Dr. Daoqin Tong will give an invited talk titled, "Distance in spatial analysis: Challenges related to spatial data aggregation, scale, and computation". She is an Associate in the School of Geographical Sciences and Urban Planning at Arizona State University.

Event Date and Time: Tuesday, February, 2021 - 3:30 - 4:30 pm

Location: Zoom Webinar

Abstract

Distance is one of the most critical concepts in geography and has been widely used to quantify spatial separation between geographical entities. While measuring the distance between two points is straightforward, assessing the spatial separation between non-point objects can be challenging. This study investigates distance measurement between a location (point) and an area (polygon). We find that traditional polygon-to-point distance measurements, which often involve abstracting a polygon into a central or representative point, could be problematic and may lead to biased estimates in regression analysis. To solve this issue, we propose a new polygon-to-point distance metric. In addition, we introduce three methods to compute the new distance metric efficiently. Simulation analysis shows the effectiveness of the new distance metric in providing unbiased estimates in linear regression. 

Please Register Here: bit.ly/385E3KI