji Uchiyama ◽  
Keisuke Suzuki ◽  
Koichi Hirata ◽  
...  
Keyword(s):  
Central Sensitization ◽  
Large Scale ◽  
Population Based ◽  
Cross Sectional Study ◽  
Future Research ◽  
Coffee Intake ◽  
Cross Sectional ◽  
Logistic Regression Models ◽  
Scale Population ◽  
Potential Factors

Abstract To investigate the prevalence of CSS in a general population. A large-scale cross-sectional study on 21,661 residents (7,531 men, 14,130 women) in a community in Japan was performed. CSS were assessed using Central Sensitization Inventory (CSI-A, B). Participants with a CSI-A score ≥40 was defined as having CSS. Age, sex, district, CSI-B (10 CSS-related diseases), lifestyle, and mental health factors were rated in a self-reported survey. The prevalence of CSS and its relationship with potential factors were examined by sex using descriptive and logistic regression models. The prevalence of CSS was 5.4% (95% Confidence Interval (CI) 5.1 to 5.7) in all participants. It significantly differed between men (3.6%, 95% CI 3.2 to 4.1) and women (6.3%, 95% CI 5.6 to 6.7). A CSI-A score ≥40 correlated with more than one CSI-B disease, exercise habits, sleeping hours per day, perceived stress, and resilience in both men and women. In women, age, ex-smokers, coffee intake (≥1 day per week), and alcohol intake correlated with CSS. The prevalence of CSS was 5.4% in the community examined and was higher in women than in men. CSS-related diseases and many factors correlated with CSS. The present results provide important information for future research on CSS.

Widespread underestimation of the danger of groundwater contamination by shortcuts into aquifers

2020 ◽  
Author(s):  
Andreas Hartmann ◽  
The karst vulnerablity research consortium
Keyword(s):  
Water Quality ◽  
Groundwater Contamination ◽  
Large Scale ◽  
Scale Model ◽  
World Population ◽  
Continental Scale ◽  
Scale Modelling ◽  
Agricultural Pollutants ◽  
First Time

<p>Groundwater pollution threatens human and ecosystem health in many areas around the globe. Shortcuts to the groundwater through enlarged cracks and fissures, often referred to as concentrated recharge, are known to transmit short-lived pollutants into carbonate aquifers endangering water quality of around a quarter of the world population. However, the large-scale impact of concentrated recharge on water quality remains poorly understood. Here we apply a continental-scale model to quantify for the first time the danger of groundwater contamination by degradable pollutants through concentrated recharge in carbonate rock regions. We show that concentrated recharge is the primary reason for the rapid transport of contaminants to the groundwater, increasing the percentage of non-degraded pollutants from <1% in areas without concentrated recharge to around 20-50% in areas where concentrated recharge is present. Our findings are most pronounced in the Mediterranean region where agricultural pollutants in groundwater recharge like Glyphosate can exceed allowed concentrations by up to 19 times. Our results imply that in regions where shortcuts to the groundwater exist, continuing industrial agricultural productivity to optimize food production may result in a widespread reduction of available drinking water and harm ecosystem services more intense than presently available large-scale modelling concepts suggest.</p>

scholarly journals Epidemiology of community-acquired and recurrent Clostridioides difficile infection

2021 ◽  
Vol 14 ◽  
pp. 175628482110162
Author(s):  
Yichun Fu ◽  
Yuying Luo ◽  
Ari M Grinspan
Keyword(s):  
Large Scale ◽  
Infection Prevention ◽  
The United States ◽  
Future Research ◽  
Clostridioides Difficile ◽  
Epidemiologic Surveillance ◽  
Scale Population ◽  
Clostridioides Difficile Infection ◽  
Healthcare Associated ◽  
Hospital Acquired

Clostridioides difficile infection is a leading cause of healthcare-associated infections with significant morbidity and mortality. For the past decade, the bulk of infection prevention and epidemiologic surveillance efforts have been directed toward mitigating hospital-acquired C. difficile. However, the incidence of community-associated infection is on the rise. Patients with community-associated C. difficile tend to be younger and have lower mortality rate. Rates of recurrent C. difficile infection overall have decreased in the United States, but future research and public health endeavors are needed to standardize and improve disease detection, stratify risk factors in large-scale population studies, and to identify regional and local variations in strain types, reservoirs and transmission routes to help characterize and combat the changing epidemiology of C. difficile.

