From Event: SPIE Commercial + Scientific Sensing and Imaging, 2018
Thermal image quality is very critical for accurately quantify spatial and temporal growth and stress patterns of field crops. Image quality can be impacted by many factors including environment, flying altitude, and camera focal length. Often times the thermal sensor selection is based upon price or already owned sensor. Metrics are available to select the flight altitude based on the thermal sensor for desired ground resolution, however, no study has been conducted to provide the relative difference in image quality and efficiency of generating a thermal orthomosaic. Therefore, this study was conducted with the goal to compare the accuracy of canopy temperature quantification and assess the quality of thermal orthomosaic when using a thermal sensor of different focal length and image acquisition at varying flying altitudes. Three thermal infrared cameras were selected with focal lengths of 9mm, 13mm, and 19mm. All three cameras were flown at altitudes of 10m, 40m, and 70m, to collect aerial imagery of 7,000 m2 soybeans field. The cameras were mounted on a rotary quadcopter. All flights were conducted at 3 m/s flying speed, and 1 second shutter trigger interval. A ground reference system provided ground truth data for thermometric transformations. Imagery data was compared to assess differences in number of images collected, percentage overlap required for 1 second shutter trigger interval, quality of orthomosaic and accuracy of canopy temperatures. Preliminary results show that 13 mm focal length and 40 m altitude result in a finer resolution orthomosaic. The canopy temperatures were quantified accurately regardless of altitude and focal length.
Ajay Sharda and Harman S. Sangha, "Image quality and accuracy of different thermal sensor at varying operation parameters (Conference Presentation)," Proc. SPIE 10664, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping III, 106640G (Presented at SPIE Commercial + Scientific Sensing and Imaging: April 16, 2018; Published: 15 May 2018); https://doi.org/10.1117/12.2307168.5783315373001.
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