The application of AISA hyperspectral images to the classification of vegetation communities and Natura 2000 habitats of Lower Narew Valley

Hubert Zieliński; Anna Jarocińska

doi:10.1117/12.2580532

14 October 2020 The application of AISA hyperspectral images to the classification of vegetation communities and Natura 2000 habitats of Lower Narew Valley

Hubert Zieliński, Anna Jarocińska

Author Affiliations +

Proceedings Volume 11581, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2020; 115810Z (2020) https://doi.org/10.1117/12.2580532
Event: Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2020, 2020, Wilga, Poland

Abstract

The aim of the study was to evaluate the application of AISA (Airborne Imaging Spectrometer for Applications) hyperspectral images for the classification of vegetation communities and Natura 2000 habitats of the Lower Narew Valley. The AISA Eagle data were acquired in 129 bands in the 400-970 nm range and 1 m spatial resolution. The provided data were previously radiometrically and geometrically corrected. During the pre-processing Minimum Noise Fraction transformation was done and first 20 bands were selected. Basing on field reference data received from the Institute of Technology and Life Sciences, the optimal method of determining training and verification polygons was determined. Using the Support Vector Machine (SVM) algorithm, the image was classified into 11 classes, including two Natura 2000 habitats - xeric sand calcareous grasslands (6120) and lowland hay meadows (6510). The classification result was verified using the reference data. The overall accuracy was equal 85.69% and Kappa coefficient 0.84. Then, a post-classification map of the studied area was prepared.

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Hubert Zieliński and Anna Jarocińska "The application of AISA hyperspectral images to the classification of vegetation communities and Natura 2000 habitats of Lower Narew Valley", Proc. SPIE 11581, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2020, 115810Z (14 October 2020); https://doi.org/10.1117/12.2580532

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KEYWORDS

Vegetation

Image classification

Hyperspectral imaging

Environmental monitoring

Remote sensing

Data processing

Image processing

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