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Article

Multispectral Remote Sensing from Unmanned Aircraft: Image Processing Workflows and Applications for Rangeland Environments

1
Jornada Experimental Range, New Mexico State University, 2995 Knox St., Las Cruces, NM 88003, USA
2
Goforth Scientific Inc., P.O. Box 1579, Leesburg, VA 20177, USA
3
USDA-Agricultural Research Service, Jornada Experimental Range, 2995 Knox St., Las Cruces, NM 88003, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2011, 3(11), 2529-2551; https://doi.org/10.3390/rs3112529
Received: 28 September 2011 / Revised: 18 November 2011 / Accepted: 18 November 2011 / Published: 22 November 2011
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs) based Remote Sensing)
Using unmanned aircraft systems (UAS) as remote sensing platforms offers the unique ability for repeated deployment for acquisition of high temporal resolution data at very high spatial resolution. Multispectral remote sensing applications from UAS are reported in the literature less commonly than applications using visible bands, although light-weight multispectral sensors for UAS are being used increasingly. . In this paper, we describe challenges and solutions associated with efficient processing of multispectral imagery to obtain orthorectified, radiometrically calibrated image mosaics for the purpose of rangeland vegetation classification. We developed automated batch processing methods for file conversion, band-to-band registration, radiometric correction, and orthorectification. An object-based image analysis approach was used to derive a species-level vegetation classification for the image mosaic with an overall accuracy of 87%. We obtained good correlations between: (1) ground and airborne spectral reflectance (R2 = 0.92); and (2) spectral reflectance derived from airborne and WorldView-2 satellite data for selected vegetation and soil targets. UAS-acquired multispectral imagery provides quality high resolution information for rangeland applications with the potential for upscaling the data to larger areas using high resolution satellite imagery. View Full-Text
Keywords: Unmanned Aircraft Systems (UAS); multispectral; reflectance; classification Unmanned Aircraft Systems (UAS); multispectral; reflectance; classification
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MDPI and ACS Style

Laliberte, A.S.; Goforth, M.A.; Steele, C.M.; Rango, A. Multispectral Remote Sensing from Unmanned Aircraft: Image Processing Workflows and Applications for Rangeland Environments. Remote Sens. 2011, 3, 2529-2551. https://doi.org/10.3390/rs3112529

AMA Style

Laliberte AS, Goforth MA, Steele CM, Rango A. Multispectral Remote Sensing from Unmanned Aircraft: Image Processing Workflows and Applications for Rangeland Environments. Remote Sensing. 2011; 3(11):2529-2551. https://doi.org/10.3390/rs3112529

Chicago/Turabian Style

Laliberte, Andrea S.; Goforth, Mark A.; Steele, Caitriana M.; Rango, Albert. 2011. "Multispectral Remote Sensing from Unmanned Aircraft: Image Processing Workflows and Applications for Rangeland Environments" Remote Sens. 3, no. 11: 2529-2551. https://doi.org/10.3390/rs3112529

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