Please use this identifier to cite or link to this item: http://ir.buu.ac.th/dspace/handle/1513/302
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dc.contributorNattaporn Soontornen
dc.contributorณัฐพร สุนทรth
dc.contributor.advisorSHU HONGen
dc.contributor.advisorSHU HONGth
dc.contributor.otherBurapha University. Faculty of Geoinformaticsen
dc.date.accessioned2021-12-01T02:36:34Z-
dc.date.available2021-12-01T02:36:34Z-
dc.date.issued9/11/2020
dc.identifier.urihttp://ir.buu.ac.th/dspace/handle/1513/302-
dc.descriptionMaster Degree of Science (M.Sc.)en
dc.descriptionวิทยาศาสตรมหาบัณฑิต (วท.ม.)th
dc.description.abstractThe Three South Thailand crime is a conflict in the Malay Pattani region that began around  1948 as an ethnic and religious separatists’ crime. For centuries the Muslim Malay minority lived at peace with the Buddhist Thai majority in the Southern Thailand region. In 1947, Haji Sulong launched a petition campaign demanding autonomy of Islamic Law, he was arrested for treason then mysteriously disappeared 5 years later after release. By the 1950s a Patani Nationalist Movement began to lead to the South Thailand crime. It has become more complex and increasingly violent since 2001. The problem of crime affects the quality of life that causes a lot of damage both on a personal level and social level. It also affects the feelings of fear and insecurity that occur under living. The organization's government has collected his crime data, but a lot of that information is compiled in the document. Which was not analyzed in a crime mapping and data statistics to make the most of the benefit. The geographic information and data on crime, that will be displayed on a digital map and analyzed, such as the crime scene, the date and time of the crime, frequency of crime, continuity. As well as trends of crime current digital maps. The geographic information system (GIS) has to popular and widely used to help with crime analysis. In which crime can occur, it is necessary to have the area or location where the crime occurred. for example (home, school, or workplace) the area or location where this crime was taken consider, study and understand crime and guidelines for prevention. Crime mapping relates to the concept of levels of spatial analysis of crime. It explains crime at different levels. Crime mapping and statistical modeling is the most important role in the use of geospatial such as planning, tracking and updates, and staff assistance systems. Maps convey powerful messages to their readers, most of whom are not know the technicalities of crime mapping. The depicted in isoline maps implies that a center of high-crime activity exists, and criminal activity is gradually diminished when officials apply it to the current work. We interest in the concrete environment because if considering the city on spatial grounds, the causes of each type of crime will occur in a different physical environment of the city. It depends on the environment in the area such as building density, the time of the incident, and the operation of the police, both in the police service radius and the service radius of the police station. By the physical environment factors of the city as mentioned above, criminal cases are created in different frequency and severity in each area. Therefore, this paper focuses on the crime analysis using the kernel density estimation and two-step floating catchment area (2SFCA). The method divide into 2 parts, The crime mapping enables the understanding of crime phenomena in three province areas. It uses the kernel density estimation (KDE), and then to detect service support zone was identified to demand and supply area, by two-step floating catchment area method (2SFCA). The analysis and display have results included an application of the Geographic Information System (GIS) supplementary to the discussion. GIS technology helps to analyzed information, such as types of crime by location, the location of victim service organizations, and their geographic service areas. This chapter examines four types of crime theories in greater detail: place (point) theories; street (line) theories; area (polygon) theories; and repeat victim theories, which can operate on point, line, or polygon level. These theories describe the levels of hot spots and how these levels can be depicted on maps. The kernel density estimation and two-step floating catchment area of criminal cases in the 3 provinces uses Euclidean distance and grid space. It is suitable for the geometry of homogeneous space, which seeks to use the geometry of flat two-dimensional map spaces. It is found that the pattern of the spatial distribution of crime cases classified by crime type has different forms of crime depending on the circumstances of the crime, Such as urban areas, the market area, etc. As for the distribution of cases that occur during the daytime, the pattern of the cases is different from the night time. Therefore, CCTV should be installed in areas with high risk and should increase. Frequency cycle for checking the area following the time of the high risk of crime. And should arrange the period for the area inspection to be tighter. Which may divide the examination time into 4 hours and increase the frequency of examination in high-risk areas. This mapping can be used to examine the availability of basic services and the sufficiency of services groups. It can visually display multiple funding sources in a geographic area to help in a fair distribution of resources. It can be extremely useful in developing a strategic program for the maintenance and development of victim services.en
dc.description.abstract-th
dc.language.isoen
dc.publisherBurapha University
dc.rightsBurapha University
dc.subjectCRIME MAPPING; SPATIAL STATISTICS; KERNEL DENSITY ESTIMATION; TWO-STEP FLOAT CATCHMENT AREAen
dc.subject.classificationSocial Sciencesen
dc.titleTHE KERNEL DENSITY ESTIMATION FOR CRIME ANALYSIS:  A CASE STUDY IN THREE PROVINCES SOUTHERN OF THAILAND.en
dc.titleการวิเคราะห์ความหนาแน่นเชิงพื้นที่อาชญากรรมศึกษาตามแบบเคอร์เนล กรณีศึกษาพื้นที่สามจังหวัดชายแดนใต้ ประเทศไทยth
dc.typeTHESISen
dc.typeวิทยานิพนธ์th
Appears in Collections:Faculty of Geoinformatics

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