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A Practical UAV Remote Sensing Methodology to Generate Multispectral Orthophotos for Vineyards: Estimation of Spectral Reflectance Using Compact Digital Cameras

A Practical UAV Remote Sensing Methodology to Generate Multispectral Orthophotos for Vineyards: Estimation of Spectral Reflectance Using Compact Digital Cameras

Adam J. Mathews
Copyright: © 2019 |Pages: 25
ISBN13: 9781522580546|ISBN10: 1522580549|EISBN13: 9781522580553
DOI: 10.4018/978-1-5225-8054-6.ch014
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MLA

Mathews, Adam J. "A Practical UAV Remote Sensing Methodology to Generate Multispectral Orthophotos for Vineyards: Estimation of Spectral Reflectance Using Compact Digital Cameras." Geospatial Intelligence: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2019, pp. 298-322. https://doi.org/10.4018/978-1-5225-8054-6.ch014

APA

Mathews, A. J. (2019). A Practical UAV Remote Sensing Methodology to Generate Multispectral Orthophotos for Vineyards: Estimation of Spectral Reflectance Using Compact Digital Cameras. In I. Management Association (Ed.), Geospatial Intelligence: Concepts, Methodologies, Tools, and Applications (pp. 298-322). IGI Global. https://doi.org/10.4018/978-1-5225-8054-6.ch014

Chicago

Mathews, Adam J. "A Practical UAV Remote Sensing Methodology to Generate Multispectral Orthophotos for Vineyards: Estimation of Spectral Reflectance Using Compact Digital Cameras." In Geospatial Intelligence: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 298-322. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-8054-6.ch014

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Abstract

This paper explores the use of compact digital cameras to remotely estimate spectral reflectance based on unmanned aerial vehicle imagery. Two digital cameras, one unaltered and one altered, were used to collect four bands of spectral information (blue, green, red, and near-infrared [NIR]). The altered camera had its internal hot mirror removed to allow the sensor to be additionally sensitive to NIR. Through on-ground experimentation with spectral targets and a spectroradiometer, the sensitivity and abilities of the cameras were observed. This information along with on-site collected spectral data were used to aid in converting aerial imagery digital numbers to estimates of scaled surface reflectance using the empirical line method. The resulting images were used to create spectrally-consistent orthophotomosaics of a vineyard study site. Individual bands were subsequently validated with in situ spectroradiometer data. Results show that red and NIR bands exhibited the best fit (R2: 0.78 for red; 0.57 for NIR).

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