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挖掘房地产市场的见解:整合地理空间数据以进行全面的房产估值和城市规划。

Unlocking insights in real estate markets: Integrating geo-spatial data for comprehensive property valuation and urban planning.

作者信息

Varol Serkan, Catma Serkan

机构信息

Engineering Management and Technology Department, Serkan Varol, University of Tennessee at Chattanooga, TN 37403, USA.

Department of Business Administration, Serkan Catma, University of South Carolina Beaufort, Bluffton, SC 29910, USA.

出版信息

Data Brief. 2024 Nov 17;57:111141. doi: 10.1016/j.dib.2024.111141. eCollection 2024 Dec.

Abstract

This article summarizes a database for analyzing the impact of structural and environmental characteristics on residential property values in Hamilton County, TN. The original dataset consists of house characteristics data for 873 residential sales between January 1, 2023, and September 25, 2023. Using Google's API tools and Point to Edge computations, several geographical variables-including the distance to green recreational areas, surrounding facilities, restaurants, air quality index, walk score-were gathered. The aggregated information can help forecast Hamilton County's housing market with accuracy and correctly assess the environmental impact on housing prices. More specifically, the value of any environmental amenity in the study area can be implicitly estimated using this dataset.

摘要

本文总结了一个用于分析田纳西州汉密尔顿县结构和环境特征对住宅物业价值影响的数据库。原始数据集包含2023年1月1日至2023年9月25日期间873笔住宅销售的房屋特征数据。利用谷歌的应用程序编程接口工具和点到边计算,收集了几个地理变量,包括到绿色休闲区的距离、周边设施、餐厅、空气质量指数、步行得分。汇总后的信息有助于准确预测汉密尔顿县的住房市场,并正确评估环境对房价的影响。更具体地说,使用该数据集可以隐含地估计研究区域内任何环境便利设施的价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62c0/11647156/9be77c1a0d5f/gr1.jpg

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