scholarly journals Improvement of Spatial Autocorrelation, Kernel Estimation, and Modeling Methods by Spatial Standardization on Distance

2019 ◽  
Vol 8 (4) ◽  
pp. 199 ◽  
Author(s):  
Souris ◽  
Demoraes
Keyword(s):  
Spatial Analysis ◽  
Spatial Autocorrelation ◽  
Presidential Election ◽  
Spatial Modeling ◽  
Kernel Estimation ◽  
Direct Impact ◽  
Modeling Methods ◽  
Weighted Means ◽  
Point Set ◽  
Surface Calculation

In a point set in dimension superior to 1, the statistical distribution of the number of pairs of points as a function of distance between the points of the pair is not uniform. This distribution is not considered in a large number of classic methods based on spatially weighted means used in spatial analysis, such as spatial autocorrelation indices, kernel interpolation methods, or spatial modeling methods (autoregressive, or geographically weighted). It has a direct impact on the calculations and the results of indices and estimations, and by not taking into account this distribution of the distances, spatial analysis calculations can be biased. In this article, we introduce a "spatial standardization", which corrects and adjusts the calculations with respect to the distribution of point pairs distances. As an example, we apply this correction to the calculation of spatial autocorrelation indices (Moran and Geary indices) and to trend surface calculation (by spatial kernel interpolation) on the results of the 2017 French presidential election.

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.

scholarly journals Geospatial modeling, analysis and mapping for aerodrome land development

2021 ◽  
Vol 310 ◽  
pp. 04003
Author(s):  
Liudmila Mitsevich ◽  
Natalia Zhukovskaya
Keyword(s):  
Land Use ◽  
Spatial Modeling ◽  
Land Development ◽  
Spatial Modelling ◽  
Power Lines ◽  
Geospatial Modeling ◽  
Modeling Methods ◽  
Modeling Analysis ◽  
The Republic ◽  
Special Limitation

The article discusses aerodrome geospatial modeling methods and geoinformation analysis for determining land use zones and obstacle restriction areas. Tall trees, buildings and structures, exceeding special limitation surfaces in the aerodrome flight areas, are obstacles that are dangerous. Using spatial modelling, which determines maximal permissible heights, it is proposed to predict the heights of natural and artificial vertical objects in order to analyse and plan land use capabilities. As a basis for spatial modeling, it is proposed to use stereoscopic models with a resolution of 0.3m, built on aircraft-based scanner images. Using the methods of geoinformation analysis, it is suggested to make horizontal zoning of aerodrome areas according to the most important air navigation safety and ecological indicators (power lines, roads, permitted classes of construction objects location). The study presents the research results of the proposed methodology for the Republic of Belarus aerodrome.

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 KAJIAN PERUBAHAN PENGGUNAAN LAHAN DAN HARGA LAHAN DI WILAYAH SEKITAR PINTU TOL UNGARAN

2016 ◽  
Vol 18 (1) ◽  
pp. 53
Author(s):  
Dinda Kholivia Masykuroh ◽  
Iwan Rudiarto
Keyword(s):  
Land Use ◽  
Spatial Analysis ◽  
Land Use Change ◽  
Spatial Modeling ◽  
Surrounding Area ◽  
Land Price ◽  
Price Changes ◽  
Toll Road ◽  
Modeling Approach ◽  
Land Rents

<div><p class="AbstractEnglish">The operation of section I of Semarang-Solo toll road provides alternative access to Semarang City from its hinterland, especially Ungaran Subdistrict. Improved accessibility from Semarang City to Ungaran has impacted to land use of the surrounding area. It can be seen from the increase in new built-up areas in Kalirejo as well as Sidomulyo Villages. The land use change also gives impact to land rents or prices. This study aims to assess the land use and land price changes in the Villages of Kalirejo and Sidomulyo as a result of the existence of the Ungaran toll-gate. The methods used are quantitative completed with observation and review of the relevant documents. This study uses spatial modeling approach with ArcGIS software. Spatial analysis is used to determine the change of land use that occurred in the two villages in 2003, 2011 and 2014. The results of this study show that the existence of the Ungaran toll gate has triggered changes of non-built-up into the built-up area. Changes have also been there in the price of land in the two villages. Besides, this dynamic situation has encouraged the emergence of new sub-center located in the Kalirejo Village.</p></div>

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.

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.

scholarly journals Spatial Analysis of Gunshot Reports on Twitter in Mexico City

2021 ◽  
Vol 10 (8) ◽  
pp. 540
Author(s):  
Enrique García-Tejeda ◽  
Gustavo Fondevila ◽  
Oscar S. Siordia
Keyword(s):  
Spatial Analysis ◽  
Mexico City ◽  
Nearest Neighbor ◽  
Kernel Estimation ◽  
Test Methods ◽  
Spatial Concentration ◽  
The West ◽  
Exact Test ◽  
Firearm Violence ◽  
The City

The quarantine and stay-at-home measures implemented by most governments significantly impacted the volume and distribution of crime, and already, a body of literature exists that focuses on the effects of lockdown on crime. However, the effects of lockdown on firearm violence have yet to be studied. Within this context, this study analyzes reports of gunshots in Mexico City registered on Twitter from October 2018 to 2019 (pre-COVID-19) and from October 2019 to 2020 (during COVID-19), using a combination of spatial (nearest neighbor ratio, Ripley’s K function and kernel estimation) and non-spatial (Fisher’s exact test) methods. The results indicate a spatial concentration of gunshot reports in Mexico City and a reduction in frequency of reports during the pandemic. While they show no change in the overall concentration of gunshots during lockdown, they do indicate an expansion in the patterns of spatial intensity (moving from the west to the center of the city). One possible explanation is the capacity of possible victims of firearm crimes in certain municipalities to comply with lockdown measures and thus avoid exposure to such crimes.

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