Comparison of Handheld NDVI Sensor Measurements and Drone Sensing NDVI in Potato Fields.

Abstract

NDVI（Normalized difference vegetation index）measurements have become easier to recent years. This study compares handheld NDVI sensor values with light sources（H-NDVI）and NDVI calculated from images taken by drones equipped with multispectral cameras and spectral sunlight sensors（D-NDVI）. Root mean square error（RMSE）of the H-NDVI estimated from the D-NDVI, the assumed error and the range of NDVI used for growth diagnosis revealed the need for conversion between H-NDVI and D-NDVI. The effect of differences in sunlight conditions on D-NDVI measurements was also investigated. D-NDVI and H-NDVI were measured in the field plots of potato（Solanum tuberosum L.）varieties, 'Konahime' and 'Toya'. The regression equations were obtained with coefficients of determinations greater than 0.98, slopes ranging from 0.976 to 0.994, and intercepts from 0.005 to 0.017. The two regression equations were statistically combinable and the RMSE was small enough at 0.036, which were sufficiently small. The combined regression equation was used to convert D-NDVI to H-NDVI （estimated H-NDVI）, and no significant difference was found between the differences in D-NDVI and estimated H-NDVI respectively and H-NDVI．D-NDVI did not need to be converted to H-NDVI by the regression equation. The effect of direct sunlight on the D-NDVI measurements was compared among the different conditions of hourly sunshine hours and solar radiation. The results showed that the measured values were stable regardless of these conditions.