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سنجش قابلیت جرمخیزی پارک‌های شهری خوی براساس مدل ترکیبی | ||
| پژوهشهای جغرافیای انسانی | ||
| مقاله 7، دوره 48، شماره 2، تیر 1395، صفحه 297-312 اصل مقاله (1.44 M) | ||
| نوع مقاله: مقاله علمی پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jhgr.2016.54640 | ||
| نویسندگان | ||
| ژیلا سجادی* 1؛ حسن جنگی2 | ||
| 1دانشیار جغرافیا و برنامه‌ریزی شهری، دانشگاه شهید بهشتی | ||
| 2دانشجوی دکتری جغرافیا و برنامه‌ریزی شهری، دانشگاه شهید بهشتی | ||
| چکیده | ||
| در این مقاله، ظرفیتسنجی جرائم انجامشده در پارک‌های شهر خوی انجام میگیرد و داده‌ها براساس سه مدل ضریب‌ویژگی، استانداردسازی و از طریق AHP رتبه‌بندی میشوند. پس از شناسایی هشت پارک مهم شهر، ابتدا جرائم از نظر فراوانی و درصد طبقه‌بندی میشوند. سپس با توجه به معیارها و زیرمعیارهای رسمی طبقه‌بندی‌شدة جرم در کتب حقوقی، مدل ضریب‌ویژگی و استانداردسازی داده‌ها پیاده شد. در پایان نیز با استفاده از نرم‌افزار Expert Choice، تمامی معیارها و زیرمعیارها از طریق مقایسة دوبه‌دویی انجام گرفت و خروجی‌های آن به‌صورت جداول طبقه‌بندی‌شده تنظیم شد. مطابق نتایج، پارک طوبی (بهاران) براساس انواع مختلف جرمخیزی در رتبة اول و پارک ملت در رتبة آخر قرار دارد. خریدوفروش مواد مخدر، رابطۀ نامشروع و قماربازی و شرط‌بندی نیز از نظر شدت و تعداد در رتبه‌های اول تا سوم قرار گرفتند. همچنین نتایج نشان داد دو پارک شهر شادی و لاله شرایط نامساعدی برای حیات آتی دارند و شهر شادی به‌عنوان مهم‌ترین مکان تفریحی در گذشته، هم‌اکنون اوضاع بسیار نامطلوبی از جمله حضور مداوم معتادان و جرائم عمومی دارد. برای سنجش شدت جرائم براساس افکار عمومی، بعد از طبقه‌بندی آنها به زبان ساده، 382 نمونه از مجموع 75000 عضو جامعة آماری، براساس فرمول کوکران انتخاب شدند و پرسشنامه در هشت پارک منتخب توزیع شد. سپس براساس آن، جرائم براساس شدت از 1 تا 5 امتیازدهی شدند. براساس نتایج، قتل با 1910 و بچهدزدی با 1786 بیشترین و ایجاد مزاحمت برای بانوان با 765 و وندالیسم با 708، کمترین امتیاز را کسب کردند. | ||
| کلیدواژه‌ها | ||
| استانداردسازی؛ جرم؛ ضریب‌ویژگی؛ فضای سبز عمومی (پارک)؛ AHP | ||
| عنوان مقاله [English] | ||
| Potential of Urban Parks in Occurrence of Crime, based on Feature Coefficient Model, Standardization of Data and AHP (Case Study: Khoy City) | ||
| نویسندگان [English] | ||
| Zhila Sajadi1؛ Hassan Jangi2 | ||
| 1Associate Professor of Geography and Urban Planning, Shahid Beheshti University, Tehran, Iran | ||
| 2Ph.D. Candidate in Geography and Urban Planning, Shahid Beheshti University, Tehran, Iran | ||
| چکیده [English] | ||
| Introduction One of the most important concerns of modern human population is presence in public spaces such as parks and increased happiness in life. Perhaps the most important problem to realize is the crime that threatens the future of a park. In the definition of the crime, it is explained as an act or the commission of an act that is forbidden or the omission of a duty that is commanded by a public law and that makes the offender liable to punishment by that law (Britannica) and park is an area of land, usually in a largely natural state, for the enjoyment of the public, facilities for rest and recreation, often owned, set apart, and managed by a city, state, or nation or an enclosed area or a stadium used for sports (dictionary.com). Also, a public space is a social space such as a town square that is generally open and accessible. Public space has also become something of a touchstone for critical theory in relation to philosophy, (urban) geography, visual art, cultural studies, social studies and urban design. The term 'public space' is also often misconstrued to mean other things such as 'gathering place', which is an element of the larger concept of social space (Sensagent). Therefore, the most important goal of urban planner is to recognize these parks as places of recreation and leisure in summer Methodology In this research, we identify and classify the nature of crime in the Khoy city. Khoy city is located in a vast plain surrounded by mountains .It is the first city in Qarbi Azarbaijan Province in extent and the second largest city in terms of population. It has nearly 22 parks and gardens that require to be studied to measure crimes in these parks. The names of these parks are Mellat, Laleh, Golestan, Touba (Baharan), Sheikh Navaei, Shahre Shadi, 22 Bahman and Niloufar. Ranking of crime in city parks was undertaken by a factor of three models feature coefficient, standardization of data and the AHP method. The research method was descriptive– analytical and has been used to collect data from documents, interview, direct observation and correlation. At first, according to legal books, in a simple and clear classification of the crimes based on the Criterion and sub Criterion the precise location of each park were determined along with the surrounding neighborhoods. After identifying the main 8 parks, crimes was examined to frequency and percentage and then specified ranking. Results and Discussion In the next stage, the model of feature coefficient was based on standardization of data and the AHP method. In the this study, a new way, in terms of the number, the most important crimes within 8 parks city has been identified and specified the coefficients and points of this parks. These were selected based on the most attracting population and traffic volume. Total 75,000 cases as statistical population were achieved. The estimated population through direct observation in the parks and by Cochrane Methodology was published in 382 forms of the scoring table. It was asked of respondents to submit score of 1 to 5. Number 1 is superficial crime and number 5 is serious crime. Points were calculated by sum of the coefficients of 1 to 5 to number of respondents to determine percentage to total crime in a park. The results indicated that murder with 1910 events, baby kidnapping with 1786 are the maximum and harassing to women with 765 and vandalism with 708 are the minimum score. After this, model of feature coefficient was performed based on Criterion and Standardization of data based on sub-Criterion. In order, Touba (Baharan) park with 42.2, Shahre Shadi with 36.1 and Laleh with 26.63 gained the highest scores. At the end, for calculation of AHP based on Expert Choice Software, we conducted pairwise comparison in the all criteria and sub-criteria. The results were adjusted similar by classified table. Also, it should be notedthat Touba (Baharan) park with 0.184, Shahre Shadi with 0.156, and Laleh with 0.144 gained the highest scores. Thus, ranking of all the crimes were classified based on the frequency and severity and also based on three models feature coefficients, standardization of data and the AHP. Conclusion The results of all the studies indicated that Touba (Baharan) park based on all crimes is the first place and Mellat Park in final place. Since the Mellat Park is the newest park, except crimes against property, in all crimies is on low rank. In total, Mellat Park is secure in terms of frequency and severity of crimes. The main reasons for good condition in this park are continuous monitoring by police (Nirouye Entezami), having numerous guards and trained and public participation to keep the park healthy. It is important that Shahre Shadi Park on such circumstances has been built several years ago but nowit is the second park in the crime. Therefore, the most important guidelines and recommendations is revival of values in Shahre Shadi park and seriousness of on keeping the Mellat park until be avoided become a backyard. Shahre Shadi and Laleh parks are on the bad condition. Addicts and general crimes are high, alarming and worrying.in the Laleh Park has increased harassing to women. Touba (Baharan) Park is one of the most important places for drugs crimes at the midday and afternoon hours. The most important reasons are inadequate lighting, low patrolling and no program by police. WC is Very dirty places for addicts. Also, on the classification of crimes, buy and sell of drugs in Touba (Baharan) Park and Shahre Shadi have the highest frequency but low severity than murder and baby kidnapping. Finally, essential key for the survival of all parks is public participation on the education and making healthy parks. | ||
| کلیدواژه‌ها [English] | ||
| AHP, crime, feature coefficient, public green space, standardization of data | ||
| مراجع | ||
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