{"title":"基于3D-GIS的深圳房价指数系统的设计与实现","authors":"Nianlong Han, Wei Zhang, Kai Liang","doi":"10.1109/GEOINFORMATICS.2015.7378676","DOIUrl":null,"url":null,"abstract":"Shenzhen is one of cities that is real estate market-oriented, and the real estate is an important industry in the economic development. Real estate price statistics have drawn more and more attention and is being questioned due to distortion of announced real estate price in recent years. For example, the new commercial house price statistics is measured by using a simple average of price statistics, but the sample's heterogeneity leads to the house prices by statistics inconsistent with the real house prices. Meanwhile, in the process of second-hand housing transactions, the transaction prices is distortion and real house prices are out of control, caused by fake contracts. In order to grasp changes and trends of the price in the real estate market accurately, this research designs a house price indexes model, which covers new and secondary house in Shenzhen based on the real estate database. The Shenzhen house price indexes system employs B/S and three-layer architecture. It is based on the Skyline platform, and utilizes the JavaScript language for secondary development. The Shenzhen house price indexes system can effectively integrate real estate data, spatial data, 3D simulation model and house price indexes model, which achieves to monitor, manage, and analyze real estate data, and house price indexes. The system prepares and publishes periodic house price indexes, which could provide the latest, timeliest, and most accurate real estate price information for the parties in the real estate market.","PeriodicalId":371399,"journal":{"name":"2015 23rd International Conference on Geoinformatics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The design and implementation of Shenzhen house price indexes system based on 3D-GIS\",\"authors\":\"Nianlong Han, Wei Zhang, Kai Liang\",\"doi\":\"10.1109/GEOINFORMATICS.2015.7378676\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Shenzhen is one of cities that is real estate market-oriented, and the real estate is an important industry in the economic development. Real estate price statistics have drawn more and more attention and is being questioned due to distortion of announced real estate price in recent years. For example, the new commercial house price statistics is measured by using a simple average of price statistics, but the sample's heterogeneity leads to the house prices by statistics inconsistent with the real house prices. Meanwhile, in the process of second-hand housing transactions, the transaction prices is distortion and real house prices are out of control, caused by fake contracts. In order to grasp changes and trends of the price in the real estate market accurately, this research designs a house price indexes model, which covers new and secondary house in Shenzhen based on the real estate database. The Shenzhen house price indexes system employs B/S and three-layer architecture. It is based on the Skyline platform, and utilizes the JavaScript language for secondary development. The Shenzhen house price indexes system can effectively integrate real estate data, spatial data, 3D simulation model and house price indexes model, which achieves to monitor, manage, and analyze real estate data, and house price indexes. The system prepares and publishes periodic house price indexes, which could provide the latest, timeliest, and most accurate real estate price information for the parties in the real estate market.\",\"PeriodicalId\":371399,\"journal\":{\"name\":\"2015 23rd International Conference on Geoinformatics\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 23rd International Conference on Geoinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GEOINFORMATICS.2015.7378676\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 23rd International Conference on Geoinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GEOINFORMATICS.2015.7378676","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The design and implementation of Shenzhen house price indexes system based on 3D-GIS
Shenzhen is one of cities that is real estate market-oriented, and the real estate is an important industry in the economic development. Real estate price statistics have drawn more and more attention and is being questioned due to distortion of announced real estate price in recent years. For example, the new commercial house price statistics is measured by using a simple average of price statistics, but the sample's heterogeneity leads to the house prices by statistics inconsistent with the real house prices. Meanwhile, in the process of second-hand housing transactions, the transaction prices is distortion and real house prices are out of control, caused by fake contracts. In order to grasp changes and trends of the price in the real estate market accurately, this research designs a house price indexes model, which covers new and secondary house in Shenzhen based on the real estate database. The Shenzhen house price indexes system employs B/S and three-layer architecture. It is based on the Skyline platform, and utilizes the JavaScript language for secondary development. The Shenzhen house price indexes system can effectively integrate real estate data, spatial data, 3D simulation model and house price indexes model, which achieves to monitor, manage, and analyze real estate data, and house price indexes. The system prepares and publishes periodic house price indexes, which could provide the latest, timeliest, and most accurate real estate price information for the parties in the real estate market.