Shutter Speed Influences the Capability of a Low-Cost Multispectral Sensor to Estimate Turfgrass (Cynodon dactylon L.—Poaceae) Vegetation Vigor Under Different Solar Radiation Conditions

Radiometric calibration of multispectral imagery plays a critical role in the determination of vegetation-related features. This radiometric calibration strongly depends on a proper sensor configuration when acquiring images, the shutter speed being a critical parameter. The objective of the present study was to appraise the influence of shutter speed on the reflectance in the visible and near-infrared (NIR) spectral regions registered by a low-cost multispectral sensor (MAPIR Survey3) on a homogeneous field of turfgrass (<i>Cynodon dactylon L.</i>-Poaceae) and on the vegetation index (VI) values calculated from them, under different solar radiation conditions. For this purpose, 10 shutter speed configurations were tested in field campaigns with variable solar radiation values. The main results demonstrated that the reflectance in the green spectral region was more sensitive to shutter speed than that of the red and NIR spectral regions, particularly under high solar radiation conditions. Moreover, VIs calculated using the green band were more sensitive to slow shutter speeds, thus presenting a higher probability of providing meaningless artifact values. In conclusion, this study provides shutter speed recommendations under different illumination conditions to optimize the reflectance and the VI sensitivity within the image, which can be applied as a simple method to optimize image acquisition from unmanned aerial vehicles under varying solar radiation conditions.

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Publication Details

Journal
Sensors
Published
2025-12-20
DOI
https://doi.org/10.3390/s26010047
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
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article

Shutter Speed Influences the Capability of a Low-Cost Multispectral Sensor to Estimate Turfgrass (Cynodon dactylon L.—Poaceae) Vegetation Vigor Under Different Solar Radiation Conditions

L. Caruso, Giuseppe Manetto, Rosa María Martínez-Meroño, Sebastian Lupica et al.
Sensors
Remote Sensing in Agriculture
article

Shutter Speed Influences the Capability of a Low-Cost Multispectral Sensor to Estimate Turfgrass (Cynodon dactylon L.—Poaceae) Vegetation Vigor Under Different Solar Radiation Conditions

L. Caruso, Giuseppe Manetto, Rosa María Martínez-Meroño, Sebastian Lupica, G. Schillaci, Domenico Longo, S. Failla, Emanuele Cerruto, Nicola Furnitto, Giuseppe Sottosanti, Ramírez-Cuesta Juan Miguel, Pedro Freire-García, Maria Spagnuolo, Salvatore Privitera
article en

Abstract

Radiometric calibration of multispectral imagery plays a critical role in the determination of vegetation-related features. This radiometric calibration strongly depends on a proper sensor configuration when acquiring images, the shutter speed being a critical parameter. The objective of the present study was to appraise the influence of shutter speed on the reflectance in the visible and near-infrared (NIR) spectral regions registered by a low-cost multispectral sensor (MAPIR Survey3) on a homogeneous field of turfgrass (<i>Cynodon dactylon L.</i>-Poaceae) and on the vegetation index (VI) values calculated from them, under different solar radiation conditions. For this purpose, 10 shutter speed configurations were tested in field campaigns with variable solar radiation values. The main results demonstrated that the reflectance in the green spectral region was more sensitive to shutter speed than that of the red and NIR spectral regions, particularly under high solar radiation conditions. Moreover, VIs calculated using the green band were more sensitive to slow shutter speeds, thus presenting a higher probability of providing meaningless artifact values. In conclusion, this study provides shutter speed recommendations under different illumination conditions to optimize the reflectance and the VI sensitivity within the image, which can be applied as a simple method to optimize image acquisition from unmanned aerial vehicles under varying solar radiation conditions.

SensorsVol. 26(1)
University of Catania (IT), Centre d'Investigacions sobre Desertificació (ES)
European Commission, Università di Catania
Openalex Percentile: Top 31%
Remote Sensing in Agriculture
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