Current Proximal Sensing technologies are based on multispectral imaging systems able to capture images in a few spectral bands, usually centred in VIS and NIR regions, to derive vegetation indices. However, most of such systems lack an internal radiometric calibration to estimate the actual reflectance of the observed target, making them sensitive to the local radiative environment and requiring a per-session calibration against a reference target. To overcome such dependence, the instrument described adopts an active illumination of the target surface, allowing the monitoring of soil and low vegetation surfaces by a radiometrically pre-calibrated imaging camera. The system, driven by a micro-controller, is contained in a light-tight box, actively illuminated by LED sources with different emission bands (R, G, B and IR). These features make measurements with the proposed instrument independent of local lighting conditions and the need for the in situ, per-session calibrations that are mandatory with the conventionally adopted instrumentation for field measurements. The capture of multi -spectral images is performed at a relatively high resolution (1269x972 px) in the broadband visible (VIS, 420-670 nm), monochromatic (R, G, B) and near-infrared (NIR, 820 nm) domains, and is suitable to characterise different surfaces, such as soil, turf, and low-vegetation. A web-based user interface allows the control and the parametrisation of measurements, together with the archival of the acquired images both in RAW format and as calibrated spectral reflectance or already processed as the most common vegetation indices (NDVI, EVI, SAVI). The system is intended for use in a research environment and the technical management of recreation or cultivated surfaces, either for direct use or as a calibrated reference in support of proximal-sensing or drone -based applications.

Orlando, S., Minacapilli, M., Sarno, M., Carrubba, A., Motisi, A. (2022). A low-cost multispectral imaging system for the characterisation of soil and small vegetation properties using visible and near-infrared reflectance [10.1016/j.compag.2022.107359].

A low-cost multispectral imaging system for the characterisation of soil and small vegetation properties using visible and near-infrared reflectance

Orlando, S
Primo
;
Minacapilli, M;Sarno, M;Carrubba, A;Motisi, A
Ultimo
2022-11-01

Abstract

Current Proximal Sensing technologies are based on multispectral imaging systems able to capture images in a few spectral bands, usually centred in VIS and NIR regions, to derive vegetation indices. However, most of such systems lack an internal radiometric calibration to estimate the actual reflectance of the observed target, making them sensitive to the local radiative environment and requiring a per-session calibration against a reference target. To overcome such dependence, the instrument described adopts an active illumination of the target surface, allowing the monitoring of soil and low vegetation surfaces by a radiometrically pre-calibrated imaging camera. The system, driven by a micro-controller, is contained in a light-tight box, actively illuminated by LED sources with different emission bands (R, G, B and IR). These features make measurements with the proposed instrument independent of local lighting conditions and the need for the in situ, per-session calibrations that are mandatory with the conventionally adopted instrumentation for field measurements. The capture of multi -spectral images is performed at a relatively high resolution (1269x972 px) in the broadband visible (VIS, 420-670 nm), monochromatic (R, G, B) and near-infrared (NIR, 820 nm) domains, and is suitable to characterise different surfaces, such as soil, turf, and low-vegetation. A web-based user interface allows the control and the parametrisation of measurements, together with the archival of the acquired images both in RAW format and as calibrated spectral reflectance or already processed as the most common vegetation indices (NDVI, EVI, SAVI). The system is intended for use in a research environment and the technical management of recreation or cultivated surfaces, either for direct use or as a calibrated reference in support of proximal-sensing or drone -based applications.
nov-2022
Orlando, S., Minacapilli, M., Sarno, M., Carrubba, A., Motisi, A. (2022). A low-cost multispectral imaging system for the characterisation of soil and small vegetation properties using visible and near-infrared reflectance [10.1016/j.compag.2022.107359].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/573586
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