Positional error in automated geocoding of residential addresses.
Positional error in automated geocoding of residential addresses.
复制标题
DOI：
10.1186/1476-072x-2-10
复制
发表时间：
2003-12-19
影响因子：
4.9
通讯作者：
Talbot, Thomas O
中科院分区：
文献类型：
--
作者：
Cayo, Michael R;Talbot, Thomas O
背景：使用地理信息系统（GIS）技术的公共卫生应用正在稳步增长。其中许多依赖于确定人们居住的环境污染物暴露区域的能力。自动地理编码是一种用于根据街道地址为个人分配地理坐标的方法。此方法通常依赖于街道中心线文件作为地理参考。这样的过程在地理编码点中引入位置误差。我们的研究评估了在自动地理编码的住宅地址，以及如何在人口密度之间变化的错误所造成的位置误差。我们还评估了一种使用住宅物业地块数据进行地理编码的替代方法。研究结果：使用每个地理编码点与航空图像确定的真实位置之间的距离来确定3，000个住宅地址的位置误差。发现误差随着人口密度的降低而增加。在纽约北部的一个研究区域的农村地区，95%的地址地理编码在其真实位置的2,872米以内。郊区显示错误较少，其中95%的地址地理编码在421米以内。城市地区显示出最小的错误，其中95%的地址地理编码在其真实位置的152米范围内。作为使用街道中心线文件进行地理编码的替代方法，我们使用住宅物业地块点来定位地址。在农村地区，95%的包裹点位于真实位置的195米范围内。在郊区，这一距离为39米，而在城市地区，95%的宗地点与真实位置的距离在21米以内。结论：研究人员需要确定所选择的地理编码方法引起的误差水平是否会影响他们的项目结果。作为一种替代方法，如果发现传统方法造成的错误不可接受，则可以使用属性数据对地址进行地理编码。
BACKGROUND: Public health applications using geographic information system (GIS) technology are steadily increasing. Many of these rely on the ability to locate where people live with respect to areas of exposure from environmental contaminants. Automated geocoding is a method used to assign geographic coordinates to an individual based on their street address. This method often relies on street centerline files as a geographic reference. Such a process introduces positional error in the geocoded point. Our study evaluated the positional error caused during automated geocoding of residential addresses and how this error varies between population densities. We also evaluated an alternative method of geocoding using residential property parcel data. RESULTS: Positional error was determined for 3,000 residential addresses using the distance between each geocoded point and its true location as determined with aerial imagery. Error was found to increase as population density decreased. In rural areas of an upstate New York study area, 95 percent of the addresses geocoded to within 2,872 m of their true location. Suburban areas revealed less error where 95 percent of the addresses geocoded to within 421 m. Urban areas demonstrated the least error where 95 percent of the addresses geocoded to within 152 m of their true location. As an alternative to using street centerline files for geocoding, we used residential property parcel points to locate the addresses. In the rural areas, 95 percent of the parcel points were within 195 m of the true location. In suburban areas, this distance was 39 m while in urban areas 95 percent of the parcel points were within 21 m of the true location. CONCLUSION: Researchers need to determine if the level of error caused by a chosen method of geocoding may affect the results of their project. As an alternative method, property data can be used for geocoding addresses if the error caused by traditional methods is found to be unacceptable.