Radiometric Correction with Topography Influence of Multispectral Imagery Obtained from Unmanned Aerial Vehicles

This article aims to present the methods of the radiometric correction of multispectral images-a short review of the existing techniques. The role of radiometric correction is essential to many applications, especially in precision farming, forestry, and climate analysis. Moreover, this paper presents a new relative approach, which considers the angle of inclination of the terrain and the angle of incidence of electromagnetic radiation on the imaged objects when obtaining the baseline data. This method was developed for data obtained from low altitudes-for imagery data acquired by sensors mounted on UAV platforms. The paper analyses the effect of the correction on the spectral information, i.e., the compatibility of the spectral reflection characteristics obtained from the image with the spectral reflection characteristics obtained in the field. The developed method of correction for multispectral data obtained from low altitudes allows for the mapping of spectral reflection characteristics to an extent that allows for the classification of terrestrial coverage with an accuracy of over 95%. In addition, it is possible to distinguish objects that are very similar in terms of spectral reflection characteristics. This research presents a new method of correction of each spectral channel obtained by the multispectral camera, increasing the accuracy of the results obtained, e.g., based on SAM coefficients or correlations, but also when distinguishing land cover types during classification. The results are characterized by high accuracy (over 94% in classification).

Automated summary

This article provides a brief overview of existing techniques for radiometric correction of multispectral images. Radiometric correction is crucial in various applications, particularly in precision farming, forestry, and climate analysis. The paper introduces a new relative approach for obtaining baseline data by considering the terrain's inclination angle and the angle of incidence of electromagnetic radiation. The developed method enables accurate mapping and classification of terrestrial coverage based on spectral reflection characteristics, with an accuracy of over 95%.