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ARS Home » Plains Area » College Station, Texas » Southern Plains Agricultural Research Center » Aerial Application Technology Research » Research » Publications at this Location » Publication #325984
Title: Evaluation of an airborne remote sensing platform consisting of two consumer-grade cameras for crop identification

Author
item ZHANG, JIAN - Huazhong Agricultural University
item Yang, Chenghai
item SONG, HUAIBO - Huazhong Agricultural University
item Hoffmann, Wesley
item ZHANG, DONGYAN - Anhui Agricultural University
item ZHANG, GUOZHONG - Huazhong Agricultural University

Submitted to: Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/11/2016
Publication Date: 3/18/2016
Citation: Zhang, J., Yang, C., Song, H., Hoffmann, W.C., Zhang, D., Zhang, G. 2016. Evaluation of an airborne remote sensing platform consisting of two consumer-grade cameras for crop identification. Remote Sensing. 8:257.

Interpretive Summary: Remote sensing systems based on consumer-grade cameras have been increasingly used in scientific research and remote sensing applications because of their low cost and ease of use. However, the performance of consumer-grade cameras for practical applications have not been well documented in related studies. This research evaluated both normal color images and near-infrared images acquired using two consumer-grade cameras over a large cropping area for crop identification. Image classification and accuracy assessment showed that the normal color images with advanced image processing methods were effective for crop identification, though the additional near-infrared images improved crop classification accuracy. The results from this study will provide useful information for aerial applicators and other remote sensing practitioners on the use of consumer-grade cameras for crop identification and other agricultural applications.

Technical Abstract: Remote sensing systems based on consumer-grade cameras have been increasingly used in scientific research and remote sensing applications because of their low cost and ease of use. However, the performance of consumer-grade cameras for practical applications have not been well documented in related studies. The objective of this research was to apply three commonly-used classification methods (unsupervised, supervised, and object-based) to 3-band imagery with RGB (red, green, and blue bands) and 4-band imagery with RGB and near-infrared (NIR) bands to evaluate the performance of a dual-camera imaging system for crop identification. Airborne images were acquired from a cropping area in Texas and mosaicked and georeferenced. The mosaicked imagery was classified using the three classification methods to assess the usefulness of NIR imagery for crop identification and to evaluate performance differences between the object-based and pixel-based methods. Image classification and accuracy assessment showed that the additional NIR band imagery improved crop classification accuracy over the RGB imagery and that the object-based method achieved better results with additional non-spectral image features. The results from this study indicate that the airborne imaging system based on two consumer-grade cameras used in this study can be useful for crop identification and other agricultural applications.