{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/50439"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/50439","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Forest Change Dynamics Across Levels of Urbanization in the Eastern US","abstract":"The forests of the eastern United States reflect complex and highly dynamic patterns of change. This thesis seeks to explore the highly variable nature of these changes and to develop techniques that will enable researchers to examine their temporal and spatial patterns. The objectives of this research are to: 1) determine whether the forest change dynamics in the eastern US differ across levels of the urban hierarchy; 2) identify and explore key micropolitan areas that deviate from anticipated trends in forest change; and 3) develop and apply techniques for Big Data exploration of Landsat satellite images for forest cover analysis over large regions. Results demonstrate that forest change at the micropolitan level of urbanization differs from rural and metropolitan forest dynamics. The work highlights the dynamic nature of forest change within the Piedmont Atlantic megaregion, largely attributed to the forestry industry. This is by far the most dominant change phenomenon in the region but is not necessarily indicative of permanent forest change. A longer temporal analysis may be required to separate the contribution of the forest industry from permanent forest conversion in the region. Techniques utilized in this work suggest that emerging tools that provide supercomputing/parallel processing capabilities for the analysis of big satellite data open the door for researchers to better address different landscape signals and to investigate large regions at a high temporal and spatial resolution. The opportunity now exists to conduct initial assessments regarding spatio-temporal land cover trends in the southeast in a manner previously not possible.","abstract_html":"The forests of the eastern United States reflect complex and highly dynamic patterns of change. This thesis seeks to explore the highly variable nature of these changes and to develop techniques that will enable researchers to examine their temporal and spatial patterns. The objectives of this research are to: 1) determine whether the forest change dynamics in the eastern US differ across levels of the urban hierarchy; 2) identify and explore key micropolitan areas that deviate from anticipated trends in forest change; and 3) develop and apply techniques for Big Data exploration of Landsat satellite images for forest cover analysis over large regions. Results demonstrate that forest change at the micropolitan level of urbanization differs from rural and metropolitan forest dynamics. The work highlights the dynamic nature of forest change within the Piedmont Atlantic megaregion, largely attributed to the forestry industry. This is by far the most dominant change phenomenon in the region but is not necessarily indicative of permanent forest change. A longer temporal analysis may be required to separate the contribution of the forest industry from permanent forest conversion in the region. Techniques utilized in this work suggest that emerging tools that provide supercomputing/parallel processing capabilities for the analysis of big satellite data open the door for researchers to better address different landscape signals and to investigate large regions at a high temporal and spatial resolution. The opportunity now exists to conduct initial assessments regarding spatio-temporal land cover trends in the southeast in a manner previously not possible.","abstract_has_math":false,"creators":["Wu, Yi-Jei"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Forestry","degree_department":"Forest Resources and Environmental Conservation","school":null,"contributors":[],"advisors":[],"committee_chairs":["Thomas, Valerie A.","Oliver, Robert D."],"committee_members":["McGee, John A.","Sorice, Michael G."],"year":2014,"date_issued":"2014-09-03","date_published":"2014-09-03","updated_at":"2026-07-22T22:20:09Z","subjects":["National Land Cover Database (NLCD)","Landsat","Multitemporal","Change Detection"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:3654"],"render_values":[{"text":"vt_gsexam:3654","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/50439","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Thomas, Valerie A.","Oliver, Robert D."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["McGee, John A.","Sorice, Michael G."]},{"key":"dc:contributor.department","label":"Department","values":["Forest Resources and Environmental Conservation"]},{"key":"dc:creator","label":"Author","values":["Wu, Yi-Jei"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-09-04T08:00:12Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-09-04T08:00:12Z"]},{"key":"dc:date.issued","label":"Date","values":["2014-09-03"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Forestry"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["National Land Cover Database (NLCD)","Landsat","Multitemporal","Change Detection"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:3654"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/50439"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The forests of the eastern United States reflect complex and highly dynamic patterns of change. This thesis seeks to explore the highly variable nature of these changes and to develop techniques that will enable researchers to examine their temporal and spatial patterns. The objectives of this research are to: 1) determine whether the forest change dynamics in the eastern US differ across levels of the urban hierarchy; 2) identify and explore key micropolitan areas that deviate from anticipated trends in forest change; and 3) develop and apply techniques for Big Data exploration of Landsat satellite images for forest cover analysis over large regions. Results demonstrate that forest change at the micropolitan level of urbanization differs from rural and metropolitan forest dynamics. The work highlights the dynamic nature of forest change within the Piedmont Atlantic megaregion, largely attributed to the forestry industry. This is by far the most dominant change phenomenon in the region but is not necessarily indicative of permanent forest change. A longer temporal analysis may be required to separate the contribution of the forest industry from permanent forest conversion in the region. Techniques utilized in this work suggest that emerging tools that provide supercomputing/parallel processing capabilities for the analysis of big satellite data open the door for researchers to better address different landscape signals and to investigate large regions at a high temporal and spatial resolution. The opportunity now exists to conduct initial assessments regarding spatio-temporal land cover trends in the southeast in a manner previously not possible."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["Forest Change Dynamics Across Levels of Urbanization in the Eastern US"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Thomas, Valerie A.","Oliver, Robert D."],"dc:contributor.committeemember":["McGee, John A.","Sorice, Michael G."],"dc:contributor.department":["Forest Resources and Environmental Conservation"],"dc:creator":["Wu, Yi-Jei"],"dc:date.accessioned":["2014-09-04T08:00:12Z"],"dc:date.available":["2014-09-04T08:00:12Z"],"dc:date.issued":["2014-09-03"],"dc:description.abstract":["The forests of the eastern United States reflect complex and highly dynamic patterns of change. This thesis seeks to explore the highly variable nature of these changes and to develop techniques that will enable researchers to examine their temporal and spatial patterns. The objectives of this research are to: 1) determine whether the forest change dynamics in the eastern US differ across levels of the urban hierarchy; 2) identify and explore key micropolitan areas that deviate from anticipated trends in forest change; and 3) develop and apply techniques for Big Data exploration of Landsat satellite images for forest cover analysis over large regions. Results demonstrate that forest change at the micropolitan level of urbanization differs from rural and metropolitan forest dynamics. The work highlights the dynamic nature of forest change within the Piedmont Atlantic megaregion, largely attributed to the forestry industry. This is by far the most dominant change phenomenon in the region but is not necessarily indicative of permanent forest change. A longer temporal analysis may be required to separate the contribution of the forest industry from permanent forest conversion in the region. Techniques utilized in this work suggest that emerging tools that provide supercomputing/parallel processing capabilities for the analysis of big satellite data open the door for researchers to better address different landscape signals and to investigate large regions at a high temporal and spatial resolution. The opportunity now exists to conduct initial assessments regarding spatio-temporal land cover trends in the southeast in a manner previously not possible."],"dc:description.degree":["Master of Science"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:3654"],"dc:identifier.uri":["http://hdl.handle.net/10919/50439"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["National Land Cover Database (NLCD)","Landsat","Multitemporal","Change Detection"],"dc:title":["Forest Change Dynamics Across Levels of Urbanization in the Eastern US"],"dc:type":["Thesis"],"thesis:degree_discipline":["Forestry"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:20:09Z"}