scholarly journals Population analysis of retrotransposons in giraffe genomes supports RTE decline and widespread LINE1 activity in Giraffidae

Mobile DNA ◽  
2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Malte Petersen ◽  
Sven Winter ◽  
Raphael Coimbra ◽  
Menno J. de Jong ◽  
Vladimir V. Kapitonov ◽  
...  
Keyword(s):  
Large Scale ◽  
Population Analysis ◽  
Model Organism ◽  
Population Level ◽  
Data Sets ◽  
Ltr Retrotransposons ◽  
Scale Population ◽  
Mammalian Genomes ◽  
Genome Assemblies ◽  
First Time

Abstract Background The majority of structural variation in genomes is caused by insertions of transposable elements (TEs). In mammalian genomes, the main TE fraction is made up of autonomous and non-autonomous non-LTR retrotransposons commonly known as LINEs and SINEs (Long and Short Interspersed Nuclear Elements). Here we present one of the first population-level analysis of TE insertions in a non-model organism, the giraffe. Giraffes are ruminant artiodactyls, one of the few mammalian groups with genomes that are colonized by putatively active LINEs of two different clades of non-LTR retrotransposons, namely the LINE1 and RTE/BovB LINEs as well as their associated SINEs. We analyzed TE insertions of both types, and their associated SINEs in three giraffe genome assemblies, as well as across a population level sampling of 48 individuals covering all extant giraffe species. Results The comparative genome screen identified 139,525 recent LINE1 and RTE insertions in the sampled giraffe population. The analysis revealed a drastically reduced RTE activity in giraffes, whereas LINE1 is still actively propagating in the genomes of extant (sub)-species. In concert with the extremely low activity of the giraffe RTE, we also found that RTE-dependent SINEs, namely Bov-tA and Bov-A2, have been virtually immobile in the last 2 million years. Despite the high current activity of the giraffe LINE1, we did not find evidence for the presence of currently active LINE1-dependent SINEs. TE insertion heterozygosity rates differ among the different (sub)-species, likely due to divergent population histories. Conclusions The horizontally transferred RTE/BovB and its derived SINEs appear to be close to inactivation and subsequent extinction in the genomes of extant giraffe species. This is the first time that the decline of a TE family has been meticulously analyzed from a population genetics perspective. Our study shows how detailed information about past and present TE activity can be obtained by analyzing large-scale population-level genomic data sets.

Change of Attitude, Technology and Practice: Identifying the Change for Increased Value Creation with Customer Co-creation

2017 ◽  
Vol 5 (1) ◽  
pp. 70-82
Author(s):  
Soumi Paul ◽  
Paola Peretti ◽  
Saroj Kumar Datta
Keyword(s):  
Social Media ◽  
New Product Development ◽  
Value Creation ◽  
Large Scale ◽  
Customer Orientation ◽  
Customer Relationships ◽  
Future Research ◽  
Management Competencies ◽  
Business Decisions ◽  
Prime Concern

Building customer relationships and customer equity is the prime concern in today’s business decisions. The emergence of internet, especially social media like Facebook and Twitter, changed traditional marketing thought to a great extent. The importance of customer orientation is reflected in the axiom, “The customer is the king”. A good number of organizations are engaging customers in their new product development activities via social media platforms. Co-creation, a new perspective in which customers are active co-creators of the products they buy and use, is currently challenging the traditional paradigm. The concept of co-creation involving the customer’s knowledge, creativity and judgment to generate value is considered not only an upcoming trend that introduces new products or services but also fitting their need and increasing value for money. Knowledge and innovation are inseparable. Knowledge management competencies and capacities are essential to any organization that aspires to be distinguished and innovative. The present work is an attempt to identify the change in value creation procedure along with one area of business, where co-creation can return significant dividends. It is on extending the brand or brand category through brand extension or line extension. This article, through an in depth literature review analysis, identifies the changes in every perspective of this paradigm shift and it presents a conceptual model of company-customer-brand-based co-creation activity via social media. The main objective is offering an agenda for future research of this emerging trend and ensuring the way to move from theory to practice. The paper acts as a proposal; it allows the organization to go for this change in a large scale and obtain early feedback on the idea presented. 

