scholarly journals Spatial sensitivity analysis for urban hotspots using cell phone traces

2021 ◽  
pp. 239980832098584
Author(s):  
Jiahui Wu ◽  
Enrique Frias-Martinez ◽  
Vanessa Frias-Martinez
Keyword(s):  
Sensitivity Analysis ◽  
Cell Phone ◽  
Large Scale ◽  
Urban Environments ◽  
Urban Life ◽  
Spatial Sensitivity ◽  
Methodological Choices ◽  
Spatial Sensitivity Analysis ◽  
Spatio Temporal ◽  
The Impact

Urban hotspots can be used to model the structure of urban environments and to study or predict various aspects of urban life. An increasing interest in the analysis of urban hotspots has been triggered by the emergence of pervasive technologies that produce massive amounts of spatio-temporal data including cell phone traces (or Call Detail Records). Although hotspot analyses using cell phone traces are extensive, there is no consensus among researchers about the process followed to compute them in terms of four important methodological choices: city boundaries, spatial units, interpolation methods, and hotspot variables. Using a large-scale CDR dataset from Mexico, we provide an interpretable systematic spatial sensitivity analysis of the impact that these methodological choices might have on the stability of the hotspot variables in both static and dynamic settings.

The Impact of Quantitative Easing on Emerging Markets – Literature Review

e-Finanse ◽  
2018 ◽  
Vol 14 (4) ◽  
pp. 67-76
Author(s):  
Piotr Bartkiewicz
Keyword(s):  
Emerging Markets ◽  
Large Scale ◽  
Empirical Literature ◽  
Quantitative Easing ◽  
Methodological Choices ◽  
The Subject ◽  
Methodological Approaches ◽  
The Impact ◽  
Sufficient Precision

AbstractThe article presents the results of the review of the empirical literature regarding the impact of quantitative easing (QE) on emerging markets (EMs). The subject is of interest to policymakers and researchers due to the increasingly larger role of EMs in the world economy and the large-scale capital flows occurring after 2009. The review is conducted in a systematic manner and takes into consideration different methodological choices, samples and measurement issues. The paper puts the summarized results in the context of transmission channels identified in the literature. There are few distinct methodological approaches present in the literature. While there is a consensus regarding the direction of the impact of QE on EMs, its size and durability have not yet been assessed with sufficient precision. In addition, there are clear gaps in the empirical findings, not least related to relative underrepresentation of the CEE region (in particular, Poland).

Dynamics of Aeolian Sand Streamers and Airflow Turbulence over a Beach Surface

2021 ◽  
Author(s):  
Andreas Baas
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Temporal Variability ◽  
Large Scale ◽  
Sonic Anemometer ◽  
Dynamic Structure ◽  
Sand Transport ◽  
Video Imagery ◽  
Spatio Temporal ◽  
The Impact

<p>Sand transport by wind over granular beds displays dynamic structure and organisation in the form of streamers (aka ‘sand snakes’) that appear, meander and intertwine, and then dissipate as they are advected downwind. These patterns of saltating grain populations are thought to be initiated and controlled by coherent flow structures in the turbulent boundary layer wind that scrape over the bed surface raking up sand into entrainment. Streamer behaviour is thus fundamental to understanding sand transport dynamics, in particular its strong spatio-temporal variability, and is equally relevant to granular transport in other geophysical flows (fluvial, submarine).</p><p>This paper presents findings on streamer dynamics and associated wind turbulence observed in a field experiment on a beach, with measurements from 30Hz video-imagery using Large-Scale Particle Image Velocimetry (LS-PIV), combined with 50Hz wind measurements from 3D sonic anemometry and co-located sand transport rate monitoring using an array of laser particle counters (‘Wenglors’), all taking place over an area of ~10 m<sup>2</sup> and over periods of several minutes. The video imagery was used to identify when and where streamers advected past the sonic anemometer and laser sensors so that relationships could be detected between the passage of turbulence structures in the airflow and the length- and time-scales, propagation speeds, and sand transport intensities of associated streamers. The findings form the basis for a phenomenological model of streamer dynamics under turbulent boundary layer flows that predicts the impact of spatio-temporal variability on local measurement of sand transport.</p>

scholarly journals Spatial sensitivity analysis of snow cover data in a distributed rainfall–runoff model

