{"id":{"repo_id":"missouri","oai_identifier":"oai:mospace.umsystem.edu:10355/33171"},"canonical_url":"https://search.dev.ndltd.org/etd/missouri/oai:mospace.umsystem.edu:10355/33171","repository":{"repo_id":"missouri","name":"University of Missouri","base_url":"https://mospace.umsystem.edu/oai/request"},"display":{"title":"Biomass assessment in the U.S. midwest using MODIS time-series","abstract":"Bioenergy becomes the largest source of renewable energy in the United States. Switchgrass, a type a Warm Season Grasses, has been regarded as alternative resources instead of annual crops for obtaining the bioenergy. The study is to delineate annual crops and perennial crops (Warm-Season Grasses and Cool-Season Grasses) in the U.S. Midwest based on MODIS time-series products and Cropland Data Layers (CDL) from 2000 to 2009. In addition, this study is to extract WSG biomass proximity by integral NDVI. Besides, based on Multiple Linear Regression, this study aims to identify the sensitive environmental factors that affect distributions of WSG. Major findings include: (1) the classification maps are relatively good for annual and perennial crops in the U.S. Midwest from 2000 to 2009. (2) In the U.S. Midwest, WSG biomass proximity of western states is lower than eastern states. (3) The precipitation in May shows dominantly higher influence on WSG biomass. Temperatures in April, June, and September have positive effects on WSG growth. However, temperatures in May and July have negative effects on WSG biomass. Land Capability Class of soil is less a control to WSG biomass than climate factors.","abstract_html":"Bioenergy becomes the largest source of renewable energy in the United States. Switchgrass, a type a Warm Season Grasses, has been regarded as alternative resources instead of annual crops for obtaining the bioenergy. The study is to delineate annual crops and perennial crops (Warm-Season Grasses and Cool-Season Grasses) in the U.S. Midwest based on MODIS time-series products and Cropland Data Layers (CDL) from 2000 to 2009. In addition, this study is to extract WSG biomass proximity by integral NDVI. Besides, based on Multiple Linear Regression, this study aims to identify the sensitive environmental factors that affect distributions of WSG. Major findings include: (1) the classification maps are relatively good for annual and perennial crops in the U.S. Midwest from 2000 to 2009. (2) In the U.S. Midwest, WSG biomass proximity of western states is lower than eastern states. (3) The precipitation in May shows dominantly higher influence on WSG biomass. Temperatures in April, June, and September have positive effects on WSG growth. However, temperatures in May and July have negative effects on WSG biomass. Land Capability Class of soil is less a control to WSG biomass than climate factors.","abstract_has_math":false,"creators":["Zhang, Wei, M.A."],"institution":"University of Missouri--Columbia","degree_name":"M.A.","degree_level":"Masters","degree_discipline":"Geography (MU)","degree_department":null,"school":null,"contributors":[],"advisors":["Wang, Cuizhen"],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012","date_published":"2012","updated_at":"2026-07-24T03:07:35Z","subjects":["bioenergy","warm-season grasses","environmental factors"],"languages":["eng","English"],"rights":["OpenAccess."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10355/33171","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Wang, Cuizhen"]},{"key":"dc:creator","label":"Author","values":["Zhang, Wei, M.A."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2013-03-11T14:46:27Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2013-03-11T14:46:27Z"]},{"key":"dc:date.issued","label":"Date","values":["2012"]},{"key":"dc:publisher","label":"Institution","values":["University of Missouri--Columbia"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Geography (MU)"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.A."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Missouri--Columbia"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["bioenergy","warm-season grasses","environmental factors"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]},{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["OpenAccess."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10355/33171"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Title from PDF of title page (University of Missouri--Columbia, viewed on March 11, 2013).","The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.","Thesis advisor: Dr. Cuizhen Wang","Includes bibliographical references.","M.A. University of Missouri--Columbia 2012.","\"December 2012\""]},{"key":"dc:description.abstract","label":"Abstract","values":["Bioenergy becomes the largest source of renewable energy in the United States. Switchgrass, a type a Warm Season Grasses, has been regarded as alternative resources instead of annual crops for obtaining the bioenergy. The study is to delineate annual crops and perennial crops (Warm-Season Grasses and Cool-Season Grasses) in the U.S. Midwest based on MODIS time-series products and Cropland Data Layers (CDL) from 2000 to 2009. In addition, this study is to extract WSG biomass proximity by integral NDVI. Besides, based on Multiple Linear Regression, this study aims to identify the sensitive environmental factors that affect distributions of WSG. Major findings include: (1) the classification maps are relatively good for annual and perennial crops in the U.S. Midwest from 2000 to 2009. (2) In the U.S. Midwest, WSG biomass proximity of western states is lower than eastern states. (3) The precipitation in May shows dominantly higher influence on WSG biomass. Temperatures in April, June, and September have positive effects on WSG growth. However, temperatures in May and July have negative effects on WSG biomass. Land Capability Class of soil is less a control to WSG biomass than climate factors."]},{"key":"dc:title","label":"Title","values":["Biomass assessment in the U.S. midwest using MODIS time-series"]}]}],"canonical_facts":{"dc:contributor.advisor":["Wang, Cuizhen"],"dc:creator":["Zhang, Wei, M.A."],"dc:date.accessioned":["2013-03-11T14:46:27Z"],"dc:date.available":["2013-03-11T14:46:27Z"],"dc:date.issued":["2012"],"dc:description":["Title from PDF of title page (University of Missouri--Columbia, viewed on March 11, 2013).","The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.","Thesis advisor: Dr. Cuizhen Wang","Includes bibliographical references.","M.A. University of Missouri--Columbia 2012.","\"December 2012\""],"dc:description.abstract":["Bioenergy becomes the largest source of renewable energy in the United States. Switchgrass, a type a Warm Season Grasses, has been regarded as alternative resources instead of annual crops for obtaining the bioenergy. The study is to delineate annual crops and perennial crops (Warm-Season Grasses and Cool-Season Grasses) in the U.S. Midwest based on MODIS time-series products and Cropland Data Layers (CDL) from 2000 to 2009. In addition, this study is to extract WSG biomass proximity by integral NDVI. Besides, based on Multiple Linear Regression, this study aims to identify the sensitive environmental factors that affect distributions of WSG. Major findings include: (1) the classification maps are relatively good for annual and perennial crops in the U.S. Midwest from 2000 to 2009. (2) In the U.S. Midwest, WSG biomass proximity of western states is lower than eastern states. (3) The precipitation in May shows dominantly higher influence on WSG biomass. Temperatures in April, June, and September have positive effects on WSG growth. However, temperatures in May and July have negative effects on WSG biomass. Land Capability Class of soil is less a control to WSG biomass than climate factors."],"dc:identifier.uri":["http://hdl.handle.net/10355/33171"],"dc:language":["English"],"dc:language.iso":["eng"],"dc:publisher":["University of Missouri--Columbia"],"dc:rights":["OpenAccess."],"dc:subject":["bioenergy","warm-season grasses","environmental factors"],"dc:title":["Biomass assessment in the U.S. midwest using MODIS time-series"],"dc:type":["Thesis"],"thesis:degree_discipline":["Geography (MU)"],"thesis:degree_level":["Masters"],"thesis:degree_name":["M.A."],"thesis:institution_name":["University of Missouri--Columbia"]},"updated_at":"2026-07-24T03:07:35Z"}