Harri Ojanen

Remote Sensing of 3-D Geometry and Surface Moisture of a Peat Production Area Using Hyperspectral Frame Cameras in Visible to Short-Wave Infrared Spectral Ranges Onboard a Small Unmanned Airborne Vehicle (UAV)

Miniaturized hyperspectral imaging sensors are becoming available to small unmanned airborne vehicle (UAV) platforms. Imaging concepts based on frame format offer an attractive alternative to conventional hyperspectral pushbroom scanners because they enable enhanced processing and interpretation potential by allowing for acquisition of the 3-D geometry of the object and multiple object views together with the hyperspectral reflectance signatures. The objective of this investigation was to study the performance of novel visible and near-infrared (VNIR) and short-wave infrared (SWIR) hyperspectral frame cameras based on a tunable Fabry-Pérot interferometer (FPI) in measuring a 3-D digital surface model and the surface moisture of a peat production area. UAV image blocks were captured with ground sample distances (GSDs) of 15, 9.5, and 2.5 cm with the SWIR, VNIR, and consumer RGB cameras, respectively. Georeferencing showed consistent behavior, with accuracy levels better than GSD for the FPI cameras. The best accuracy in moisture estimation was obtained when using the reflectance difference of the SWIR band at 1246 nm and of the VNIR band at 859 nm, which gave a root mean square error (rmse) of 5.21 pp (pp is the mass fraction in percentage points) and a normalized rmse of 7.61%. The results are encouraging, indicating that UAV-based remote sensing could significantly improve the efficiency and environmental safety aspects of peat production.

Short-wave infrared (SWIR) spectral imager based on Fabry-Perot interferometer for remote sensing

VTT Technical Research Centre of Finland has developed a spectral imager for short-wave infrared (SWIR) wavelength range. The spectral imager is based on a tunable Fabry-Perot interferometer (FPI) accompanied by a commercial InGaAs Camera. The FPI consists of two dielectric coated mirrors separated by a tunable air gap. Tuning of the air gap tunes also transmitted wavelength and therefore FPI acts as a tunable band bass filter. The FPI is piezo-actuated and it uses three piezo-actuators in a closed capacitive feedback loop for air gap tuning. The FPI has multiple order transmission bands, which limit free spectral range. Therefore spectral imager contains two FPI in a stack, to make possible to cover spectral range of 1000 – 1700 nm. However, in the first tests imager was used with one FPI and spectral range was limited to 1100-1600 nm. The spectral resolution of the imager is approximately 15 nm (FWHM). Field of view (FOV) across the flight direction is 30 deg. Imaging resolution of the spectral imager is 256 x 320 pixels. The focal length of the optics is 12 mm and F-number is 3.2. This imager was tested in summer 2014 in an unmanned aerial vehicle (UAV) and therefore a size and a mass of the imager were critical. Total mass of the imager is approximately 1200 grams. In test campaign the spectral imager will be used for forest and agricultural imaging. In future, because results of the UAV test flights are promising, this technology can be applied to satellite applications also.

Assessment of Classifiers and Remote Sensing Features of Hyperspectral Imagery and Stereo-Photogrammetric Point Clouds for Recognition of Tree Species in a Forest Area of High Species Diversity

Recognition of tree species and geospatial information on tree species composition is essential for forest management. In this study, tree species recognition was examined using hyperspectral imagery from visible to near-infrared (VNIR) and short-wave infrared (SWIR) camera sensors in combination with a 3D photogrammetric canopy surface model based on RGB camera stereo-imagery. An arboretum with a diverse selection of 26 tree species from 14 genera was used as a test area. Aerial hyperspectral imagery and high spatial resolution photogrammetric color imagery were acquired from the test area using unmanned aerial vehicle (UAV) borne sensors. Hyperspectral imagery was processed to calibrated reflectance mosaics and was tested along with the mosaics based on original image digital number values (DN). Two alternative classifiers, a k nearest neighbor method (k-nn), combined with a genetic algorithm and a random forest method, were tested for predicting the tree species and genus, as well as for selecting an optimal set of remote sensing features for this task. The combination of VNIR, SWIR, and 3D features performed better than any of the data sets individually. Furthermore, the calibrated reflectance values performed better compared to uncorrected DN values. These trends were similar with both tested classifiers. Of the classifiers, the k-nn combined with the genetic algorithm provided consistently better results than the random forest algorithm. The best result was thus achieved using calibrated reflectance features from VNIR and SWIR imagery together with 3D point cloud features; the proportion of correctly-classified trees was 0.823 for tree species and 0.869 for tree genus.

