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Piccolo3 spectral systems

Piccolo3 spectral systems

Mac Arthur A.(1,2), Hagdorn, M.(1), Taylor R.(3), and Robinson I. (4). (1) GeoSciences, U. of Edinburgh, (2) LEO/IPL U. of Valencia, (3) Physics, U. of Edinburgh, (4) Rutherford Appleton Laboratories

Introduction to Piccolo3 spectral systems

Mac Arthur A.(1,2), Hagdorn, M.(1), Taylor R.(3), and Robinson I. (4). (1) GeoSciences, U. of Edinburgh, (2) LEO/IPL U. of Valencia, (3) Physics, U. of Edinburgh, (4) Rutherford Appleton Laboratories

Important Please note. 

Posted Jan. 2022. Fore optic shutters. Unfortunately, the bi-stable high speed electronic shutters incorporated in the piccolo fore optics are now obsolete. They were first specified in 2012 and the same model can no longer be purchased from the shutter manufacturer. The replacement shutters now offered by the manufacturer is higher specification (a longer life cycle is claimed) but are significantly more expensive. As these replacement shutters are of slightly larger external dimensions (diameter and thickness) the fore optic shutter mounting trays also need to be replaced. The replacement shutter trays can fit within the current fore optic barrels, so current barrels can continue to be used. Information on how to source replacement shutters and shutter trays is presented in Section 8 Piccolo3 Fore optic and Fibre optic assemblies See the Fore optic component suppliers paragraph.


Piccolo3 spectrometer systems

Piccolo3 systems are modular non-imaging dual-field-of-view (DFOV) multi-spectral range spectrometer systems. These systems are used to make spectrally and radiometrically resolved measurements normally for fixed-point logging, rotary-wing UAV, and field spectroscopy applications under natural skylight. The spectral and radiometric ranges can be matched to particular applications and available budgets. Piccolo3 systems have been developed by TeamPiccolo at GeoSciences, University of Edinburgh in collaboration with colleagues at the LEO/IPL, University of Valencia and Alker Fibre Optics Ltd and Peak Design industry collaborators.

The need for  Piccolo3 spectral systems – a summary

Optical imaging of the Earth’s surface from satellites is now routine. A great number of providers supply images, with pixel sizes of a few metres, that are processed to red, green and blue (RGB) bands to simulate our (human) vision, Google Earth being a prime example. Our cognitive process and experiential learning can then be used to understand the image pixel content (perceived as colour) and relationships between pixels (perceived as recognisable objects). However, optical imaging (given an appropriate sensor system) can sense more spectral detail and/or span a far great wavelength range than we can. Specific absorption or reflectance features can be detected at wavelengths within and beyond the range of human vision. If light can be measured before it interacts with a surface and then measured after it has interacted with that surface, then it may be possible to infer some properties of the surface. As we have a reasonable understanding of the physics of the interaction of light with Earth surfaces, mathematical or computer models can be used to infer physical and chemical properties from measurements of reflected light. Then from these models, surface, or in some cases sub surface, composition can be inferred. The health, vigour and chemical composition of vegetation and other photosynthetic organisms deducted, for example. This model data can also be used to quantify surfaces, direct management interventions or assess change over time. However, when the optical (spectral) detail or wavelength range is greater than we can naturally perceive, or chemical or physical composition need to be measured and quantified, alternative approaches to human vision are needed. As satellite sensors record light ‘at sensor’, an account of the change to light as it passes from the Earth surface to the sensor is also needed. Optical sensors used near to the ground can be used to address these two issues (limits of human perception and effect of atmosphere on recorded data). However, the reflected light is also dependent on skylight impinging (illumination) on the surface at time of measurement.

The size of these near-ground optically sampled areas are far smaller than satellite image pixels, therefore they can be manually or physically sampled or destructively tested to quantify physical or chemical composition. Then relationships between these attributes and the optical data established or model outputs verified. In addition, instrument used to optically sample near to the ground can be moved both across Earth surfaces and vertically above them to sample different or larger areas. Therefore, Earth surface spatial variability can be sampled and as height above surface can be increased the effects of the atmosphere on reflected light can be better understood. In addition, as near ground instrument can also be held in place for extended periods, measurements of Earth surface change over time can be made. However, these instruments also need to record the skylight incident on the surface. For a more detailed discussion see Mac Arthur and Robinson (2015)

Piccolo spectral systems: by being modular, can be selected to match the spectral detail and range of interest; by being lightweight and portable, can manually or with suitable platforms (i.e. rotary-wing drones) be moved across the Earth surfaces and at increasing heights above them; by being weatherproof and able to record and store measurements, can measure Earth surface change over time; and by being dual-field-of-view, can measure surface radiance/exitance and irradiant skylight near simultaneously. Piccolo spectral systems can be used for: fixed-location long term logging, rotary-wing UAV spatial sampling, or as field spectrometers to advance Earth observation science and further understanding of Earth processes for the benefit of all or as EO or physics educational tools.


Mac Arthur, A. & Robinson, I. A critique of field spectroscopy and the challenges and opportunities it presents for remote sensing for agriculture, ecosystems, and hydrology. 14 Oct 2015, Proceedings of SPIE. SPIE, Vol. 9637. 11 p. 963705


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