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Virginia Tech

Estimation of Important Scenic Beauty Covariates from Remotely Sensed Data

Abstract

dc:description.abstract

The overall objective of this study was to determine if remotely sensed data could be used to model scenic beauty. Terrestrial digital images from within forest stands located in Prince Edward Gallion State Forest near Farmville, Virginia were rated for their scenic beauty by a group of students to obtain scenic beauty estimates (SBEs). Since the inter-rater reliability was low for the SBEs, they were not used in the modeling efforts. Instead, stand parameters (collected on tenth acre plots) that have been used in scenic beauty prediction models, like mean diameter at breast height (dbh), were the dependent variables in regression analyses. A color-infrared aerial photograph from the National Aerial Photography Program (NAPP) was scanned to achieve a pixel ground resolution of one meter. The digital aerial photograph was rectified and used as the remotely sensed data. Since the aerial photograph was taken in April, only conifer stands were used in the analyses. Summary statistics were obtained from a 23 by 23 window around plot locations in three images: the original image, a texture image created with the variance algorithm and a 7x7 window, and the first principal component image. The summary statistics were used as the independent variables in regression analyses. The mean texture digital number for the green band predicted the mean dbh of a plot with an R2 of 0.623. A maximum of 44.3 and 27.4 percent of the variability in trees per acre and basal area per acre, respectively, was explained by the models developed in this study. It seems unlikely that the remotely sensed forest stand variables would perform well as surrogates for field measurements used in scenic quality models.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Forestry
Department dc:contributor.department
Forestry
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2000

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Blinn, Christine Elizabeth
Chairs dc:contributor.committeechair
  • Wynne, Randolph H.
  • Buhyoff, Gregory J.
Committee member dc:contributor.committeemember
  • Hull, Robert Bruce IV

Subjects

dc:subject × 4

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
etd-06202000-11050038
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/33656

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Blinn, Christine Elizabeth. Estimation of Important Scenic Beauty Covariates from Remotely Sensed Data. masters thesis, Virginia Tech, 2000. http://hdl.handle.net/10919/33656