Reflectance Box

The reflectance box (RoX) is a robust and easy tool to collect hyperspectral time series of your environmental research area. Fully autonoumus operation, a rugged weatherproof design paired with low power consumption makes it your uncomplicated companion for all kind of reflectance observations.

flyer manual


RoX is an automated field spectroscopy device capable of collecting unattended, continuous, long-term hyperspectral measurements.

It represents the evolution of prototypes such as Multiplexer Radiometer Irradiometer (MRI), SFLUOR box and SIF-System developed from a collaboration between Jülich Research Center and the Remote Sensing of Environmental Dynamics Laboratory of the University Milano Bicocca. The basic routines of the RoX are based on SPECY (Forschungszentrum Jülich, IBG-2: Plant Sciences).

The RoX is designed for long term measurements of solar radiance, reflected radiance and reflectance. Its robustness and flexibility make the RoX suitable for several application (e.g. vegetation monitoring, water quality, snow and ice properties).

The core of the system is the Flame spectrometer from Ocean Optics covering the Visible/Near Infrared region (300- 950 nm). Upward and downward channels of RoX allow to sequentially measure the solar irradiance and the reflected radiance from the canopy.



Wavelength range

VIS-NIR: ~ 400–950 nm (other options also available on demand)

Spectral Sampling Interval (SSI)

~ 0.65 nm

Spectral resolution (FWHM)

~ 1.5 nm

Signal to Noise Ratio (SNR)

~ 250

Field Of View (FOV)

Upwelling radiance ~ 25°. Downwelling radiance 180°


Signal Optimization

Automatic adaption to varying light conditions

Dark current

Accurate dark current determination at each measurement cycle

Manual acquisition

Interface software for manual measurement and calibration

Automatic acquisition

Fully autonomous measurement mode for unattended data acquisition 20 seconds under bright sunshine 60 seconds in overcast conditions

Quick measurements

10 seconds under bright sunshine 30 seconds in overcast conditions


Reference system stability check and uncertainty estimates

Simultaneous metadata

Temperature, GPS position, GPS time

Data storage

SD card up to 32 GB (12 months of measurements)


Robust and Waterproof housing based on the 1200 Pelicase


300 × 250 × 130 mm

Power supply

12 Volt. From battery and solar panels

Power consumption

800 mAh

Energy saver

Day/night switch for energy saving


RS232 via cable and wireless


Dust Protection

Additional dust protection for Cosine Receptors

Fiber optics

Flexible length of fiber optics according to user needs

Power supply

Solar panel and battery

Field use

Backpack option including small battery packs


How do I process RoX data?

To generate reflectance, radiance and a long list of vegetation indices, an open source R-package is available at github. For simple use, the package is wrapped in a graphical user interface to process years of data with a few clicks.

Can I power the RoX from a battery?

Yes. The RoX accepts 9-14 V via the main plug. Adapter cable to power the RoX via a LiPo battery can be ordered along with the instrument and allow hours of autonomy..

Can the RoX be used in a mobile way?

Yes! The small case and the low power consumption make the RoX a perfect field spectrometer. Having an upward and another downward looking fiber does also eliminate the need for a frequent white reference measurement. To trigger the instrument you can use the USB connection or the wireless communication. Don´t forget to checkout our fiber levelling gimbal to ensure your measurements are always nadir.


Differences in vegetation index values using measurements from two azimuth and multiple zenith viewing angles. International agrophysics 2024.

Hyun-Dong Moon, Hyunki Kim, Yuna Cho,Euni Jo, Jae-Hyun Ryu, Ho-Yong Ahn,Sang-Il Na, Kyung-Do Lee, Yang-Won Lee, Jaeil Cho


Towards a standardized, ground-based network of hyperspectral measurements: Combining time series from autonomous field spectrometers with Sentinel-2. Remote Sensing of Environment. 2024

Paul Naethe, Andrea De Sanctis, Andreas Burkart, Petya K.E. Campbell, Roberto Colombo, Biagio Di Mauro, Alexander Damm, Tarek El-Madany, Francesco Fava, John A. Gamon, Karl F. Huemmrich, Mirco Migliavacca, Eugenie Paul-Limoges, Uwe Rascher, Micol Rossini, Dirk Schüttemeyer, Giulia Tagliabue, Yongguang Zhang, Tommaso Julitta


Heterogeneous marine robotic system for environmental monitoring missions. IEEE 2023.

