Cloud and clear sky contamination due to sub-pixel clouds remains as a troubling issue for scientific applications that rely on remotely sensed data. Sub-pixel level clouds may not be detected by a standard cloud filtering process, and thus can cause uncertainties in satellite-based meteorological property retrievals. In this study, using collocated data from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Geostationary Operational Environmental Satellite (GOES) data, sub-pixel cloud and clear-sky contamination were studied over the west coast of Northern California. The hyper-spectral data from AVIRIS have a spatial resolution on the order of 11.5 m for the study case, thus can be used for carefully examining the sub pixel cloud related bias in GOES data. This study suggest that significant sub-pixel cloud and clear-sky contamination exist, and should be considered for future applications that use measurements from passive sensors such as GOES. Lastly, simulated AVIRIS radiance values from a radiative transfer model were used to explore the possibility of using AVIRIS data for future aerosol studies.
","abstract_html":"<p>Cloud and clear sky contamination due to sub-pixel clouds remains as a troubling issue for scientific applications that rely on remotely sensed data. Sub-pixel level clouds may not be detected by a standard cloud filtering process, and thus can cause uncertainties in satellite-based meteorological property retrievals. In this study, using collocated data from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Geostationary Operational Environmental Satellite (GOES) data, sub-pixel cloud and clear-sky contamination were studied over the west coast of Northern California. The hyper-spectral data from AVIRIS have a spatial resolution on the order of 11.5 m for the study case, thus can be used for carefully examining the sub pixel cloud related bias in GOES data. This study suggest that significant sub-pixel cloud and clear-sky contamination exist, and should be considered for future applications that use measurements from passive sensors such as GOES. Lastly, simulated AVIRIS radiance values from a radiative transfer model were used to explore the possibility of using AVIRIS data for future aerosol studies.</p>","abstract_has_math":false,"creators":["Kaplan, Celil"],"institution":null,"degree_name":"Master of Science (MS)","degree_level":"Thesis","degree_discipline":"Atmospheric Sciences","degree_department":null,"school":null,"contributors":["Jianglong Zhang"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-01-01T08:00:00Z","date_published":"2013-01-01T08:00:00Z","updated_at":"2026-07-24T03:26:30Z","subjects":["AVIRIS, GOES"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.und.edu/theses/1554","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Jianglong Zhang"]},{"key":"dc:creator","label":"Author","values":["Kaplan, Celil"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"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":["Master of Science (MS)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["AVIRIS, GOES"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.und.edu/theses/1554"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Cloud and clear sky contamination due to sub-pixel clouds remains as a troubling issue for scientific applications that rely on remotely sensed data. Sub-pixel level clouds may not be detected by a standard cloud filtering process, and thus can cause uncertainties in satellite-based meteorological property retrievals. In this study, using collocated data from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Geostationary Operational Environmental Satellite (GOES) data, sub-pixel cloud and clear-sky contamination were studied over the west coast of Northern California. The hyper-spectral data from AVIRIS have a spatial resolution on the order of 11.5 m for the study case, thus can be used for carefully examining the sub pixel cloud related bias in GOES data. This study suggest that significant sub-pixel cloud and clear-sky contamination exist, and should be considered for future applications that use measurements from passive sensors such as GOES. Lastly, simulated AVIRIS radiance values from a radiative transfer model were used to explore the possibility of using AVIRIS data for future aerosol studies.
"]},{"key":"dc:title","label":"Title","values":["An Investigation Of Sub-Pixel Cloud/clear-Sky Contamination Using Hyper-Spectral AVIRIS Data"]}]}],"canonical_facts":{"dc:contributor":["Jianglong Zhang"],"dc:creator":["Kaplan, Celil"],"dc:description.abstract":["Cloud and clear sky contamination due to sub-pixel clouds remains as a troubling issue for scientific applications that rely on remotely sensed data. Sub-pixel level clouds may not be detected by a standard cloud filtering process, and thus can cause uncertainties in satellite-based meteorological property retrievals. In this study, using collocated data from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Geostationary Operational Environmental Satellite (GOES) data, sub-pixel cloud and clear-sky contamination were studied over the west coast of Northern California. The hyper-spectral data from AVIRIS have a spatial resolution on the order of 11.5 m for the study case, thus can be used for carefully examining the sub pixel cloud related bias in GOES data. This study suggest that significant sub-pixel cloud and clear-sky contamination exist, and should be considered for future applications that use measurements from passive sensors such as GOES. Lastly, simulated AVIRIS radiance values from a radiative transfer model were used to explore the possibility of using AVIRIS data for future aerosol studies.
"],"dc:identifier":["https://commons.und.edu/theses/1554"],"dc:subject":["AVIRIS, GOES"],"dc:title":["An Investigation Of Sub-Pixel Cloud/clear-Sky Contamination Using Hyper-Spectral AVIRIS Data"],"thesis:degree_discipline":["Atmospheric Sciences"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science (MS)"]},"updated_at":"2026-07-24T03:26:30Z"}