{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/99363"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/99363","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Three-dimensional cloud volume reconstruction from the Multi-angle Imaging SpectroRadiometer","abstract":"Clouds continue to contribute the largest uncertainty to estimates and interpretations of the Earth's energy budget, and their representation in climate models has been recognized for decades as a dominant source of uncertainty in climate change projections. It has been suggested that understanding the 3-D structure of cloud would lead to better understanding of the Earth's radiative and latent fluxes. Indeed, knowing cloud 3-D geometry could lead to: 1) improving our understanding of cloud microphysical properties and processes, and 2) improving our knowledge of the radiative effects of cloud on the Earth's energy budget. The Multi-angle Imaging SpectroRadiometer (MISR) is on board the Terra satellite, in its 17th year of operation as of 2017. MISR provides nine views of the same scene that allow scientists to visualize the 3-D structure of observed clouds to a certain extent. Taking advantage of such multi-angle characteristic, this project aims to reconstruct cloud volumes from MISR data. The reconstruction domain is defined such that it takes into account the curvature of the Earth’s ellipsoidal surface. The input satellite images used are the Radiometric Camera-by-camera Cloud Masks at 1.1 km resolution developed by the MISR science team, and custom cloud masks at 275 m resolution developed from MISR RGB images in this project. Due to the time difference between each camera view angle, wind correction is performed on the input cloud masks. For the reconstruction method, “ray casting” algorithms that fully account for the instrument's geometric properties are developed. The reconstruction results are presented for three hand-picked MISR cloud scenes. Strengths and limitations of the reconstruction method are explored, and the outlook for the use of the reconstruction results are discussed.","abstract_html":"Clouds continue to contribute the largest uncertainty to estimates and interpretations of the Earth's energy budget, and their representation in climate models has been recognized for decades as a dominant source of uncertainty in climate change projections. It has been suggested that understanding the 3-D structure of cloud would lead to better understanding of the Earth's radiative and latent fluxes. Indeed, knowing cloud 3-D geometry could lead to: 1) improving our understanding of cloud microphysical properties and processes, and 2) improving our knowledge of the radiative effects of cloud on the Earth's energy budget. The Multi-angle Imaging SpectroRadiometer (MISR) is on board the Terra satellite, in its 17th year of operation as of 2017. MISR provides nine views of the same scene that allow scientists to visualize the 3-D structure of observed clouds to a certain extent. Taking advantage of such multi-angle characteristic, this project aims to reconstruct cloud volumes from MISR data. The reconstruction domain is defined such that it takes into account the curvature of the Earth’s ellipsoidal surface. The input satellite images used are the Radiometric Camera-by-camera Cloud Masks at 1.1 km resolution developed by the MISR science team, and custom cloud masks at 275 m resolution developed from MISR RGB images in this project. Due to the time difference between each camera view angle, wind correction is performed on the input cloud masks. For the reconstruction method, “ray casting” algorithms that fully account for the instrument's geometric properties are developed. The reconstruction results are presented for three hand-picked MISR cloud scenes. Strengths and limitations of the reconstruction method are explored, and the outlook for the use of the reconstruction results are discussed.","abstract_has_math":false,"creators":["Lee, Byungsuk"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Atmospheric Sciences","degree_department":null,"school":null,"contributors":["Di Girolamo, Larry"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-03-13T15:48:54Z","date_published":"2018-03-13T15:48:54Z","updated_at":"2026-07-22T22:24:37Z","subjects":["Cloud volume reconstruction","Ray casting","Remote sensing","Multi-angle Imaging SpectroRadiometer (MISR)"],"languages":["en"],"rights":["Copyright 2017 Byungsuk Lee"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/99363","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Di Girolamo, Larry"]},{"key":"dc:creator","label":"Author","values":["Lee, Byungsuk"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-03-13T15:48:54Z","2017-12-12","2017-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Atmospheric Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Cloud volume reconstruction","Ray casting","Remote sensing","Multi-angle Imaging SpectroRadiometer (MISR)"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2017 Byungsuk Lee"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/99363"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Clouds continue to contribute the largest uncertainty to estimates and