Boreal Forest Snow Damage Mapping Using Multi-Temporal Sentinel-1 Data

Natural disturbances significantly influence forest ecosystem services and biodiversity. Accurate delineation and early detection of areas affected by disturbances are critical for estimating extent of damage, assessing economical influence and guiding forest management activities. In this study we...

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Bibliographic Details
Published in:Remote Sensing
Main Authors: Erkki Tomppo, Oleg Antropov, Jaan Praks
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2019
Subjects:
boreal forest
snow damage
synthetic aperture radar
Sentinel-1
support vector machine
improved k-NN
genetic algorithm
Science
Q
The Sentinel
Northern Finland
Online Access:https://doi.org/10.3390/rs11040384
https://doaj.org/article/782caa08f169441bae9d13a81450b510
Description
Summary:Natural disturbances significantly influence forest ecosystem services and biodiversity. Accurate delineation and early detection of areas affected by disturbances are critical for estimating extent of damage, assessing economical influence and guiding forest management activities. In this study we focus on snow load damage detection from C-Band SAR images. Snow damage is one of the least studied forest damages, which is getting more common due to current climate trends. The study site was located in the southern part of Northern Finland and the SAR data were represented by the time series of C-band SAR scenes acquired by the Sentinel-1 sensor. Methods used in the study included improved k nearest neighbour method, logistic regression analysis and support vector machine classification. Snow damage recordings from a large snow damage event that took place in Finland during late 2018 were used as reference data. Our results showed an overall detection accuracy of 90%, indicating potential of C-band SAR for operational use in snow damage mapping. Additionally, potential of multitemporal Sentinel-1 data in estimating growing stock volume in damaged forest areas were carried out, with obtained results indicating strong potential for estimating the overall volume of timber within the affected areas. The results and research questions for further studies are discussed.

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