3/30/2023 0 Comments Poi organizer![]() ![]() Therefore, a framework is required to expedite the tagging and authentication process of the tagged data in an efficient manner to exploit the power of POI data. Although POI on Bhuvan is improving day by day however to overcome the challenges mentioned above is an important task. Hence, it's a need of hour to enrich the unique Indian GIS portal "Bhuvan" with Point of Interest (POI) data where one can find all necessary information. Maximum public places even in a small village must be geotagged to provide better citizen centric services specifically in developing countries. There are some challenges with this data, such as authentication and skewedness. People have been contributing large amount of data every day in Geographical Information Portal however to harness the real power of this tremendous amount of data, it must be managed efficiently. The data products generated from this study are of great use for quantitative urban studies at the building level. The proposed framework is transferrable to other China cities for deriving the information of building types from web mapping platforms. Our NLP-based approaches and building type identification methods show overall accuracies of 89.0% and 78.2%, and kappa coefficient of 0.71 and 0.83, respectively. The proposed framework was tested using over 440,000 building footprints in Beijing, China. Second, based on the relationship between building footprints and POIs, we identified building types using two indicators of type ratio and area ratio. First, we used natural language processing (NLP)-based approaches (i.e., text similarity measurement and topic modeling) to automatically reclassify POI categories into which can be used to directly infer building types. ![]() In this paper, we proposed a framework to derive the information of building type using geospatial data, including point-of-interest (POI) data, building footprints, land use polygons, and roads, from Gaode and Baidu Maps. However, in many parts of the world, this information is still missing. The information of building types is highly needed for urban planning and management, especially in high resolution building modeling in which buildings are the basic spatial unit. ![]() We demonstrate the implementation and results from this methodology using one of the most popular sailing regions of Greece, namely the Ionian Sea, as a case study. In this paper, we describe a methodology for the automatic generation of route recommendations, based on the semantic modelling of spatial data, and the determination of realistic sea route options, based on vessel density maps produced from raw AIS data. Current literature demonstrates a complete lack of research in the development of itinerary recommendation systems in the context of sailing holidays. The tourists’ experience during the initial contemplation and planning phase, taking place weeks or months before an actual trip, and where a broad range of route options needs to be explored, could thus significantly benefit from support given by automated IT tools. Boat chartering offers more flexibility to explore different regions from year to year, but this means that significantly more time must be spent planning the route, since local experience is absent. Due to the global financial crisis, yacht ownership has declined, but demand for such holiday products remained steady, therefore shifting the yachters profile towards younger and less experienced consumers who prefer to charter boats, rather than own one. Sailing holiday activities represent a significant portion of the Blue Economy growth in Europe and across the world. ![]()
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