Modeling Positional Uncertainty Acquired Through Street Geocoding

2018 ◽  
Vol 9 (4) ◽  
pp. 1-22 ◽  
Author(s):  
Hyeongmo Koo ◽  
Yongwan Chun ◽  
Daniel A. Griffith
Keyword(s):  
Spatial Analysis ◽  
Spatial Autocorrelation ◽  
Positional Uncertainty ◽  
Potential Factors ◽  
Volusia County

This article describes how modeling positional uncertainty helps to understand potential factors of uncertainty, and to identify impacts of uncertainty on spatial analysis results. However, modeling geocoding positional uncertainty still is limited in providing a comprehensive explanation about these impacts, and requires further investigation of potential factors to enhance understanding of uncertainty. Furthermore, spatial autocorrelation among geocoded points has been barely considered in this type of modeling, although the presence of spatial autocorrelation is recognized in the literature. The purpose of this article is to extend the discussion about modeling geocoding positional uncertainty by investigating potential factors with regression, whose model is appropriately specified to account for spatial autocorrelation. The analysis results for residential addresses in Volusia County, Florida reveal covariates that are significantly associated with uncertainty in geocoded points. In addition, these results confirm that spatial autocorrelation needs to be accounted for when modeling positional uncertainty.

scholarly journals A Novel Efficiency Measure Model for Industrial Land Use Based on Subvector Data Envelope Analysis and Spatial Analysis Method

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Wei Chen ◽  
Rui He ◽  
Qun Wu
Keyword(s):  
Land Use ◽  
Spatial Analysis ◽  
Spatial Autocorrelation ◽  
Industrial Development ◽  
Efficiency Measure ◽  
Industrial Land ◽  
Envelope Analysis ◽  
Land Use Efficiency ◽  
Industrial Land Use ◽  
Use Efficiency

With the rapid and unbalanced development of industry, a large amount of cultivated land is converted into industrial land with lower efficiency. The existing research is extensively concerned with industrial land use and industrial development in isolation, but little attention has been paid to the relationship between them. To help address this gap, the paper creates a new efficiency measure method for industrial land use combining Subvector Data Envelope Analysis (DEA) with spatial analysis approach. The proposed model has been verified by using the industrial land use data of 30 Chinese provinces from 2001 to 2013. The spatial autocorrelation relationship between industrial development and industrial land use efficiency is explored. Furthermore, this paper examines the effects of industrial development on industrial land use efficiency by spatial panel data model. The results indicate that the industrial land use efficiency and the industrial development level in the provinces of eastern region are higher than those of the western region. The spatial distribution of industrial land use efficiency shows remarkable positive spatial autocorrelation. However, the level of industrial development has obvious negative spatial autocorrelation since 2009. The improvement of industrial development has a significant positive impact on the industrial land use efficiency.

Spatial Autocorrelation and Association Measures

2011 ◽  
pp. 1502-1508
Author(s):  
J. Negreiros ◽  
M. Painho ◽  
I. Lopes ◽  
A.C. Costa
Keyword(s):  
Spatial Analysis ◽  
Spatial Autocorrelation ◽  
Spatial Data ◽  
Regional Analysis ◽  
Geographical Information ◽  
Association Measures ◽  
Share Data ◽  
Definition Of ◽  
Graphic Database

Several classical statements relating to the definition of GIS can be found in specialized literature such as the GIS International Journal, expressing the idea that spatial analysis can somehow be useful. GIS is successful not only because it integrates data, but it also enables us to share data in different departments or segments of our organizations. I like this notion of putting the world’s pieces back together again (ArcNews, 2000). “GIS is simultaneously the telescope, the microscope, the computer and the Xerox machine of regional analysis and the synthesis of spatial data” (Abler, 1988). “GIS is a system of hardware, software and liveware implemented with the aim of storing, processing, visualizing and analyzing data of a spatial nature. Other definitions are also possible” (Painho, 1999). “GIS is a tool for revealing what is otherwise invisible in geographical information” (Longley, Goodchild, Maguire, & Rhind, 2001). Certainly, GIS is not a graphic database.

scholarly journals Autokorelasi Spasial untuk Identifikasi Pola Hubungan Kemiskinan di Jawa Timur

2012 ◽  
Vol 3 (1) ◽  
pp. 217
Author(s):  
Rokhana Dwi Bekti
Keyword(s):  
Spatial Analysis ◽  
Spatial Autocorrelation ◽  
Moran’S I ◽  
Poor People ◽  
Spatial Autocorrelation Analysis ◽  
Autocorrelation Analysis ◽  
Moran's I ◽  
Relationship Of ◽  
The Relationship