Visible spectral imager for occultation and nightglow (VISION) for the PICASSO Mission

PICASSO - A PICo-satellite for Atmospheric and Space Science Observations is an ESA project led by the Belgian Institute for Space Aeronomy, in collaboration with VTT, Clyde Space Ltd. (UK), and the Centre Spatial de Liège (BE). VTT Technical Research Centre of Finland Ltd. will deliver the Visible Spectral Imager for Occultation and Nightglow (VISION) for the PICASSO mission. The VISION targets primarily the observation of the Earths atmospheric limb during orbital Sun occultation. By assessing the radiation absorption in the Chappuis band for different tangent altitudes, the vertical profile of the ozone is retrieved. A secondary objective is to measure the deformation of the solar disk so that stratospheric and mesospheric temperature profiles are retrieved by inversion of the refractive raytracing problem. Finally, occasional full spectral observations of polar auroras are also foreseen. The VISION design realized with commercial of the shelf (CoTS) parts is described. The VISION instrument is small, lightweight (~500 g), Piezo-actuated Fabry-Perot Interferometer (PFPI) tunable spectral imager operating in the visible and near-infrared (430 – 800 nm). The spectral resolution over the whole wavelength range will be better than 10 nm @ FWHM. VISION has is 2.5° x 2.5° total field of view and it delivers maximum 2048 x 2048 pixel spectral images. The sun image size is around 0.5° i.e. ~500 pixels. To enable fast spectral data image acquisition VISION can be operated with programmable image sizes. VTT has previously developed PFPI tunable filter based AaSI Spectral Imager for the Aalto-1 Finnish CubeSat. In VISION the requirements of the spectral resolution and stability are tighter than in AaSI. Therefore the optimization of the of the PFPI gap control loop for the operating temperature range and vacuum conditions has to be improved. VISION optical, mechanical and electrical design is described.

MEMS FPI-based smartphone hyperspectral imager

This paper demonstrates a mobile phone- compatible hyperspectral imager based on a tunable MEMS Fabry-Perot interferometer. The realized iPhone 5s hyperspectral imager (HSI) demonstrator utilizes MEMS FPI tunable filter for visible-range, which consist of atomic layer deposited (ALD) Al2O3/TiO2-thin film Bragg reflectors. Characterization results for the mobile phone hyperspectral imager utilizing MEMS FPI chip optimized for 500 nm is presented; the operation range is λ = 450 – 550 nm with FWHM between 8 – 15 nm. Also a configuration of two cascaded FPIs (λ = 500 nm and λ = 650 nm) combined with an RGB colour camera is presented. With this tandem configuration, the overall wavelength tuning range of MEMS hyperspectral imagers can be extended to cover a larger range than with a single FPI chip. The potential applications of mobile hyperspectral imagers in the vis-NIR range include authentication, counterfeit detection and potential health/wellness and food sensing applications.

PICASSO VISION instrument design, engineering model test results, and flight model development status

PICASSO - A PICo-satellite for Atmospheric and Space Science Observations is an ESA project led by the Belgian Institute for Space Aeronomy, in collaboration with VTT Technical Research Centre of Finland Ltd, Clyde Space Ltd. (UK) and Centre Spatial de Liège (BE). The test campaign for the engineering model of the PICASSO VISION instrument, a miniaturized nanosatellite spectral imager, has been successfully completed. The test results look very promising. The proto-flight model of VISION has also been successfully integrated and it is waiting for the final integration to the satellite platform.

Hand-held MEMS hyperspectral imager for VNIR mobile applications

This paper presents a novel miniaturized hand-held hyperspectral imager for VNIR range of λ = 600 – 900 nm based on MEMS Fabry-Perot interferometer (MFPI) technology. In recent years, tunable MFPI optical filters have been utilized to demonstrate sensors for mobile applications, including CO2 smartphone sensor for mid infra-red region and hyperspectral iPhone for visible spectrum. This hand-held sensor module targets the VNIR range in order to enable food sensing, while utilizing low-cost camera technology to enable potential volume scalability for future sensing applications. The sensor module is wirelessly connected to a mobile device, which enables further application algorithms development and cloudbased solutions.

VTT's Fabry-Perot interferometer technologies for hyperspectral imaging and mobile sensing applications

VTT’s Fabry-Perot interferometers (FPI) technology enables creation of small and cost-efficient microspectrometers and hyperspectral imagers – these robust and light-weight sensors are currently finding their way into a variety of novel applications, including emerging medical products, automotive sensors, space instruments and mobile sensing devices. This presentation gives an overview of our core FPI technologies with current advances in generation of novel sensing applications including recent mobile technology demonstrators of a hyperspectral iPhone and a mobile phone CO2 sensor, which aim to advance mobile spectroscopic sensing.