Abstract

Modeling municipal or urban decisions is challenging due to the abundance of variables that guide end results. One such challenging issue is the existence of vacant lots in a city, which causes poorer standard of living for the community. As a result, reclaiming these properties and putting them into productive use is a primary concern. However, each time community leaders had to ``reinvent the wheel'' and make decisions from scratch. To this end, we propose the creation of a vacant lot model and utilizing it to provide recommendations for vacant lot conversions, providing a starting point for such decision making. We define a vacant lot model in terms of determinants to a vacant lot's impact, and evaluate the proposed method on real-world vacant lot datasets from the cities of Philadelphia, Pennsylvania and Baltimore, Maryland. Our results indicate that our prediction model performs accurately on cities with a centralized approach to vacant lot conversion.

Library of Congress Subject Headings

Vacant lands--Data processing; Decision making--Data processing; Machine learning

Publication Date

5-2017

Document Type

Thesis

Student Type

Graduate

Degree Name

Software Engineering (MS)

Department, Program, or Center

Software Engineering (GCCIS)

Advisor

Naveen Sharma

Advisor/Committee Member

Pradeep Murukannaiah

Advisor/Committee Member

Scott Hawker

Comments

Physical copy available from RIT's Wallace Library at TD657.5 .C46 2017

Campus

RIT – Main Campus

Plan Codes

SOFTENG-MS

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