Simulating an Autonomously Operating Low-Cost Static Terrestrial LiDAR for Multitemporal Maize Crop Height Measurements
AbstractIn order to optimize agricultural processes, near real-time spatial information about in-field variations, such as crop height development (i.e., changes over time), is indispensable. This development can be captured with a LiDAR system. However, its applicability in precision agriculture is often hindered due to high costs and unstandardized processing methods. This study investigates the potential of an autonomously operating low-cost static terrestrial laser scanner (TLS) for multitemporal height monitoring of maize crops. A low-cost system is simulated by artificially reducing the point density of data captured during eight different campaigns. The data were used to derive and assess crop height models (CHM). Results show that heights calculated with CHM based on the unreduced point cloud are accurate when compared to manually measured heights (mean deviation = 0.02 m, standard deviation = 0.15 m, root mean square error (RMSE) = 0.16 m). When reducing the point cloud to 2% of its original size to simulate a low-cost system, this difference increases (mean deviation = 0.12 m, standard deviation = 0.19 m, RMSE = 0.22 m). We found that applying the simulated low-cost TLS system in precision agriculture is possible with acceptable accuracy up to an angular scan resolution of 8 mrad (i.e., point spacing of 80 mm at 10 m distance). General guidelines for the measurement set-up and an automatically executable method for CHM generation and assessment are provided and deserve consideration in further studies. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Crommelinck, S.; Höfle, B. Simulating an Autonomously Operating Low-Cost Static Terrestrial LiDAR for Multitemporal Maize Crop Height Measurements. Remote Sens. 2016, 8, 205.
Crommelinck S, Höfle B. Simulating an Autonomously Operating Low-Cost Static Terrestrial LiDAR for Multitemporal Maize Crop Height Measurements. Remote Sensing. 2016; 8(3):205.Chicago/Turabian Style
Crommelinck, Sophie; Höfle, Bernhard. 2016. "Simulating an Autonomously Operating Low-Cost Static Terrestrial LiDAR for Multitemporal Maize Crop Height Measurements." Remote Sens. 8, no. 3: 205.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.