{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/53850"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/53850","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Policy capturing with the use of visual stimuli: a method of quantifying the determinants of landscape preference","abstract":"Policy Capturing, a potential methodology for evaluating landscape preference, was described and tested. This methodology, tested and applied in industrial psychology since 1960, results in a mathematical model that theoretically represents the human decision-making process. Under experimental conditions, judges were asked to express their preferences for scenes of the Blue Ridge Parkway (Virginia and North Carolina). A multivariate linear model simulating each judge's decision was computed by regressing landscape preferences onto 10 dimensions thought to influence such preferences. An equation which \"captures,\" or defines the policy of each judge was generated. Individual equations were then clustered and a composite strategy calculated at each step until one overall policy was obtained. Coefficients of determination (R²'s) for some individuals were generally large (>0.50). However, composite R²'s were fairly low (<0.25). Methodological problems concerning the use of policy capturing for landscape assessment along with practical management applications are discussed.","abstract_html":"Policy Capturing, a potential methodology for evaluating landscape preference, was described and tested. This methodology, tested and applied in industrial psychology since 1960, results in a mathematical model that theoretically represents the human decision-making process. Under experimental conditions, judges were asked to express their preferences for scenes of the Blue Ridge Parkway (Virginia and North Carolina). A multivariate linear model simulating each judge&#x27;s decision was computed by regressing landscape preferences onto 10 dimensions thought to influence such preferences. An equation which &quot;captures,&quot; or defines the policy of each judge was generated. Individual equations were then clustered and a composite strategy calculated at each step until one overall policy was obtained. Coefficients of determination (R²&#x27;s) for some individuals were generally large (&gt;0.50). However, composite R²&#x27;s were fairly low (&lt;0.25). Methodological problems concerning the use of policy capturing for landscape assessment along with practical management applications are discussed.","abstract_has_math":false,"creators":["Propst, Dennis B."],"institution":"Virginia Polytechnic Institute and State University","degree_name":"Ph. D.","degree_level":"doctoral","degree_discipline":"Forestry","degree_department":"Forestry","school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1979,"date_issued":"1979","date_published":"1979","updated_at":"2026-07-22T22:18:47Z","subjects":[],"languages":["en_US"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10919/53850","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.department","label":"Department","values":["Forestry"]},{"key":"dc:creator","label":"Author","values":["Propst, Dennis B."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2015-06-29T22:06:51Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2015-06-29T22:06:51Z"]},{"key":"dc:date.issued","label":"Date","values":["1979"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Polytechnic Institute and State University"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]},{"key":"dc:type.dcmitype","label":"Dc Type Dcmitype","values":["Text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Forestry"]},{"key":"thesis:degree_level","label":"Degree Level","values":["doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph. 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Under experimental conditions, judges were asked to express their preferences for scenes of the Blue Ridge Parkway (Virginia and North Carolina). A multivariate linear model simulating each judge's decision was computed by regressing landscape preferences onto 10 dimensions thought to influence such preferences. An equation which \"captures,\" or defines the policy of each judge was generated. Individual equations were then clustered and a composite strategy calculated at each step until one overall policy was obtained. Coefficients of determination (R²'s) for some individuals were generally large (>0.50). However, composite R²'s were fairly low (<0.25). Methodological problems concerning the use of policy capturing for landscape assessment along with practical management applications are discussed."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph. 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A multivariate linear model simulating each judge's decision was computed by regressing landscape preferences onto 10 dimensions thought to influence such preferences. An equation which \"captures,\" or defines the policy of each judge was generated. Individual equations were then clustered and a composite strategy calculated at each step until one overall policy was obtained. Coefficients of determination (R²'s) for some individuals were generally large (>0.50). However, composite R²'s were fairly low (<0.25). Methodological problems concerning the use of policy capturing for landscape assessment along with practical management applications are discussed."],"dc:description.degree":["Ph. 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