An Airborne Multispectral Imaging System Based on Two Consumer-Grade Cameras for Agricultural Remote Sensing

Remote Sensing

Chenghai Yang¹  John K. Westbrook²  Charles P.-C. Suh²  Daniel E. Martin¹  W. Clint Hoffmann¹  Yubin Lan¹  Bradley K. Fritz¹ 

[1] USDA-Agricultural Research Service, Aerial Application Technology Research Unit, 3103 F&B Road, College Station, TX 77845, USA; E-Mails:;USDA-Agricultural Research Service, Insect Control and Cotton Disease Research Unit, 2771 F&B Road, College Station, TX 77845, USA; E-Mails:

关键词: airborne multispectral imaging system;    consumer-grade camera;    geotagged image;    image alignment;    crop condition assessment;    pest detection;   

DOI  :  10.3390/rs6065257

来源: mdpi

【 摘 要 】

This paper describes the design and evaluation of an airborne multispectral imaging system based on two identical consumer-grade cameras for agricultural remote sensing. The cameras are equipped with a full-frame complementary metal oxide semiconductor (CMOS) sensor with 5616 × 3744 pixels. One camera captures normal color images, while the other is modified to obtain near-infrared (NIR) images. The color camera is also equipped with a GPS receiver to allow geotagged images. A remote control is used to trigger both cameras simultaneously. Images are stored in 14-bit RAW and 8-bit JPEG files in CompactFlash cards. The second-order transformation was used to align the color and NIR images to achieve subpixel alignment in four-band images. The imaging system was tested under various flight and land cover conditions and optimal camera settings were determined for airborne image acquisition. Images were captured at altitudes of 305–3050 m (1000–10,000 ft) and pixel sizes of 0.1–1.0 m were achieved. Four practical application examples are presented to illustrate how the imaging system was used to estimate cotton canopy cover, detect cotton root rot, and map henbit and giant reed infestations. Preliminary analysis of example images has shown that this system has potential for crop condition assessment, pest detection, and other agricultural applications.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland