Abstract
AbstractSmartphone‐based visual assessment of vegetation cover is a promising, fast, and repeatable approach that allows land managers to compare measurements on their farm with other farms. This study determined the influence of the smartphone device on green cover measurements on several crops. The hypothesis was that different smartphones would provide similar green cover (reflectance) for management purposes (i.e., <10% difference). Forty fields in Finland were sampled between 10 and 28 July 2020 with Motorola Moto G7 and Samsung Galaxy A6 smartphones. The results were compared also with Sentinel‐2 remote sensing of normalized difference vegetation index (NDVI) and biomass quadrants. The two smartphones had different green reflectance values that were correlated to each other. Both green reflectance measurements correlated with the NDVI that was measured with the Sentinel 2 satellite sensor and biomass. These findings suggest that smartphone‐based monitoring can be used at least to classify vegetation to low, medium, and high density but that results from different cameras should not be compared.
Highlights
Rapid canopy cover estimation can inform farmers on the success of their practices
It is a digital image automatic threshold classification method based on Abbreviations: FGCC, fractional green canopy cover; NDVI, normalized difference vegetation index
Canopeo FGCC measurements from the two devices were highly correlated (Spearman rho ρ = .89; p < .001), but the Samsung Galaxy A6 smartphone produced higher canopy cover values than the Motorola Moto G7, especially at medium canopy cover indices and in sunny to partly cloudy conditions (Figure 1)
Summary
Rapid canopy cover estimation can inform farmers on the success of their practices (cover crops, seeding rates, fertilization, biomass vs. yield, etc.). Smartphone-based assessment is a promising approach for efficient estimation of green cover, and it correlates well with manual methods for above ground biomass, leaf area, and light interception (Xiong et al, 2019). Canopeo is an app developed for Matlab and smartphones (IOS and Android) that aims for accurate and rapid fractional green canopy cover (FGCC) estimation. It is a digital image automatic threshold classification method based on Abbreviations: FGCC, fractional green canopy cover; NDVI, normalized difference vegetation index
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
