Classification of Tundra Vegetation in the Krkonoše Mts. National Park Using APEX, AISA Dual and Sentinel-2A Data. Issue 1 (1st January 2017)

• Record Type: Journal Article
• Authors: Kupková, Lucie; Červená, Lucie; Suchá, Renáta; Jakešová, Lucie; Zagajewski, Bogdan; Březina, Stanislav; Albrechtová, Jana
• Is Part Of: European journal of remote sensing. Volume 50:Issue 1(2017)
• Page Start: 29
• Page End: 46
• Publication Date: 2017-01-01
• Subjects: Tundra vegetation -- The Krkonoše Mountains -- Per-pixel classification -- Object-based classification -- Hyperspectral data -- Sentiel-2A; Remote sensing -- Periodicals; Remote sensing; Electronic journals; Periodicals; 621.3678
• DOI: 10.1080/22797254.2017.1274573
• Languages: English
• ISSNs: 2279-7254

Abstract

ABSTRACT: The aim of this study was to evaluate and compare suitability of aerial hyperspectral data (AISA Dual and APEX sensors) and Sentinel-2A data for classification of tundra vegetation cover in the Krkonoše Mts. National Park. We compared classification results (accuracy, maps) of pixel-based (Maximum Likelihood, Suport Vector Machine and Neural Net) and object-based approaches. The best classification results (overall accuracy 84.3%, Kappa coefficient = 0.81) were achieved for AISA Dual data using per-pixel SVM classifier for 40 PCA bands. The best classification results of APEX though were only 1.7 percentage points lower. To get comparable results for Sentinel-2A classification legend had to be simplified. With the simplified legend the accuracy using MLC classifier reached 77.7%.