2014 ◽  
Vol 11 (10) ◽  
pp. 11987-12025 ◽  
Author(s):  
T. Berezowski ◽  
J. Nossent ◽  
J. Chormański ◽  
O. Batelaan
Keyword(s):  
Sensitivity Analysis ◽  
Distributed Data ◽  
Rainfall Runoff ◽  
Spatial Sensitivity ◽  
Wetspa Model ◽  
Spatial Parameters ◽  
Spatial Sensitivity Analysis ◽  
Rainfall Runoff Model ◽  
Different Response ◽  
Runoff Model

Abstract. As the availability of spatially distributed data sets for distributed rainfall–runoff modelling is strongly growing, more attention should be paid to the influence of the quality of the data on the calibration. While a lot of progress has been made on using distributed data in simulations of hydrological models, sensitivity of spatial data with respect to model results is not well understood. In this paper we develop a spatial sensitivity analysis (SA) method for snow cover fraction input data (SCF) for a distributed rainfall–runoff model to investigate if the model is differently subjected to SCF uncertainty in different zones of the model. The analysis was focused on the relation between the SCF sensitivity and the physical, spatial parameters and processes of a distributed rainfall–runoff model. The methodology is tested for the Biebrza River catchment, Poland for which a distributed WetSpa model is setup to simulate two years of daily runoff. The SA uses the Latin-Hypercube One-factor-At-a-Time (LH-OAT) algorithm, which uses different response functions for each 4 km × 4 km snow zone. The results show that the spatial patterns of sensitivity can be easily interpreted by co-occurrence of different environmental factors such as: geomorphology, soil texture, land-use, precipitation and temperature. Moreover, the spatial pattern of sensitivity under different response functions is related to different spatial parameters and physical processes. The results clearly show that the LH-OAT algorithm is suitable for the spatial sensitivity analysis approach and that the SCF is spatially sensitive in the WetSpa model.

scholarly journals Cultural investment and urban socio-economic development: a geosocial network approach

2017 ◽  
Vol 4 (9) ◽  
pp. 170413 ◽  
Author(s):  
Xiao Zhou ◽  
Desislava Hristova ◽  
Anastasios Noulas ◽  
Cecilia Mascolo ◽  
Max Sklar
Keyword(s):  
Urban Areas ◽  
Large Scale ◽  
Clustering Coefficient ◽  
Economic Deprivation ◽  
Large Scale Data ◽  
Investment Optimization ◽  
Spatio Temporal ◽  
Socio Economic Impact ◽  
Cultural Investment ◽  
The Impact

Being able to assess the impact of government-led investment onto socio-economic indicators in cities has long been an important target of urban planning. However, owing to the lack of large-scale data with a fine spatio-temporal resolution, there have been limitations in terms of how planners can track the impact and measure the effectiveness of cultural investment in small urban areas. Taking advantage of nearly 4 million transition records for 3 years in London from a popular location-based social network service, Foursquare, we study how the socio-economic impact of government cultural expenditure can be detected and predicted. Our analysis shows that network indicators such as average clustering coefficient or centrality can be exploited to estimate the likelihood of local growth in response to cultural investment. We subsequently integrate these features in supervised learning models to infer socio-economic deprivation changes for London’s neighbourhoods. This research presents how geosocial and mobile services can be used as a proxy to track and predict socio-economic deprivation changes as government financial effort is put in developing urban areas and thus gives evidence and suggestions for further policymaking and investment optimization.

Modeling the Impact of Mobility on the Connectivity of Vehicular Networks in Large-Scale Urban Environments

2016 ◽  
Vol 65 (4) ◽  
pp. 2753-2758 ◽  
Author(s):  
Xueshi Hou ◽  
Yong Li ◽  
Depeng Jin ◽  
Dapeng Oliver Wu ◽  
Sheng Chen
Keyword(s):  
Large Scale ◽  
Vehicular Networks ◽  
Urban Environments ◽  
The Impact
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