Spatial autocorrelation is a spatial analysis to determine the relationship pattern or correlation among some locations (observation). On the poverty case of East Java, this method will provide important information for analyze the relationship of poverty characteristics in each district or cities. Therefore, in this research performed spatial autocorrelation analysis on the data of East Java’s poverty. The method used is moran's I test and Local Indicator of Spatial Autocorrelation (LISA). The analysis showed that by the moran's I test, there is spatial autocorrelation found in the percentage of poor people amount in East Java, both in 2006 and 2007. While by LISA, obtained the conclusion that there is a significant grouping of district or cities.

scholarly journals Social Deprivation, Waiting Time for Diagnosis and Therapeutic Management of Patients With Prostatic Cancer in the Somme Area, France

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 66s-66s
Author(s):  
H. Ben Khadhra ◽  
F. Saint ◽  
E. Trecherel ◽  
B. Lapotre-Ledoux ◽  
S. Zerkly ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Spatial Analysis ◽  
Spatial Autocorrelation ◽  
Cancer Registry ◽  
Waiting Time ◽  
Cancer Incidence ◽  
Social Deprivation ◽  
Socioeconomic Deprivation ◽  
Socioeconomic Level ◽  
Prostate Cancer Incidence

Background: In France, prostate cancer is at the top of the list of the most common cancers in men. The morbidity and mortality of this cancer were found to be related to the geographic level of socioeconomic deprivation with a higher rate of mortality and more frequent aggressive cases among men with low socioeconomic level, this was associated with health disparities in the management of this cancer. Our study region is considered as an economically deprived area with a poverty rate significantly higher than the national average. Aim: The aim of our study was to assess the impact of the socioeconomic level on the incidence, mortality, aggressiveness and management of prostate cancer, using data from a population-based cancer registry. Methods: For this research, prostate cancer data, between 2006 and 2010, were obtained from the Somme area cancer registry. Social economic status was assessed using the European Deprivation Index (EDI). This index has been used to classify each geographical unit (IRIS) according to social deprivation. IRIS is the smallest submunicipal geographical entity for which census data are available. Each prostate cancer case was allocated to the corresponding IRIS by geolocalizing the addresses using geographic information system (GIS). For spatial analysis, hierarchical generalized linear modeling was fitted. To assess for spatial autocorrelation, Moran's I test was conducted and then spatial autocorrelation was modeled by a set of random effects that are assigned a conditional autoregressive (CAR) prior distribution. Results: A total of 2405 incident cases of prostate cancer were registered in the Somme area. The age-standardized rate was 98.2 cases per 100,000 person-years (PY). The standardized mortality rate was 28.1 deaths per 105 PY. The coefficient associated with the EDI obtained from the spatial analysis of prostate cancer incidence was negative (-0.348; 95% CI: −0.0831) which indicates that prostate cancer incidence was more important in the less deprived areas. The relative risk of prostate cancer mortality associated with the quintile 5 of the EDI relatively to quintile 1 was 3.09; 95% CI: [1.70-5.59]. For the aggressiveness, the coefficient associated with the EDI was 0.0493 with a 95% CI: [0.0162-0.0810], and the Q5/Q1 RR was equal to 1.36 95% CI: [1.09-1.73]. EDI estimated coefficient for proportion of cases who received curative treatment versus patients who received palliative treatment was −0.1089, 95 CI%: [−0.1505 to −0.0693]. EDI coefficient for waiting time was not significant. Conclusion: Our study showed a significant association between socioeconomic deprivation and prostate cancer with worse outcomes among men with the lowest socioeconomic status. Geographical differences in screening rate could explain this pattern. More in-depth research with a source data review is required to know precisely the determinism of this association and therefore adjust the eventual disparities.

Mining Activities and the Spatial-Temporal Variations of Earthquakes in Southern Africa

2018 ◽  
Vol 3 (1) ◽  
pp. 23-29
Author(s):  
Charles Mborah
Keyword(s):  
Spatial Analysis ◽  
Southern Africa ◽  
Temporal Distribution ◽  
Temporal Variations ◽  
Mining Activities ◽  
Earthquake Occurrence ◽  
Key Factors ◽  
The World ◽  
Potential Factors ◽  
Weak Zones

Spatial-temporal variations in earthquake occurrence have been studied in many regions of the world but little can be said aboutthe Southern Africa Region in this regard. Using earthquakes of magnitudes greater than or equal to one together with theFORTRAN language and Generic Mapping Tools (GMT), spatial variations of earthquakes spanning the period 1966 to 2014were examined for the region. Similarly, the temporal variations with earthquakes of magnitudes greater than or equal to fourwere studied. The spatial analysis showed that the highest number of events (1438) in the period occurred at an average depthof around 7.5 km representing approximately 79.9 % of the total earthquakes considered. The temporal distribution of events onthe other hand showed that the highest number of events (590) were recorded in the year 1993. Three main issues were identifiedas potential factors responsible for the observed variations. Activities such as mining and failures in weak zones of the rockmass as well as increase in the number of stations were identified as the key factors responsible for the observed distributions.The third factor could not be independently verified. However, earlier studies suggest that this factor indeed have caused majorearthquakes in the region.

