ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume X-3-2024
https://doi.org/10.5194/isprs-annals-X-3-2024-215-2024
https://doi.org/10.5194/isprs-annals-X-3-2024-215-2024
04 Nov 2024
 | 04 Nov 2024

An Empirical Line approach for Agrowing Camera Aerial Images of inland waters based on exponential fit and in situ water measurements

Beatriz Cirino Lucchetta, Fernanda Sayuri Yoshino Watanabe, Nariane Marselhe Ribeiro Bernardo, Rafael de Campos Fialho, Nilton Nobuhiro Imai, Antonio Maria Garcia Tommaselli, and Gustavo Soares Roncolato

Keywords: Remote Sensing, Radiometric Calibration, Unmanned Aerial Vehicles (UAV), Multispectral Images, Water Bodies

Abstract. With the advancement of technology in the area of remote sensing, monitoring the Earth's surface using multispectral cameras attached to unmanned aerial vehicles (UAV) has become promising. However, in many Earth observation applications, it is needed to make compatible the spatial data of images captured by high spatial resolution multispectral sensors with the spectral response of targets on the Earth's surface. This relation is obtained through a radiometric calibration. The empirical line method is commonly used to calibrate the spectral bands of sensors. Thus, applications of this method using linear fit have retrieved negative values in water bodies. So that, attempting different adjustments, as well different reference targets, can solve this issue. In this study, the water quality of small bodies of water was analysed using a Agrowing multispectral camera, which derived negative values when applying linear fit. The aim of this study, therefore, was to fit a radiometric calibration based on empirical line method for Agrowing camera in inland water applications. Besides of standard reference targets, water samples also were attempted because showed a lower radiance response than the darkest (black) calibration target. Two empirical line methods were applied to convert the digital number (DN) from the Agrowing images into remote sensing reflectance (Rrs): linear and exponential. The exponential method showed to be more appropriate, with greater accuracy, unlike the linear method.