{"id":{"repo_id":"sdstate","oai_identifier":"oai:openprairie.sdstate.edu:etd-2078"},"canonical_url":"https://search.dev.ndltd.org/etd/sdstate/oai:openprairie.sdstate.edu:etd-2078","repository":{"repo_id":"sdstate","name":"South Dakota State University","base_url":"https://openprairie.sdstate.edu/do/oai/"},"display":{"title":"Fire Type Classification in the Brazilian Tropical Moist Forest Biome","abstract":"<p>The Brazilian Tropical Moist Forest Biome (BTMFB) is “<em>Earth’s greatest biological treasure and a major component of the earth system</em>” and forest degradation and deforestation by fire is a serious issue in this region. Fires in the BTMFB can be broadly classified as maintenance, deforestation and forest fire types. Spatially and temporally explicit information on the incidences of fire types are important as they have widely varying atmospheric emissions and ecological impacts. Satellite based remote sensing is a practical means of monitoring the BTMFB that spans almost 4 million km2. However, there has been no way to reliably classify satellite active fire type to date. In this work, methods to characterize MODIS active fire detections are developed using physically based and geographic context/proximity approaches. The research methodology is developed by addressing four hypotheses concerning differences among active fire type characteristics including factors that drive and mediate fire in the BTMFB. Differences in the active fire characteristics among different fire types are presented and discussed. The spatio-temporal distribution of fire types over 8 year (2003-2010) period is documented, analyzed and presented. This dissertation has, to date, resulted in one published, one in press, and one submitted paper.</p>","abstract_html":"&lt;p&gt;The Brazilian Tropical Moist Forest Biome (BTMFB) is “&lt;em&gt;Earth’s greatest biological treasure and a major component of the earth system&lt;/em&gt;” and forest degradation and deforestation by fire is a serious issue in this region. Fires in the BTMFB can be broadly classified as maintenance, deforestation and forest fire types. Spatially and temporally explicit information on the incidences of fire types are important as they have widely varying atmospheric emissions and ecological impacts. Satellite based remote sensing is a practical means of monitoring the BTMFB that spans almost 4 million km2. However, there has been no way to reliably classify satellite active fire type to date. In this work, methods to characterize MODIS active fire detections are developed using physically based and geographic context/proximity approaches. The research methodology is developed by addressing four hypotheses concerning differences among active fire type characteristics including factors that drive and mediate fire in the BTMFB. Differences in the active fire characteristics among different fire types are presented and discussed. The spatio-temporal distribution of fire types over 8 year (2003-2010) period is documented, analyzed and presented. This dissertation has, to date, resulted in one published, one in press, and one submitted paper.&lt;/p&gt;","abstract_has_math":false,"creators":["Sathyachandran, Sanath Kumar"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation - Open Access","degree_discipline":"Geospatial Science and Engineering","degree_department":null,"school":null,"contributors":["David P. Roy"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-01-01T08:00:00Z","date_published":"2014-01-01T08:00:00Z","updated_at":"2026-07-24T04:28:36Z","subjects":["Forest Sciences","Geographic Information Sciences","Physical and Environmental Geography"],"languages":["en"],"rights":["Copyright © 2014 Sanath Kumar Sathyachandran"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://openprairie.sdstate.edu/etd/1078","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["David P. 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Fires in the BTMFB can be broadly classified as maintenance, deforestation and forest fire types. Spatially and temporally explicit information on the incidences of fire types are important as they have widely varying atmospheric emissions and ecological impacts. Satellite based remote sensing is a practical means of monitoring the BTMFB that spans almost 4 million km2. However, there has been no way to reliably classify satellite active fire type to date. In this work, methods to characterize MODIS active fire detections are developed using physically based and geographic context/proximity approaches. The research methodology is developed by addressing four hypotheses concerning differences among active fire type characteristics including factors that drive and mediate fire in the BTMFB. Differences in the active fire characteristics among different fire types are presented and discussed. The spatio-temporal distribution of fire types over 8 year (2003-2010) period is documented, analyzed and presented. This dissertation has, to date, resulted in one published, one in press, and one submitted paper.</p>"]},{"key":"dc:title","label":"Title","values":["Fire Type Classification in the Brazilian Tropical Moist Forest Biome"]}]}],"canonical_facts":{"dc:contributor":["David P. Roy"],"dc:creator":["Sathyachandran, Sanath Kumar"],"dc:date.available":["2016-10-07T07:00:00Z"],"dc:description.abstract":["<p>The Brazilian Tropical Moist Forest Biome (BTMFB) is “<em>Earth’s greatest biological treasure and a major component of the earth system</em>” and forest degradation and deforestation by fire is a serious issue in this region. Fires in the BTMFB can be broadly classified as maintenance, deforestation and forest fire types. Spatially and temporally explicit information on the incidences of fire types are important as they have widely varying atmospheric emissions and ecological impacts. Satellite based remote sensing is a practical means of monitoring the BTMFB that spans almost 4 million km2. However, there has been no way to reliably classify satellite active fire type to date. In this work, methods to characterize MODIS active fire detections are developed using physically based and geographic context/proximity approaches. The research methodology is developed by addressing four hypotheses concerning differences among active fire type characteristics including factors that drive and mediate fire in the BTMFB. Differences in the active fire characteristics among different fire types are presented and discussed. The spatio-temporal distribution of fire types over 8 year (2003-2010) period is documented, analyzed and presented. 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