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Forest Community Mapping Using Hyperspectral (CHRIS/PROBA) and Sentinel-2 Multispectral Images

Głowienka Ewa, Zembol Nicole

Geomatics and Environmental Engineering

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2022

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Vol. 16, no. 4

103--117

EN

The possibility to use hyperspectral images (CHRIS/PROBA) and multispectral images (Sentinel-2) in the classification of forest communities is assessed in this article. The pre-processing of CHRIS/PROBA image included: noise reduction, radiometric correction, atmospheric correction, geometric correction. Due to MNF transformation the number of the hyperspectral image channels was reduced (to 10 channels) and smiling errors were removed. Sentinel-2 image (level 2A) did not require pre-processing. Three tree genera occurring in the study area were selected for the classification: pine (Pinus), alder (Alnus) and birch (Betula). Image classification was carried out with three methods: SAM (Spectral Angle Mapper ), MTMF (Mixture Tuned Matched Filtering), SVM (Support Vector Machine). For the CHRIS/PROBA image, the algorithm SVM turned out to be the best. Its overall accuracy (OA) was 72%. The poorest result (OA = 52%) was for the MTMF classifier. In the classification of Sentinel-2 multispectral image the best result was for the MTMF method: OA = 82%, kappa coefficient 0.7. For other methods, the overall accuracy exceeded 65%. Among the classified genera, the highest producer’s accuracy was obtained for pine (PA = 96%), and the broad-leaf genera: alder and birch had PA ranging from 42% to 85%.

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Gas leaks detection using passive thermal infrared hyperspectral imaging

Lagueux P., Tremblay P., Morton V., Chamberland M., Farley V., Kastek M., Firmanty K.

Measurement Automation Monitoring

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2017

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Vol. 63, No. 2

65--68

EN

There are many types of natural gas fields including shale formations which are common especially in the St-Lawrence Valley (Canada). Since methane (CH4), the major component of shale gas, is odorless, colorless and highly flammable, in addition of being a greenhouse gas, methane emanations and/or leaks are important to consider for both safety and environmental reasons. On this regard, passive remote sensing represents an interesting approach since it allows characterization of large areas from a safe location. In order to illustrate the potential of passive thermal infrared hyperspectral imaging for research on natural gas, imaging was carried out on a shale gas leak that unexpectedly happened during a geological survey near Hospital Enfant-Jesus (Québec City, Canada) in December 2016. Quantitative methane imaging was carried out based on its unique infrared spectral signature. The results show how this novel technique could be used for advanced research on shale gases.

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Hyperspectral LWIR measurements with imaging diffraction grating spectrometer and uncooled thermal camera

Olbrycht R., Rzeszotarski D.

Measurement Automation Monitoring

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2015

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Vol. 61, No. 6

169--172

EN

This paper demonstrates how to perform hyperspectral infrared measurements with uncooled thermal camera and imaging spectrometer. Such thermal cameras are sensitive to wavelengths in the range of 7 – 14 µm (LWIR). There is a description of a diffraction grating based spectrometer with Czerny-Turner optical configuration. To perform hyperspectral acquisition of thermograms it is required to have the camera synchronized with spectrometer, so that recorded frames correspond to known wavelengths. For this purpose the dedicated software was developed and it is also described in this paper, with its operation algorithm. There is a problem of thermal camera drift, and this paper proposes the solution to deal with it. Moreover a description how to obtain transmission plot and exemplary results is presented with the description of measurement rig. In addition, noise related issues are covered and discussed.