Fausto Ferreira,Anja Babić,Martin Oreč,Nikola Mišković,Corrado Motta,Roberta Ferretti,Angelo Odetti, Simona Aracri, Gabriele Bruzzone, Massimo Caccia, Federica Braga, Giorgia Manfè, Giuliano Lorenzetti, Gianmarco Scarpa, Francesca De Pascalis


Calibration and Validation from Ground to Airborne and Satellite Level: Joint Application of Time-Synchronous Field Spectroscopy, Drone, Aircraft and Sentinel-2 Imaging

Paul Naethe, Maryam Asgari, Caspar Kneer, Michel Knieps, Alexander Jenal, Immanuel Weber, Tina Moelter, Filip Dzunic, Paul Deffert, Edvinas Rommel, Michael Delaney, Björn Baschek, Gilles Rock, Jens Bongartz, Andreas Burkart


Very High-Resolution Imagery and Machine Learning for Detailed Mapping of Riparian Vegetation and Substrate Types

Edvinas Rommel,Laura Giese, Katharina Fricke, Frederik Kathöfer, Maike Heuner,Tina Mölter, Paul Deffert, Maryam Asgari, Paul Näthe, Filip Dzunic, Gilles Rock,Jens Bongartz, Andreas Burkart, Ina Quick, Uwe Schröder, Björn Baschek


Iterative design of a high light throughput cosine receptor fore optic for unattended proximal remote sensing. Journal of Applied Remote Sensing. 2022.

Andreas Burkart, Mitchell Kennedy, Paul Näthe, Tommaso Julitta


Preliminary Investigation on Phytoplankton Dynamics and Primary Production Models in an Oligotrophic Lake from Remote Sensing Measurements. Sensors 2021.

Ilaria Cesana, Mariano Bresciani, Sergio Cogliati, Claudia Giardino, Remika Gupana, Dario Manca, Stefano Santabarbara, Monica Pinardi, Martina Austoni, Andrea Lami, Roberto Colombo.


Retrieval of Dust Properties From Spectral Snow Reflectance Measurements. Front. Environ. Sci., 2021.

A. Kokhanovsky, B. Di Mauro, R. Garzonio, R. Colombo


Deep Learning with WASI Simulation Data for Estimating Chlorophyll a Concentration of Inland Water Bodies. Remotes sensing 2021.

Philipp M. Maier, Sina Keller and Stefan Hinz


Changes of NOx in urban air detected with monitoring VIS-NIR field spectrometer during the coronavirus pandemic: A case study in Germany. Science of The Total Environment. 2020.

Paul Näthe, Michael Delaney, Tommaso Julitta


Proximal VIS-NIR spectrometry to retrieve substance concentrations in surface waters using partial least squares modelling. Water Supply ws2018177.

A. Wagner S. Hilgert T. Kattenborn S. Fuchs


PRISMA hyperspectral satellite mission: first data on snow in the Alps, EGU General Assembly 2020

Di Mauro, B., Garzonio, R., Bramati, G., Cogliati, S., Cremonese, E., Julitta, T., Panigada, C., Rossini, M., and Colombo


Exploiting top of Canopy Sun Induced Chlorophyll Fluorescence by the FloX. From Instrument performance to data processing. OPTIMISE COST Action Final Meeting. 21-23 February 2018, Sofia (Bulgaria)

Julitta T. Burkart A. Colombo R. Rossini M. Schickling A. Migliavacca M. Cogliati S. Wutzler T. Näthe P. Rascher U.

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Characterisation of reflectance and chlorophyll fluorescence anisotropy – defining requirements for an experimental setup. Geophysical Research Abstracts, vol. 20, EGU2018-16936, 2018. EGU General Assembly 2018

Biriukova K. Julitta T. Celesti M. Panigada C. Evdokimov A. Migliavacca M. Rossini M

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