5 October 2017 A geospatial database model for the management of remote sensing datasets at multiple spectral, spatial, and temporal scales
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Abstract
In this study the development and implementation of a geospatial database model for the management of multiscale datasets encompassing airborne imagery and associated metadata is presented. To develop the multi-source geospatial database we have used a Relational Database Management System (RDBMS) on a Structure Query Language (SQL) server which was then integrated into ArcGIS and implemented as a geodatabase. The acquired datasets were compiled, standardized, and integrated into the RDBMS, where logical associations between different types of information were linked (e.g. location, date, and instrument). Airborne data, at different processing levels (digital numbers through geocorrected reflectance), were implemented in the geospatial database where the datasets are linked spatially and temporally. An example dataset consisting of airborne hyperspectral imagery, collected for inter and intra-annual vegetation characterization and detection of potential hydrocarbon seepage events over pipeline areas, is presented. Our work provides a model for the management of airborne imagery, which is a challenging aspect of data management in remote sensing, especially when large volumes of data are collected.
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Gabriela Ifimov, Gabriela Ifimov, Grace Pigeau, Grace Pigeau, J. Pablo Arroyo-Mora, J. Pablo Arroyo-Mora, Raymond Soffer, Raymond Soffer, George Leblanc, George Leblanc, } "A geospatial database model for the management of remote sensing datasets at multiple spectral, spatial, and temporal scales", Proc. SPIE 10428, Earth Resources and Environmental Remote Sensing/GIS Applications VIII, 104281Q (5 October 2017); doi: 10.1117/12.2278510; https://doi.org/10.1117/12.2278510
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