Identifying the urban-rural fringe using wavelet transform and kernel density estimation: A case study in Beijing City, China

2016 ◽  
Vol 83 ◽  
pp. 286-302 ◽  
Author(s):  
Jian Peng ◽  
Shiquan Zhao ◽  
Yanxu Liu ◽  
Lu Tian
Keyword(s):  
Wavelet Transform ◽  
Density Estimation ◽  
Kernel Density Estimation ◽  
Kernel Density ◽  
Beijing City ◽  
Urban Rural

Favorability functions based on kernel density estimation for logistic models: A case study

2008 ◽  
Vol 52 (9) ◽  
pp. 4533-4543 ◽  
Author(s):  
Ana Colubi ◽  
Gil González-Rodríguez ◽  
María José Domínguez-Cuesta ◽  
Montserrat Jiménez-Sánchez
Keyword(s):  
Density Estimation ◽  
Kernel Density Estimation ◽  
Logistic Models ◽  
Kernel Density

scholarly journals datplot

2021 ◽  
pp. 1-11
Author(s):  
Lisa Steinmann ◽  
Barbora Weissova
Keyword(s):  
Density Estimation ◽  
Kernel Density Estimation ◽  
Focal Point ◽  
Kernel Density ◽  
R Package ◽  
Line Graphs ◽  
Classical Archaeology ◽  
Northwestern Turkey ◽  
Epigraphic Evidence

This article introduces datplot, an R package designed to prepare chronological data for visualization, focusing on the treatment of objects dated to overlapping periods of time. Datplot is suitable for all disciplines in which scientists long for a synoptic method that enables the visualization of the chronology of a collection of heterogeneously dated objects. It is especially helpful for visualizing trends in object assemblages over long periods of time—for example, the development of pottery styles—and it can also assist in the dating of stratigraphy. As both authors come from the field of classical archaeology, the examples and case study demonstrating the functionality of the package analyze classical materials. In particular, we focus on presenting an assemblage of epigraphic evidence from Bithynia (northwestern Turkey), with a microregional focal point in the territory of Nicaea (modern Iznik). In the article, we present the internal methodology of datplot and the process of preparing a dataset of categorically and numerically dated objects. We demonstrate visualizing the data prepared by datplot using kernel density estimation and compare the outcome with more established methods such as histograms and line graphs.

scholarly journals Measuring Urban Renewal: A Dual Kernel Density Estimation to Assess the Intensity of Building Renovation—Case Study in Lisbon

Urban Science ◽  
2018 ◽  
Vol 2 (3) ◽  
pp. 91 ◽  
Author(s):  
Filipe Brandão ◽  
Ricardo Correia ◽  
Alexandra Paio
Keyword(s):  
Density Estimation ◽  
Kernel Density Estimation ◽  
Data Gathering ◽  
Kernel Density ◽  
Parametric Modeling ◽  
Industrialized Countries ◽  
Urban Context ◽  
Construction Activity ◽  
Context Data

In the cities of post-industrialized countries, renovation is the main part of building construction activity and has a major urban impact. Measuring this ongoing phenomenon and its distribution is of great usefulness for municipality urban planning and public policies. In this context, it is essential to introduce tools and processes that can allow for describing and predict how building renovation evolves. Open databases have become a valuable resource for observing processes and interactions in urban context. Data-driven analysis methods were used to directly interact with open city data, thus aiming to propose an alternative building renovation approach based on data gathering, parametric modeling, and visualization. Kernel Density Estimation (KDE) is an efficient tool that overcomes incomplete data, as not all renovation is reported to city halls. This article presents a preliminary study on a method of measuring building renovation intensity using the city of Lisbon building permit alphanumerical and spatial database as a case study.

scholarly journals Delimitating Urban Commercial Central Districts by Combining Kernel Density Estimation and Road Intersections: A Case Study in Nanjing City, China

2019 ◽  
Vol 8 (2) ◽  
pp. 93 ◽  
Author(s):  
Jing Yang ◽  
Jie Zhu ◽  
Yizhong Sun ◽  
Jianhua Zhao
Keyword(s):  
Density Estimation ◽  
Kernel Density Estimation ◽  
Quantitative Research ◽  
Kernel Density ◽  
New Method ◽  
The Road ◽  
Nanjing City ◽  
Road Intersections ◽  
Intersection Density

An urban, commercial central district is often regarded as the heart of a city. Therefore, quantitative research on commercial central districts plays an important role when studying the development and evaluation of urban spatial layouts. However, conventional planar kernel density estimation (KDE) and network kernel density estimation (network KDE) do not reflect the fact that the road network density is high in urban, commercial central districts. To solve this problem, this paper proposes a new method (commercial-intersection KDE), which combines road intersections with KDE to identify commercial central districts based on point of interest (POI) data. First, we extracted commercial POIs from Amap (a Chinese commercial, navigation electronic map) based on existing classification standards for urban development land. Second, we calculated the commercial kernel density in the road intersection neighborhoods and used those values as parameters to build a commercial intersection density surface. Finally, we used the three standard deviations method and the commercial center area indicator to differentiate commercial central districts from areas with only commercial intersection density. Testing the method using Nanjing City as a case study, we show that our new method can identify seven municipal, commercial central districts and 26 nonmunicipal, commercial central districts. Furthermore, we compare the results of the traditional planar KDE with those of our commercial-intersection KDE to demonstrate our method’s higher accuracy and practicability for identifying urban commercial central districts and evaluating urban planning.

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