How Many Bits? Radiometric Resolution as a Factor in Obtaining Forestry Information with Remotely Sensed Measurments

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dc.contributor.advisorGoward, Samuelen_US
dc.contributor.authorFranks, Shannonen_US
dc.contributor.departmentGeographyen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2006-02-04T08:23:05Z
dc.date.available2006-02-04T08:23:05Z
dc.date.issued2006-01-19en_US
dc.description.abstractIn this study, Landsat 7 and IKONOS data were compared to determine if higher quantization is beneficial for forestry remote sensing. An industrial forestry site in central Virginia was chosen for analysis because of its large variation in standing biomass. Data were selected and processed so that the measurements were as comparable as possible to one another. The processing steps included spatial aggregation, pixel alignment, and calibration to planetary reflectance. Due to several aspects of study design and execution, the results are inconclusive. The registered data sets were found to differ by more than 1-2%, which is above the theoretical limits based on their radiometric resolutions. Lessons learned from this study are that to investigate radiometric resolutions, extreme care must be taken to understand the consequences of every data processing step and that all differences in the compared datasets cannot be overcome.en_US
dc.format.extent10167374 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/3315
dc.language.isoen_US
dc.subject.pqcontrolledRemote Sensingen_US
dc.subject.pqcontrolledGeographyen_US
dc.subject.pquncontrolledRemote Sensingen_US
dc.subject.pquncontrolledRadiometric Resolutionen_US
dc.subject.pquncontrolledForestryen_US
dc.subject.pquncontrolledQuantizationen_US
dc.titleHow Many Bits? Radiometric Resolution as a Factor in Obtaining Forestry Information with Remotely Sensed Measurmentsen_US
dc.typeThesisen_US

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