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The method estimates AOD using radiance differences between shadow and non-shadow regions, originally requiring substantial user knowledge and time. The study focuses on automating key steps to improve operational readiness, including prediction of future shadow locations, reduction of computational complexity via computer programming, and analysis of shadow morphology to identify optimum radiance sampling regions within observed shadows.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/automating-the-shadow-method-for-aerosol-optical-depth-retrieval-masters-thesis/157600/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/automating-the-shadow-method-for-aerosol-optical-depth-retrieval-masters-thesis/157600.png","ImageObject",300,407,{"name":92,"@type":93},"Aria Callaghan","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-03","2026-08-29",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",14,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What data source and signal does the shadow method use to estimate Aerosol Optical Depth?","Question",{"text":113,"@type":114},"It uses radiance differences between shadow and non-shadow regions in QuickBird high-resolution commercial satellite imagery to estimate Aerosol Optical Depth.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"Why is automation required in this investigation?",{"text":118,"@type":114},"The original process is time-consuming and depends on substantial user knowledge, so automation is pursued to make the method more standalone and operational.",{"name":120,"@type":111,"acceptedAnswer":121},"Which aspects of the workflow are automated and improved?",{"text":122,"@type":114},"The study automates prediction of shadow locations for future times and applies programming to reduce computational complexity, while also analyzing shadow morphology to choose optimum radiance sampling regions.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},157600,1787984892,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":26,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":130,"read_time":144,"preview_page_count":4},962084926284,"https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0","Calhoun: The NPS Institutional Archive  \nDSpace Repository  \n\n| Theses and Dissertations 1. Thesis and Dissertation Collection, all items |\n| --- |\n| 2007-03\u003Cbr>Automating the shadow method for aerosol optical depth retrieval\u003Cbr>Dombrock, Ryan M.\u003Cbr>Monterey, California. Naval Postgraduate School |\n\n[http://hdl.handle.net/10945/3548](http://hdl.handle.net/10945/3548)  \nDownloaded from NPS Archive: Calhoun  \nNAVAL POSTGRADUATE  \nSCHOOL MONTEREY, CALIFORNIA  \nTHESIS  \nAUTOMATING THE SHADOW METHOD FOR AEROSOL OPTICAL DEPTH RETRIEVAL  \nby  \nRyan M. Dombrock  \nMarch 2007  \nThesis Advisor: P. A. Durkee  \nSecond Reader: K. E. Nielsen  \nApproved for public release; distribution is unlimited  \nTHIS PAGE INTENTIONALLY LEFT BLANK  \n\n| REPORT DOCUMENTATION PAGE |  |  |  |  | Form Approved OMB No. 0704-0188 |  |\n| --- | --- | --- | --- | --- | --- | --- |\n| Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188) Washington DC 20503. |  |  |  |  |  |  |\n| 1. AGENCY USE ONLY (Leave blank) |  | 2. REPORT DATE\u003Cbr>March 2007 |  | 3. REPORT TYPE AND DATES COVERED\u003Cbr>Master’s Thesis |  |  |\n| 4. TITLE AND SUBTITLE Automating the Shadow Method for Aerosol Optical Depth Retrieval |  |  |  |  | 5. FUNDING NUMBERS |  |\n| 6. AUTHOR(S) Ryan M. Dombrock |  |  |  |  |  |  |\n| 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)\u003Cbr>Naval Postgraduate School\u003Cbr>Monterey, CA 93943-5000 |  |  |  |  | 8. PERFORMING ORGANIZATION REPORT NUMBER |  |\n| 9. SPONSORING /MONITORING AGENCY NAME(S) AND ADDRESS(ES)\u003Cbr>N/A |  |  |  |  | 10. SPONSORING/MONITORING AGENCY REPORT NUMBER |  |\n| 11. SUPPLEMENTARY NOTES The views expressed in this thesis are those of the author and do not reflect the official policy or position of the Department of Defense or the U.S. Government. |  |  |  |  |  |  |\n| 12a. DISTRIBUTION / AVAILABILITY STATEMENT\u003Cbr>Approved for public release; distribution is unlimited |  |  |  |  | 12b. DISTRIBUTION CODE |  |\n| 13. ABSTRACT (maximum 200 words)\u003Cbr>A new method for remote sensing retrieval of Aerosol Optical Depth was proposed and investigated by Vincent (2006) . This shadow-based method uses the radiance difference between shadow and non-shadow regions in QuickBird high resolution commercial satellite imagery to estimate Aerosol Optical Depth. Though the process is initially time-consuming, requiring a high level of user knowledge to accomplish the procedure, great potential exists for further development into a stand-alone operational method for overland retrievals at any location and time. It is the automation of this process in order to make it more operational in nature that is the purpose of this investigation. Knowledge is gained in the realm of predicting shadow location for future times. Specific process automation is applied through computer programming to decrease the computational complexity of the method. Also the physical variations of shadow regions are investigated in terms of their brightness change across various spatial profiles. This study of shadow region variation is termed shadow morphology and seeks to provide a user with optimum radiance sampling regions within an observed shadow region. Through the integration of these automation techniques, a more unified and operationally focused iteration of the shadow method is derived. |  |  |  |  |  |  |\n| 14. SUBJECT TERMS\u003Cbr>Aerosol, Aerosol Optical Depth Retrieval, Shadow Mo","cbCaitScGbSOyn7D","https://ap.wps.com/l/cbCaitScGbSOyn7D","pdf",636965,"English","# Abstract\n## Aerosol Optical Depth retrieval method\n## Automation goals and operationalization\n## Shadow prediction and computational efficiency\n## Shadow morphology and radiance sampling","[{\"question\":\"What data source and signal does the shadow method use to estimate Aerosol Optical Depth?\",\"answer\":\"It uses radiance differences between shadow and non-shadow regions in QuickBird high-resolution commercial satellite imagery to estimate Aerosol Optical Depth.\"},{\"question\":\"Why is automation required in this investigation?\",\"answer\":\"The original process is time-consuming and depends on substantial user knowledge, so automation is pursued to make the method more standalone and operational.\"},{\"question\":\"Which aspects of the workflow are automated and improved?\",\"answer\":\"The study automates prediction of shadow locations for future times and applies programming to reduce computational complexity, while also analyzing shadow morphology to choose optimum radiance sampling regions.\"}]","Automating the Shadow Method for Aerosol Optical Depth Retrieval - Master’s Thesis | PDF",151]