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Crop-Surface-Models (CSMs) are a useful tool for monitoring in-field crop growth variability, thus enabling precision agriculturewhich is necessary for achieving higher agricultural yields. This contribution provides a first assessment on the suitability of usingconsumer-grade smart cameras as sensors for the stereoscopic creation of crop-surface models using oblique imagery acquired fromground-based positions. An application that automates image acquisition and transmission was developed. Automated imageacquisition took place throughout the growing period of barley in 2013. For three dates where both automated image acquisition andmanual measurements of plant height were available, CSMs were generated using a combination of AgiSoft PhotoScan and EsriArcGIS. The coefficient of determination R2 between the average of the manually measured plant heights per plots and the averageheight of the developed crop surface models was 0.61 (n = 24). The overall correlation between the manually measured heights andthe CSM-derived heights is 0.78. The average per plot of the manually measured plant heights in the timeframe covered by thegenerated CSMs range from 19 to 95 cm, while the average plant height per plot of the generated CSMs range from 2.1 to 69 cm.These first results show that the presented approach is feasible

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

Evaluating the potential of consumer-grade smart cameras for low-cost stereo-photogrammetric Crop-Surface Monitoring