كليدواژه :
تصاوير داراي برچسب مكاني , محتواي توليد شده توسط كاربر , عكاسي داوطلبانه-نهاد , داده مكاني مردم گستر
چكيده فارسي :
شناخت مكانهاي محبوب و مورد توجه عموم در هر شهر و رتبه بندي آنها، كاربردهاي مختلفي از جمله توسعه گردشگري، مديريت ترافيك و برنامهريزي شهري دارد. يكي از روشهاي دستيابي به اين نوع ادراك مردمي، روش عكاسي داوطلبانه-نهاد است. در اين روش از افراد خواسته ميشود تا از مناظر مورد علاقه و غير مورد علاقهشان عكسبرداري نمايند. سپس محتواي اين تصاوير براي دستيابي به درك آنها از محيط مورد بررسي قرار ميگيرد. در حالي كه امروزه با توسعه وب 2، مردم عكسهايي كه از مناظر زيبا و يا موضوعات مورد توجه اخذ نمودهاند را به اشتراك ميگذارند. هدف از اين مقاله تلفيق مفهوم روش عكاسي داوطلبانه-نهاد و تحليل فراداده تصاوير مردمگستر در شناسايي و رتبهبندي مكانهاي مورد علاقه است. در اين تحقيق منطقه 6 شهر تهران به عنوان منطقه مطالعاتي در نظر گرفته شد و تصاوير داراي برچسب مكاني مربوط به آن استخراج گرديد. سپس از روش خوشهبندي تراكم مبناي مكاني همراه با نويز براي استخراج مكانهاي مورد توجه استفاده شد و هر مكان كشف شده تفسير و محبوبيت آن با توجه به محتواي تصاوير، تعداد تصاوير و تعداد بارگذارندگان تصاوير محاسبه گرديد. پارك لاله، پارك ساعي و ميدان فردوسي به ترتيب بالاترين امتياز محبوبيت را كسب كردند. تحليل زماني محبوبيت مكانهاي فوق نشان داد كه در مجموع ماههاي فروردين و ارديبهشت بيش از ساير ماهها مورد توجه عموم واقع شده است. تحليل كاربري مكانهاي كشف شده نيز بيانگر آن است كه كاربري فضاي سبز با اختلاف قابل توجهي بالاتر از ساير كاربريها قرار گرفته است. براي ارزيابي ميزان محبوبيت مكانها از مجموع امتيازاتي كه كاربران به هر مكان در سايتهاي GoogleMap و FourSquare داده اند، استفاده شد و نتيجه اين ارزيابي نشان داد كه در دسته مكانهاي خيلي محبوب بيشترين انطباق وجود دارد.
چكيده لاتين :
Identification people's regions of interest and ranking them based on their popularity level have many applications such as tourism development, traffic management and urban planning. Most of interesting places from tourism's view-points are parks, museums, historical places and scenic areas. To identify these places, it is necessary to access people's perception about environment. Accessing to this environmental perception isn't possible from traditional maps or satellite images. One approach to achieve this kind of people's environmental perception is VEP[1]. In this method, people are asked to take photos about subject of research and then the content of these photos are analyzed. So in the VEP method, the content of images is very important part. However, todays with the development of web 2, people share their taken photos from scenic places and interesting subjects. Each photo has metadata about its spatial location, identity and name of its up-loader, title and more. Therefore, researches in the field of geo-tagged photos, analyzed metadata of these photos. However, in this research, we investigated both of photos' content and metadata to rank popular places and it can be said that the integration of VEP and VGI methods is our main contribution.
Tehran region 6 was considered as the case study and its geo-tagged photos are extracted from Panoramio site. Then DBSCAN[2] method was applied to extract regions of interest. The DBSCAN method has many advantages that are 1) it is density-base and the place that have dense data points is identified as cluster. Therefore, it is appropriate for our research that density of photos is an indicator of place's popularity 2) Moreover, in this method, there is no need to know the number of clusters previously and 3) the shape of clusters can be arbitrary.
Two mandatory parameters of the DBSCAN method are Eps (Neighborhood’s radius) and MinPts (at-least number of points) but there isn't any ideal method to obtain optimal values of these parameters for all applications. Therefore, to find appropriate values, we ran DBSCAN with different parameters and finally we set Eps as 1000 and MinPts as 10, and in result, 17 clusters were identified. The concept of each cluster was identified based on GeoNames POI[3] and unrelated clusters of tourism were removed. Then the popularity score of each region of interest was computed based on its photos' contents, number of photos and number of up-loaders. One of the scene-recognition algorithms was applied to investigate photos' content. The Laleh Park, Saei Park and Ferdosi square achieved high popularity scores. In the next step, popularity of these places in different months, seasons and years were investigated. Totally it can be said that most of the photos were taken in the April and May, or in other words, in the spring. Moreover, the relation between regions of interest and their land-use types were investigated that shows that green-space was significantly more than other land- use types. The detected places were compared with tourist attractions in Tehran region 6 and this comparison showed that natural attractiveness such as parks and gardens have appeared more than other attractiveness in geo-tagged photos. Comparing the computed popularity score of each region of interest, with sum of its scores on GoogleMap and FourSquare, showed that more coincidence exists in the class of very popular place
