Udali, Alberto and Lingua, Emanuele and Persson, Henrik
(2021).
Assessing Forest Type and Tree Species Classification Using Sentinel-1 C-Band SAR Data in Southern Sweden.
Remote Sensing. 13
, 3237
[Research article]
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Abstract
The multitemporal acquisition of images from the Sentinel-1 satellites allows continuous monitoring of a forest. This study focuses on the use of multitemporal C-band synthetic aperture radar (SAR) data to assess the results for forest type (FTY), between coniferous and deciduous forest, and tree species (SPP) classification. We also investigated the temporal stability through the use of backscatter from multiple seasons and years of acquisition. SAR acquisitions were pre-processed, histogram-matched, smoothed, and temperature-corrected. The normalized average backscatter was extracted for interpreted plots and used to train Random Forest models. The classification results were then validated with field plots. A principal component analysis was tested to reduce the dimensionality of the explanatory variables, which generally improved the results. Overall, the FTY classifications were promising, with higher accuracies (OA of 0.94 and K = 0.86) than the SPP classification (OA of 0.66 and K = 0.54). The use of merely winter images (OA = 0.89) reached, on average, results that were almost as good as those using of images from the entire year. The use of images from a single winter season reached a similar result (OA = 0.87). We conclude that multiple Sentinel-1 images acquired in winter conditions are feasible to classify forest types in a hemi-boreal Swedish forest.
Authors/Creators: | Udali, Alberto and Lingua, Emanuele and Persson, Henrik | ||||||
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Title: | Assessing Forest Type and Tree Species Classification Using Sentinel-1 C-Band SAR Data in Southern Sweden | ||||||
Series Name/Journal: | Remote Sensing | ||||||
Year of publishing : | 2021 | ||||||
Volume: | 13 | ||||||
Article number: | 3237 | ||||||
Number of Pages: | 20 | ||||||
Publisher: | MDPI | ||||||
Language: | English | ||||||
Publication Type: | Research article | ||||||
Article category: | Scientific peer reviewed | ||||||
Version: | Published version | ||||||
Copyright: | Creative Commons: Attribution 4.0 | ||||||
Full Text Status: | Public | ||||||
Subjects: | (A) Swedish standard research categories 2011 > 2 Engineering and Technology > 207 Environmental Engineering > Remote Sensing | ||||||
Keywords: | SAR, backscatter, forest classification, C-band, Sentinel-1 | ||||||
URN:NBN: | urn:nbn:se:slu:epsilon-p-113468 | ||||||
Permanent URL: | http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-113468 | ||||||
Additional ID: |
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ID Code: | 25279 | ||||||
Faculty: | S - Faculty of Forest Sciences | ||||||
Department: | (S) > Dept. of Forest Resource Management (NL, NJ) > Dept. of Forest Resource Management | ||||||
Deposited By: | SLUpub Connector | ||||||
Deposited On: | 09 Sep 2021 09:25 | ||||||
Metadata Last Modified: | 09 Sep 2021 09:31 |
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