Assessing Radiometric Correction Approaches for Multi-Spectral UAS Imagery for Horticultural Applications

Yu-Hsuan Tu,Kasper Johansen,Stuart Phinn,Andrew Robson

doi:10.3390/rs10111684

Abstract

Multi-spectral imagery captured from unmanned aerial systems (UAS) is becoming increasingly popular for the improved monitoring and managing of various horticultural crops. However, for UAS-based data to be used as an industry standard for assessing tree structure and condition as well as production parameters, it is imperative that the appropriate data collection and pre-processing protocols are established to enable multi-temporal comparison. There are several UAS-based radiometric correction methods commonly used for precision agricultural purposes. However, their relative accuracies have not been assessed for data acquired in complex horticultural environments. This study assessed the variations in estimated surface reflectance values of different radiometric corrections applied to multi-spectral UAS imagery acquired in both avocado and banana orchards. We found that inaccurate calibration panel measurements, inaccurate signal-to-reflectance conversion, and high variation in geometry between illumination, surface, and sensor viewing produced significant radiometric variations in at-surface reflectance estimates. Potential solutions to address these limitations included appropriate panel deployment, site-specific sensor calibration, and appropriate bidirectional reflectance distribution function (BRDF) correction. Future UAS-based horticultural crop monitoring can benefit from the proposed solutions to radiometric corrections to ensure they are using comparable image-based maps of multi-temporal biophysical properties.

Highlights

There is a direct connection between how much photosynthetic active radiation is absorbed and scattered by plant leaves and their biogeochemical properties
Multi-spectral imagery captured from unmanned aerial systems (UAS) is becoming more commonly used as a technology for monitoring and managing horticultural crops based on such phenomenon [5,6,7,8,9,10]
Increasing spatial resolution in UAS imagery comes with lower flight altitude, which means that each camera frame covers a smaller area

Summary

Introduction

There is a direct connection between how much photosynthetic active radiation is absorbed and scattered by plant leaves and their biogeochemical properties. One of the final products from common commercially available image processing applications is an ortho-rectified mosaic with digital number values [9,10,11]. Such images are sufficient for some types of classification [4,10,11], the digital numbers only represent the relative brightness range of the ground features and cannot be used to extract consistent information on biophysical properties, derive calibrated vegetation indices or be used to compare multi-temporal datasets. The orthomosaic imagery needs to be converted from digital number to normalised at-surface reflectance [4,12]

Methods

Results

Discussion

Conclusion