On the accuracy of infrared-converted drone cameras for use in vegetation and environmental monitoring

Abstract

Abstract Drones equipped with cameras sensitive to near-infrared wavelengths are increasingly being used in environmental assessment studies and in agriculture. These cameras can measure vegetation cover, extent of eutrophication in water bodies, and aspects of crops, such as growth vigour, biomass and potential yield. Infrared converted cameras that capture near-infrared wavelengths offer a low-cost alternative to multi-sensor multispectral cameras or drone-borne spectrometers. However, some studies point to lower accuracy in measurements by such infrared converted sensors. So, to what extent can infrared converted cameras be used to quantify vegetation condition? This study compared vegetation index measurements (NDVI) from an infrared converted camera to measurements by a multispectral camera and a handheld NDVI meter, captured over soybean and potato fields. It was observed that infrared converted camera derived NDVI was consistently lower over crop than multispectral and handheld based measurements. However, correlation between the sensor values were high (r = 0.95, r = 0.87 for respective survey days). This suggests that the infrared converted sensor is valuable for qualitative assessment of vegetation status across a farm. Based on the result of this study we however recommend caution when using infrared converted camera for quantitative applications like calculating fertiliser prescription rates from vegetation index maps. We discuss possible reasons for the lower vegetation index measurements observed, noting overestimation of reflectance in the red band, but underestimation in the near-infrared band, leading to low NDVI values.