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<br />produced a tablc ofCRE resource categories whose monitoring might be enhanced by remote <br />sensing, along wilh the types of remote-sensing data Ihat might satisfy required measuremenl <br />accuracies; the types of dala subject to invesligation are listed in Table I in order of increasing <br />complexity and generally increasing cost. Personnel involved in the remote-sensing initialive <br />collected and analyzed remote-sensing data listed in Ihe table, starting with the least complex and <br />proceeding to Ihe most complex data, until a particular data set was found 10 provide acceptable <br />accuracies for a particular resource parameter. This approach was followed because cost of data <br />is an issue. <br /> <br />The remole-sensing initiative was supervised by Mike Liszewski (IT program manager) <br />and coordinated by Philip Davis <research scientist at the U,S. Geological Survey). The initiative <br />involved all of the IT personnel and many scientists from differenl disciplines, whose expertise <br />was required for evaluation of specific remote, sensing technologies, data-provider performance, <br />data-analysis methods, and resulting accuracies. This process is now near completion. This <br />report reviews Ihe GCMRC program objectives and measured parameters and the results from our <br />remote-sensing investigations on those paramelers that might benefit from improved data <br />acquisition and/or analysis, The resources are discussed in order of the increasing capabilities <br />found by remole-sensing approaches, Thus, the order of our discussions proceeds from the <br />cultural resource program to the biologic resource program and then the physical resource <br />program. <br /> <br />Remote sensing of radiation on Earth is limited to the wavelength region from the visible <br />to microwave energies and it is this broad energy region that we have investigated for monitoring <br />applications within the CRE. The different types of remote-sensing data sels that were collected <br />and investigated for the different environmental parameters are listed in Table 2, Radar data were <br />nor included in rhis evaluation because the aircraft used for radar data collections are large, <br />impossible to maneuver in the canyon, and provide too low spatial resolutions (about 5 m) when <br />flown above the canyon rim. In addition, Ihe walls of the canyon can produce secondary radar <br />refleclions that interfere wilh the primary reflections and make the image data unintelligible. <br /> <br />The collection of numerous wavelenglh bands by multi, and hyperspectral sensors limits <br />the spatial resolution that can be achieved by such sensors because of data-rate limitalions of <br />current storage devices. Spectral resolution refers to the wavelength band width for a particular <br />image, whereas spatial resolution refers to the surface dimension of a single picture element <br />within that image. For example, mullispectral senSors Ihat record 12 wavelength'bands with 50 <br />nm spectral resolution can obtain image data at a I-m ground resolution, while hyperspectral <br />sensors that record up to 220 wavelength bunds with 10 nm spectral resolution can only obtain <br />data at a 2-4 m ground resolution, The cost for image data (listed in Table 1) increases with the <br />number of wavelength bands collected, which effects the benefitlcosl ratio and makes use of more <br />sophisticated data difficult to justify, unless these dala provide infonnation thai cannot be <br />oblained by more simple, less expensive data. Therefore, our evaluations proceeded from Ihe <br />simpler to the more complex data sets, until a viable data set was found for a particular resource <br />parameter. The final section presents the team's recommendations for future remole-sensing <br />monitoring activities based on all of our investigations. <br /> <br />2,0 CulluraIISocio-E:conomic Resources <br /> <br />The primary goal oflhe cultural/socio,economic resource program is to monitor cullural <br />and socio-economic resources with respect 10 Glen Canyon dam operalions, so Ihat ultimately a <br />model can be conslructed and used to predict and possibly mitigate the effecls of dam operations <br />on these resources. The primary resources for monitoring consist of camping beaches. prehistoric <br /> <br />6 <br />