interpretations of the Earth's energy budget, and their representation in climate models has been recognized for decades as a dominant source of uncertainty in climate change projections. It has been suggested that understanding the 3-D structure of cloud would lead to better understanding of the Earth's radiative and latent fluxes. Indeed, knowing cloud 3-D geometry could lead to: 1) improving our understanding of cloud microphysical properties and processes, and 2) improving our knowledge of the radiative effects of cloud on the Earth's energy budget. The Multi-angle Imaging SpectroRadiometer (MISR) is on board the Terra satellite, in its 17th year of operation as of 2017. MISR provides nine views of the same scene that allow scientists to visualize the 3-D structure of observed clouds to a certain extent. Taking advantage of such multi-angle characteristic, this project aims to reconstruct cloud volumes from MISR data. The reconstruction domain is defined such that it takes into account the curvature of the Earth’s ellipsoidal surface. The input satellite images used are the Radiometric Camera-by-camera Cloud Masks at 1.1 km resolution developed by the MISR science team, and custom cloud masks at 275 m resolution developed from MISR RGB images in this project. Due to the time difference between each camera view angle, wind correction is performed on the input cloud masks. For the reconstruction method, “ray casting” algorithms that fully account for the instrument's geometric properties are developed. The reconstruction results are presented for three hand-picked MISR cloud scenes. Strengths and limitations of the reconstruction method are explored, and the outlook for the use of the reconstruction results are discussed.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2018-03-13 without embargo terms","The student, Byungsuk Lee, accepted the attached license on 2017-12-11 at 14:33.","The student, Byungsuk Lee, submitted this Thesis for approval on 2017-12-11 at 14:41.","This Thesis was approved for publication on 2017-12-12 at 12:40.","DSpace SAF Submission Ingestion Package generated from Vireo submission #11835 on 2018-03-13 at 10:10:25","Made available in DSpace on 2018-03-13T15:48:54Z (GMT). No. of bitstreams: 3 LEE-THESIS-2017.pdf: 34916146 bytes, checksum: e86fc6a59d5e08fbc7e1c827d66eae08 (MD5) ByungsukLee_MS_ATMS_Thesis_MATLAB_CodeFiles.zip: 93848 bytes, checksum: e623357fb435615372cfe79bb06702f2 (MD5) LICENSE.txt: 4209 bytes, checksum: 4038dcbede73605b405135c981654087 (MD5) Previous issue date: 2017-12-12"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Three-dimensional cloud volume reconstruction from the Multi-angle Imaging SpectroRadiometer"]}]}],"canonical_facts":{"dc:contributor":["Di Girolamo, Larry"],"dc:creator":["Lee, Byungsuk"],"dc:date":["2018-03-13T15:48:54Z","2017-12-12","2017-12"],"dc:description":["Clouds continue to contribute the largest uncertainty to estimates and interpretations of the Earth's energy budget, and their representation in climate models has been recognized for decades as a dominant source of uncertainty in climate change projections. It has been suggested that understanding the 3-D structure of cloud would lead to better understanding of the Earth's radiative and latent fluxes. Indeed, knowing cloud 3-D geometry could lead to: 1) improving our understanding of cloud microphysical properties and processes, and 2) improving our knowledge of the radiative effects of cloud on the Earth's energy budget. The Multi-angle Imaging SpectroRadiometer (MISR) is on board the Terra satellite, in its 17th year of operation as of 2017. MISR provides nine views of the same scene that allow scientists to visualize the 3-D structure of observed clouds to a certain extent. Taking advantage of such multi-angle characteristic, this project aims to reconstruct cloud volumes from MISR data. The reconstruction domain is defined such that it takes into account the curvature of the Earth’s ellipsoidal surface. The input satellite images used are the Radiometric Camera-by-camera Cloud Masks at 1.1 km resolution developed by the MISR science team, and custom cloud masks at 275 m resolution developed from MISR RGB images in this project. Due to the time difference between each camera view angle, wind correction is performed on the input cloud masks. For the reconstruction method, “ray casting” algorithms that fully account for the instrument's geometric properties are developed. The reconstruction results are presented for three hand-picked MISR cloud scenes. Strengths and limitations of the reconstruction method are explored, and the outlook for the use of the reconstruction results are discussed.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2018-03-13 without embargo terms","The student, Byungsuk Lee, accepted the attached license on 2017-12-11 at 14:33.","The student, Byungsuk Lee, submitted this Thesis for approval on 2017-12-11 at 14:41.","This Thesis was approved for publication on 2017-12-12 at 12:40.","DSpace SAF Submission Ingestion Package generated from Vireo submission #11835 on 2018-03-13 at 10:10:25","Made available in DSpace on 2018-03-13T15:48:54Z (GMT). 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