Standard Deviational Ellipse (SDE) models for malaria surveillance, case study: Sukabumi district-Indonesia, in 2012

Eryando, Tris; Susanna, Dewi; Pratiwi, Dian; Nugraha, Fajar

doi:10.1186/1475-2875-11-s1-p130

Cited by 27 publications

(18 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Standard deviation ellipse (SDE) can reveal geographical spatial characteristics and spatio-temporal evolution from the perspectives of center of gravity, distribution range, direction and shape, etc. [33]. It is a method to accurately reveal various economic distribution characteristics by using spatial statistical methods.…”

Section: Standard Deviation Ellipsementioning

confidence: 99%

An Approach to the Temporal and Spatial Characteristics of Vegetation in the Growing Season in Western China

et al. 2020

View full text Add to dashboard Cite

Since the implementation of the great western development strategy in 2000, the ecological environment in the western region of China has been significantly improved. In order to explore the temporal and spatial characteristics of vegetation coverage in the western region, this paper adopted the method of Maximum Value Composite (MVC) to obtain the mean Normalized Difference Vegetation Index (NDVI) of vegetation on the basis of the Moderate-resolution Imaging Spector audiometer (MODIS) data of 2000/2005/2010/2015/2018. Thereafter, the spatio-temporal differentiation characteristics of vegetation in western China were analyzed. The results show that: (1) According to the time characteristics of vegetation coverage in the western region, the average annual NDVI value of vegetation coverage in the growing season in the western region fluctuated between 0.12 and 0.15, among which that of 2000 to 2010 fluctuated more greatly but did not show obvious change trend. (2) Based on Sen trend and Mann-Kendall test analysis, the area of vegetation coverage improvement in the western region from 2000 to 2018 was larger than that of significant vegetation degradation. (3) From the perspective of global autocorrelation coefficient, Moran’s I values were all positive from 2000 to 2018, which indicates that the vegetation coverage in the west showed strong positive autocorrelation in each period. According to the average value and coefficient of variation of vegetation coverage, the vegetation coverage was lower in 2000, its internal variation was smaller, and the vegetation coverage increased with time. According to the local spatial autocorrelation analysis, the vegetation coverage levels in different regions varied greatly. (4) The standard deviation ellipse method was used to study the spatial distribution and directional transformation of vegetation. It makes the result more intuitive, and the three levels of gravity center shift, direction shift, and angle shift were considered: the vegetation growth condition in the spatial aggregation area improved in 2015; the standard deviation ellipses in 2000 and 2018 overlapped and shifted eastward, which indicates that the vegetation coverage conditions in the two years were similar and got ameliorated.

show abstract

Section: Standard Deviation Ellipsementioning

confidence: 99%

An Approach to the Temporal and Spatial Characteristics of Vegetation in the Growing Season in Western China

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Ellipse allows distribution characteristics to go longitudinally and have certain orientation. Graphing ellipses was used in disease surveillance studies to predict spatial spread trends, since the central tendency and dispersion are two principal aspects concerned by epidemiologists [46,47]. The calculations are as in Equations 9a and 9b below:…”

Section: Standard Deviational Ellipsementioning

confidence: 99%

Distribution and Spatial Pattern Analysis on Dengue Cases in Seremban District, Negeri Sembilan, Malaysia

Majid¹,

Nazi²,

Mohamed³

2019

Sustainability

View full text Add to dashboard Cite

Dengue fever disease increases alongside urbanization rate in tropical countries. Hence, the need to visualize the distribution pattern of increases is vital for the management of dengue cases, especially in Malaysia. Thus, the dengue surveillance system is proposed for the monitoring of dengue cases using computer-generated modeling for spatial distribution patterns, which is important for management and control. The present study performed distribution and spatial pattern analysis of dengue cases reported in the growing Seremban district in Negeri Sembilan, Malaysia in 2008 and 2009. The purpose of the study is to evaluate the pattern of distribution and determine whether it is clustered or dispersed. A total of 1401 and 1056 cases for dengue-related diseases were reported by the Ministry of Health Malaysia in Seremban district in the years 2008 and 2009, respectively. Three spatial statistical analysis were conducted: Spatial mean center, directional distribution, and standard distant on distribution of dengue cases reported. This study found that the distribution pattern for dengue cases is clustered. Spatial mean center and directional distribution for both sets of years have slight differences. Meanwhile, standard distance for dengue cases reported in the year 2008 is 22,085.82 m, which is bigger than dengue cases reported in 2009, showing a standard distance of 20,318.35 m. More sets of cases throughout years are required in further studies to identify factors that contribute to dengue epidemiology in the Seremban district undergoing urbanization.

show abstract

“…The standard deviational ellipse is a classic algorithm for analyzing the spatial distribution characteristics of the point dataset. This algorithm is used to measure the direction and distribution characteristics of the dataset, and the output is an ellipse [37]. The long axis of the ellipse represents the maximum diffusion direction of the study data, and the short axis of the ellipse represents the minimum diffusion direction of the study data [38].…”

Section: Standard Deviational Ellipse Analysismentioning

confidence: 99%

Analysis of Spatial Characteristics of Digital Signage in Beijing with Multi-Source Data

Zhang

Jiang

et al. 2019

IJGI

View full text Add to dashboard Cite

Digital signage is an important medium for urban outdoor advertising. Understanding the spatial distribution characteristics and factors that influence the site of digital signage are conducive to the efficient, standardized, and sustainable development of digital signage. The outdoor commercial digital signage within the Sixth Ring Road in Beijing is taken as the research object, and social network check-ins, housing prices, traffic network centrality and the mount of commercial facilities are considered factors that influence digital signage. The spatial distribution characteristics of digital signage are studied by using point pattern analysis methods. Moreover, we use three spatial clustering algorithms to study the hierarchical spatial characteristics of digital signage and test the effectiveness of the results. In addition, the factors that influence the distribution of digital signage are analyzed by Spearman correlation analysis. The results indicate that (1) the digital signage in Beijing generally presents a relatively concentrated distribution with centrality and forms an obvious gathering area and the agglomeration centers are mainly concentrated in the core parts of the central business district (CBD). (2) Digital signage is categorized into three groups, the traffic-oriented, the population-oriented, and the market-oriented. In addition, the spatial distribution of digital signage is consistent with the historical urban development of Beijing. (3) The social network check-ins with dynamic population characteristics had the highest correlation with the operation cost of digital signage. The spatial characteristics of digital signage evaluated in this study can effectively enhance the sustainable management of digital signage and provide a reference for research of the sustainable allocation of digital signage resources.

show abstract

Standard Deviational Ellipse (SDE) models for malaria surveillance, case study: Sukabumi district-Indonesia, in 2012

Cited by 27 publications

References 4 publications

An Approach to the Temporal and Spatial Characteristics of Vegetation in the Growing Season in Western China

An Approach to the Temporal and Spatial Characteristics of Vegetation in the Growing Season in Western China

Distribution and Spatial Pattern Analysis on Dengue Cases in Seremban District, Negeri Sembilan, Malaysia

Analysis of Spatial Characteristics of Digital Signage in Beijing with Multi-Source Data

Contact Info

Product

Resources

About