Scheming

2018 ◽  
Author(s):  
Seán Damer
Keyword(s):  
Social Class ◽  
Housing Policy ◽  
Large Scale ◽  
Class Structure ◽  
Local Council ◽  
Housing Scheme ◽  
Post War ◽  
First Time ◽  
The Voice ◽  
House Building

This book seeks to explain how the Corporation of Glasgow, in its large-scale council house-building programme in the inter- and post-war years, came to reproduce a hierarchical Victorian class structure. The three tiers of housing scheme which it constructed – Ordinary, Intermediate, and Slum-Clearance – effectively signified First, Second and Third Class. This came about because the Corporation uncritically reproduced the offensive and patriarchal attitudes of the Victorian bourgeoisie towards the working-class. The book shows how this worked out on the ground in Glasgow, and describes the attitudes of both authoritarian housing officials, and council tenants. This is the first time the voice of Glasgow’s council tenants has been heard. The conclusion is that local council housing policy was driven by unapologetic considerations of social class.

Overview of Subsynchronous Oscillation in Grid-connected Wind Farm

2020 ◽  
Vol 13 (7) ◽  
pp. 969-979
Author(s):  
Xu Pei-Zhen ◽  
Lu Yong-Geng ◽  
Cao Xi-Min
Keyword(s):  
Power Systems ◽  
Wind Turbine ◽  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Induction Generator ◽  
Future Research ◽  
Stable Operation ◽  
Subsynchronous Oscillation ◽  
Different Types

Background: Over the past few years, the subsynchronous oscillation (SSO) caused by the grid-connected wind farm had a bad influence on the stable operation of the system and has now become a bottleneck factor restricting the efficient utilization of wind power. How to mitigate and suppress the phenomenon of SSO of wind farms has become the focus of power system research. Methods: This paper first analyzes the SSO of different types of wind turbines, including squirrelcage induction generator based wind turbine (SCIG-WT), permanent magnet synchronous generator- based wind turbine (PMSG-WT), and doubly-fed induction generator based wind turbine (DFIG-WT). Then, the mechanisms of different types of SSO are proposed with the aim to better understand SSO in large-scale wind integrated power systems, and the main analytical methods suitable for studying the SSO of wind farms are summarized. Results: On the basis of results, using additional damping control suppression methods to solve SSO caused by the flexible power transmission devices and the wind turbine converter is recommended. Conclusion: The current development direction of the SSO of large-scale wind farm grid-connected systems is summarized and the current challenges and recommendations for future research and development are discussed.

scholarly journals A Novel Unsupervised Classification Method for Sandy Land Using Fully Polarimetric SAR Data

2021 ◽  
Vol 13 (3) ◽  
pp. 355
Author(s):  
Weixian Tan ◽  
Borong Sun ◽  
Chenyu Xiao ◽  
Pingping Huang ◽  
Wei Xu ◽  
...  
Keyword(s):  
Spectral Clustering ◽  
Large Scale ◽  
Clustering Algorithm ◽  
Feature Vector ◽  
Unsupervised Classification ◽  
Classification Method ◽  
Sandy Land ◽  
Classification Methods ◽  
The Many ◽  
Representative Points

Classification based on polarimetric synthetic aperture radar (PolSAR) images is an emerging technology, and recent years have seen the introduction of various classification methods that have been proven to be effective to identify typical features of many terrain types. Among the many regions of the study, the Hunshandake Sandy Land in Inner Mongolia, China stands out for its vast area of sandy land, variety of ground objects, and intricate structure, with more irregular characteristics than conventional land cover. Accounting for the particular surface features of the Hunshandake Sandy Land, an unsupervised classification method based on new decomposition and large-scale spectral clustering with superpixels (ND-LSC) is proposed in this study. Firstly, the polarization scattering parameters are extracted through a new decomposition, rather than other decomposition approaches, which gives rise to more accurate feature vector estimate. Secondly, a large-scale spectral clustering is applied as appropriate to meet the massive land and complex terrain. More specifically, this involves a beginning sub-step of superpixels generation via the Adaptive Simple Linear Iterative Clustering (ASLIC) algorithm when the feature vector combined with the spatial coordinate information are employed as input, and subsequently a sub-step of representative points selection as well as bipartite graph formation, followed by the spectral clustering algorithm to complete the classification task. Finally, testing and analysis are conducted on the RADARSAT-2 fully PolSAR dataset acquired over the Hunshandake Sandy Land in 2016. Both qualitative and quantitative experiments compared with several classification methods are conducted to show that proposed method can significantly improve performance on classification.

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