scholarly journals Spatial Analysis of Pottery Presence at the Former Pobedim Hillfort (an Archeological Site in Slovakia)

2019 ◽  
Vol 11 (23) ◽  
pp. 6873
Author(s):  
Vojteková ◽  
Vojtek ◽  
Tirpáková ◽  
Vlkolinská
Keyword(s):  
Spatial Analysis ◽  
Spatial Autocorrelation ◽  
High Frequency ◽  
Arable Land ◽  
Kriging Interpolation ◽  
Archaeological Research ◽  
High Concentration ◽  
The Difference ◽  
Subsequent Comparison ◽  
Archeological Site

The aim of this study was a spatial analysis of the pottery occurrence (potsherds) in the acropolis part of the Pobedim hillfort (Slovakia) using two spatial statistical methods (spatial autocorrelation and kriging interpolation) with the help of GIS and their subsequent comparison. To understand the landscape of the study area, seven land use maps were created for different historical years (1783–1785, 1845, 1882, 1956, 1971, 2010 and 2017) confirming that the study area was predominantly utilized as arable land, which was related to advantageous floodplain location between the rivers of Horný Dudváh and Dubová. Using the Moran coefficient of spatial autocorrelation, it was found that there were seven high–high clusters and three high–low clusters representing the occurrence of potsherds. Using the kriging interpolation, three clusters of high concentration were found. Subsequent comparison of both methods revealed three identical areas with high frequency of pottery occurrence indicating places where significant settlement objects were located, such as the dwelling of a wealthy man, pottery workshop and the like. The difference between the areas with high number of potsherds between the two methods is approximately 12%, which indicates an acceptable match between the two methods and their applicability for spatial (geographic)–archaeological research.

scholarly journals The path of canine visceral leishmaniasis versus the path of Center for Zoonoses Control: contributions of spatial analysis to health

2022 ◽  
Vol 38 (1) ◽  
Author(s):  
Patricia Sayuri Silvestre Matsumoto ◽  
Edilson Ferreira Flores ◽  
José Seguinot Barbosa ◽  
Umberto Catarino Pessoto ◽  
José Eduardo Tolezano ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Visceral Leishmaniasis ◽  
Spatial Autocorrelation ◽  
Public Policies ◽  
Public Health Problem ◽  
Sao Paulo ◽  
P Value ◽  
São Paulo ◽  
Paulo State ◽  
São Paulo State

Visceral leishmaniasis (VL) is a public health problem in Brazilian municipalities. As much as there is a planning of public policies regards VL in São Paulo State, new cases have been reported and spread. This paper aims to discuss how the Center for Zoonoses Control conducts its actions spatially in endemic city of Presidente Prudente, São Paulo State. Data are from the Municipal Health Department of Presidente Prudente, Adolfo Lutz Institute, and Brazilian Institute of Geography and Statistics. We spatially estimated the dog population per census tract and used geoprocessing tools to perform choropleth maps, spatial trends, and spatial autocorrelation. We found a spatial pattern of higher prevalence in the city’s outskirt and a positive statistically significant spatial autocorrelation (I = 0.2, p-value < 0.000) with clusters of high-high relationships in the Northwest part of the city. Moreover, we identified a different direction in the path of the conducted serosurveys versus the canine VL trend, which stresses the fragility of the Center for Zoonoses Control actions to control the disease. The Center for Zoonoses Control always seems to chase the disease. The spatial analysis may be useful for rethinking how the service works and helps in public policies.

A Spatial Analysis of Selected Art: a GIScience-Humanities Interface

2020 ◽  
Vol 14 (1-2) ◽  
pp. 154-175
Author(s):  
Daniel A. Griffith
Keyword(s):  
Information Systems ◽  
Spatial Analysis ◽  
Geographic Information Systems ◽  
Spatial Autocorrelation ◽  
Matrix Algebra ◽  
Remotely Sensed ◽  
Geographic Information ◽  
Statistical Analyses ◽  
Remotely Sensed Images

This exposition presents little-known connections between geography, through geographic information systems (GISs), mathematics, through matrix algebra, and art, through paintings and images, adding to the geo-humanities, spatial humanities, and humanistic mathematics literature. To this end, findings summarized for spatial statistical analyses of selected Susie Rosmarin paintings (which are reminiscent of visualizations of certain mathematical quantities known as eigenvectors), remotely sensed images that have appeared in art exhibits, and selected famous paintings by historically renowned artists reveal that spatial autocorrelation constitutes a fundamental element of art. These analyses extend the tradition of visualizing fractals as art, and interfacing cartography with art. This paper promotes analytical art, and establishes additional commonalities for GIScience, mathematics, and art.

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