Institute for Sustainable Agro-ecosystem Services @ University of Tokyo


Measured variables surface
Operating system mac, windows, linux, matlab
Licence open-source, freeware
Automation level automated
Plant requirements any
Export formats csv
Other information requires matlab to run

Scientific article(s)

EasyPCC: Benchmark Datasets and Tools for High-Throughput Measurement of the Plant Canopy Coverage Ratio under Field Conditions
Wei Guo, Bangyou Zheng, Tao Duan, Tokihiro Fukatsu, Scott Chapman, Seishi Ninomiya
Sensors, 2017 View paper

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EasyPCC is a tool for effective and accurate evaluation of the ground coverage ratio from a large number of images under variable field conditions. The core algorithm of EasyPCC is based on a pixel-based segmentation method using a decision-tree-based segmentation model (DTSM). EasyPCC was developed under the MATLAB® and R languages; thus, it could be implemented in high-performance computing to handle large numbers of images following just a single model training process.

Source: Sensors website

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