Predicting Damages to Remainder Parcels in Right-of-Way Acquisitions for Expanding Transportation Infrastructure: Using a Truncated Finite-Mixture Model

Abstract

Right-of-way acquisition is a critical component of transportation infrastructure development. Transportation infrastructure projects cannot proceed without proper right-of-way acquisition or may face significant delays. State Departments of Transportation frequently acquire parcels of land for roadway expansion projects. A majority of these acquisitions can be partial takings, referring to a portion of a parcel that is acquired. The remainder of the property usually suffers economic changes due to the partial acquisition, which can be calculated as damage percentages. The damage percentage represents the extent to which the remaining land or property value has been diminished due to the acquisition. It reflects the remaining property value percentage that may have been lost or compromised due to the acquisition. This study aims to provide a robust model to estimate damage percentages to the remainder parcels that may help state Departments of Transportation appraisers make early predictions about the damages in cases involving partial takings. The research uses 509 appraisal reports from the Tennessee Department of Transportation to identify the key parcel attributes that influence the percentage of damages. Three regression models are developed: a linear regression model, a finite-mixture model (FMM), and a truncated FMM with two latent classes. The modeling results show that the truncated FMM with two classes outperforms the other models. To validate the models, actual sales data is collected and analyzed for 59 properties, and the results suggest that the model predictions are fairly accurate. A predictive tool is developed based on the models to help appraisers anticipate right-of-way damages under different scenarios and can provide early predictions about the damages. A predictive tool called Right-of-Way Damage Assessment (ROWDA) is developed, which can utilize the coefficients of the linear regression model or the truncated finite-mixture model (FMM) based on the user’s preference. The tool can allow state departments of transportation (DOTs) to anticipate right-of-way damages/costs under varying conditions. This tool is created to assess and study inputs from right-of-way acquisitions to determine the estimated percentage of damage. ROWDA provides DOT appraisals to check the cases where the estimations may be out of range. This Microsoft Excel Macro tool serves as a link between a group of attributes and regression equations. It allows the user to input multiple parcel characteristics and compute a prediction of the estimated damage percentage. All user inputs are saved in the worksheet within the workbook on which the tool is based. The tool boasts numerous potential applications, one of which involves estimating damages prior to initiating a project, even before comprehensive appraisals are conducted. Consequently, the tool aids in evaluating project feasibility, considering adjustments in the project’s execution, and recognizing damage estimations from actual appraisals that deviate from previous assessments utilized to create the model’s predictions.