Estimation of Important Scenic Beauty Covariates from Remotely Sensed Data

Simple item page
dc.contributor.authorBlinn, Christine Elizabethen
dc.contributor.committeecochairWynne, Randolph H.en
dc.contributor.committeecochairBuhyoff, Gregory J.en
dc.contributor.committeememberHull, Robert Bruce IVen
dc.contributor.departmentForestryen
dc.date.accessioned2014-03-14T20:40:15Zen
dc.date.adate2000-06-26en
dc.date.available2014-03-14T20:40:15Zen
dc.date.issued2000-06-13en
dc.date.rdate2001-06-26en
dc.date.sdate2000-06-20en
dc.description.abstractThe 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.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-06202000-11050038en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-06202000-11050038/en
dc.identifier.urihttp://hdl.handle.net/10919/33656en
dc.publisherVirginia Techen
dc.relation.haspartBlinnETD.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectScenic Beautyen
dc.subjectForest Measurementsen
dc.subjectAerial Photographyen
dc.subjectRemote Sensingen
dc.titleEstimation of Important Scenic Beauty Covariates from Remotely Sensed Dataen
dc.typeThesisen
thesis.degree.disciplineForestryen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
BlinnETD.pdf
Size:
1.32 MB
Format:
Adobe Portable Document Format
Download

Collections

Masters Theses