{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/35738"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/35738","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Multispectral Imaging Techniques for Monitoring Vegetative Growth and Health","abstract":"Electromagnetic radiation reflectance increases dramatically around 700 nm for vegetation. This increase in reflectance is known as the vegetation red edge. The NDVI (Normalized Difference Vegetation index) is an imaging technique for quantifying red edge contrast for the identification of vegetation. This imaging technique relies on reflectance values for radiation with wavelength equal to 680 nm and 830 nm. The imaging systems required to obtain this precise reflectance data are commonly space-based; limiting the use of this technique due to satellite availability and cost. This thesis presents a robust and inexpensive new terrestrial-based method for identifying the vegetation red edge. This new technique does not rely on precise wavelengths or narrow wavelength bands and instead applies the NDVI to the visible and NIR (near infrared) spectrums in toto. The measurement of vegetation fluorescence has also been explored, as it is indirectly related to the efficiency of photochemistry and heat dissipation and provides a relative method for determining vegetation health. The imaging methods presented in this thesis represent a unique solution for the real time monitoring of vegetation growth and senesces and the determination of qualitative vegetation health. A single, inexpensive system capable of field and greenhouse deployment has been developed. This system allows for the early detection of variations in plant growth and status, which will aid production of high quality horticultural crops.","abstract_html":"Electromagnetic radiation reflectance increases dramatically around 700 nm for vegetation. This increase in reflectance is known as the vegetation red edge. The NDVI (Normalized Difference Vegetation index) is an imaging technique for quantifying red edge contrast for the identification of vegetation. This imaging technique relies on reflectance values for radiation with wavelength equal to 680 nm and 830 nm. The imaging systems required to obtain this precise reflectance data are commonly space-based; limiting the use of this technique due to satellite availability and cost. This thesis presents a robust and inexpensive new terrestrial-based method for identifying the vegetation red edge. This new technique does not rely on precise wavelengths or narrow wavelength bands and instead applies the NDVI to the visible and NIR (near infrared) spectrums in toto. The measurement of vegetation fluorescence has also been explored, as it is indirectly related to the efficiency of photochemistry and heat dissipation and provides a relative method for determining vegetation health. The imaging methods presented in this thesis represent a unique solution for the real time monitoring of vegetation growth and senesces and the determination of qualitative vegetation health. A single, inexpensive system capable of field and greenhouse deployment has been developed. This system allows for the early detection of variations in plant growth and status, which will aid production of high quality horticultural crops.","abstract_has_math":false,"creators":["Weekley, Jonathan Gardner"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Mechanical Engineering","degree_department":"Mechanical Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Wicks, Alfred L.","Reinholtz, Charles F."],"committee_members":["Nowak, Jerzy","Meehan, Kathleen"],"year":2007,"date_issued":"2007-12-04","date_published":"2007-12-04","updated_at":"2026-07-22T22:19:31Z","subjects":["Multispectral Imaging","Hyperspectral Imaging","Computer Vision","NDVI"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-11172008-144208"],"render_values":[{"text":"etd-11172008-144208","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/35738","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Wicks, Alfred L.","Reinholtz, Charles F."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Nowak, Jerzy","Meehan, Kathleen"]},{"key":"dc:contributor.department","label":"Department","values":["Mechanical Engineering"]},{"key":"dc:creator","label":"Author","values":["Weekley, Jonathan Gardner"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-14T20:48:03Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-03-14T20:48:03Z","2009-01-12"]},{"key":"dc:date.issued","label":"Date","values":["2007-12-04"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"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":["Multispectral Imaging","Hyperspectral Imaging","Computer Vision","NDVI"]}]},{"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":["etd-11172008-144208"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/35738"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Electromagnetic radiation reflectance increases dramatically around 700 nm for vegetation. This increase in reflectance is known as the vegetation red edge. The NDVI (Normalized Difference Vegetation index) is an imaging technique for quantifying red edge contrast for the identification of vegetation. This imaging technique relies on reflectance values for radiation with wavelength equal to 680 nm and 830 nm. The imaging systems required to obtain this precise reflectance data are commonly space-based; limiting the use of this technique due to satellite availability and cost. This thesis presents a robust and inexpensive new terrestrial-based method for identifying the vegetation red edge. This new technique does not rely on precise wavelengths or narrow wavelength bands and instead applies the NDVI to the visible and NIR (near infrared) spectrums in toto. The measurement of vegetation fluorescence has also been explored, as it is indirectly related to the efficiency of photochemistry and heat dissipation and provides a relative method for determining vegetation health. The imaging methods presented in this thesis represent a unique solution for the real time monitoring of vegetation growth and senesces and the determination of qualitative vegetation health. A single, inexpensive system capable of field and greenhouse deployment has been developed. This system allows for the early detection of variations in plant growth and status, which will aid production of high quality horticultural crops."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:title","label":"Title","values":["Multispectral Imaging Techniques for Monitoring Vegetative Growth and Health"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Wicks, Alfred L.","Reinholtz, Charles F."],"dc:contributor.committeemember":["Nowak, Jerzy","Meehan, Kathleen"],"dc:contributor.department":["Mechanical Engineering"],"dc:creator":["Weekley, Jonathan Gardner"],"dc:date.accessioned":["2014-03-14T20:48:03Z"],"dc:date.available":["2014-03-14T20:48:03Z","2009-01-12"],"dc:date.issued":["2007-12-04"],"dc:description.abstract":["Electromagnetic radiation reflectance increases dramatically around 700 nm for vegetation. This increase in reflectance is known as the vegetation red edge. 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The imaging methods presented in this thesis represent a unique solution for the real time monitoring of vegetation growth and senesces and the determination of qualitative vegetation health. A single, inexpensive system capable of field and greenhouse deployment has been developed. 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