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Library Validating the geometric accuracy of high spatial resolution multispectral satellite data

Validating the geometric accuracy of high spatial resolution multispectral satellite data

Validating the geometric accuracy of high spatial resolution multispectral satellite data

Resource information

Date of publication
december 2013
Resource Language
ISBN / Resource ID
AGRIS:US201500210918
Pages
271-280

Uses of high spatial resolution data obtained from satellite-based sensors include creating land cover maps, deriving large-scale quantitative assessments such as vegetation indices, and visually assessing an area for qualitative information only assessable from large-scale digital data. One of the more popular uses of high spatial resolution data is to use the image as a base map for on-screen digitizing spatially dependent vector products. Since most geographic information system (GIS) databases store a variety of current and historical data, the accuracy of any on-screen digitized product is dependent on the spatial accuracy of the reference data. Therefore, it is important to understand and validate the accuracy of data used to create spatially referenced product, even though the data come with high spatial resolution. One of the more popular and historical high spatial resolution data within most GIS labs is QuickBird's multispectral data at 2.44 × 2.44 m ². Although there are current sensors available with a higher spatial resolution, the sometimes prohibitive expense of obtaining high spatial resolution data necessitates the need to utilize and assess historic data. Since the QuickBird has been the mainstay of high spatial resolution data since 2001, understanding the geometric accuracy of the DigitalGlobe's QuickBird user-defined panchromatic and multispectral image bundle product remains relevant. In this study, we assessed the positional accuracy of this product for its utility as an “off the shelf” base map for creating other spatially referenced products. The average Euclidean distance, RMSE (root mean square error), and RSME (root square mean error) between QuickBird-identified Universal Transverse Mercator (UTM) coordinates and coincident in situ GPS-collected UTM coordinates were calculated at 33 systematically selected locations throughout the city of Nacogdoches, Texas, USA. The average Euclidean distance, RMSE, and RSME between QuickBird's projected UTM coordinates and its corresponding GPS-collected UTM coordinates measured at 5.34 meters, 5.79 meters, and 4.05 meters, respectively. They were well within DigitalGlobe's stated RMSE positional accuracy of 14.0 meters for a panchromatic and multispectral QuickBird image bundle.

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Authors and Publishers

Author(s), editor(s), contributor(s)

Unger, Daniel R.
Kulhavy, David L.
Hung, I-Kuai

Publisher(s)
Data Provider
Geographical focus