Community and Regional Planning Program

 

Date of this Version

Spring 5-2015

Comments

A Thesis Presented to the Faculty of The Graduate College at the University of Nebraska in Partial Fulfillment of Requirements For the Degree of Master of Community and Regional Planning, Major: Community and Regional Planning, under the Supervision of Professor Zhenghong Tang. Lincoln, Nebraska: May, 2015.

Copyright 2015 Richard Wagner Figueroa Alfaro.

Abstract

Ecosystems and human beings are inter-related. People receive benefits from ecosystems named Ecosystem Services such as provisioning, regulating, supporting, and cultural services. Aesthetic value from cultural services is the interaction of people with the environment related to natural beauty. Over the time, traditional approaches for evaluating aesthetic value have been developed.

The main goal of this thesis was to evaluate the aesthetic value in Nebraska by using social media data from Panoramio and Flickr since they became a huge source of information available for multiple uses. We analyzed the clusters of pictures with the location of potential areas of aesthetic value in Nebraska, discovered new areas with aesthetic value, and compared to the population.

We used the Application Programming Interface (API) to obtain the latitude and longitude of the photographs and analyzed using ArcGIS Spatial Statistical tools. Then, we overlapped them with areas of potential aesthetic value: natural landmarks, biologically unique landscapes, state parks, national parks, national forests and grasslands, national wildlife refuges, and surface water bodies. Also, we compared them to population.

Finally, we identified hot spots and cold spots of clusters in the north, west, and southeast parts of Nebraska; areas of study have a direct relationship with the hotspots; there are three new areas with aesthetic values; and there was not a strong statistically significant relationship between the clusters and population. Also, we stated some implications to Planning, research limitations, and future research areas.

Advisor: Zhenghong Tang

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