Errors related to the automatized satellite-based change detection of boreal forests in Finland

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http://hdl.handle.net/10138/336902

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Timo P. Pitkänen, Laura Sirro, Lauri Häme, Tuomas Häme, Markus Törmä, Annika Kangas. Errors related to the automatized satellite-based change detection of boreal forests in Finland. International Journal of Applied Earth Observation and Geoinformation 86 (2020), 102011, ISSN 0303-2434. https://doi.org/10.1016/j.jag.2019.102011

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Title: Errors related to the automatized satellite-based change detection of boreal forests in Finland
Author: Pitkänen, Timo P.; Sirro, Laura; Häme, Lauri; Häme, Tuomas; Törmä, Markus; Kangas, Annika
Publisher: ScienceDirect
Date: 2020
Language: en
Belongs to series: International Journal of Applied Earth Observation and Geoinformation 86 (2020)
ISSN: 1569-8432
DOI: https://doi.org/10.1016/j.jag.2019.102011
URI: http://hdl.handle.net/10138/336902
Abstract: The majority of the boreal forests in Finland are regularly thinned or clear-cut, and these actions are regulated by the Forest Act. To generate a near-real time tool for monitoring management actions, an automatic change detection modelling chain was developed using Sentinel-2 satellite images. In this paper, we focus mainly on the error evaluation of this automatized workflow to understand and mitigate incorrect change detections. Validation material related to clear-cut, thinned and unchanged areas was collected by visual evaluation of VHR images, which provided a feasible and relatively accurate way of evaluating forest characteristics without a need for prohibitively expensive fieldwork. This validation data was then compared to model predictions classified in similar change categories. The results indicate that clear-cuts can be distinguished very reliably, but thinned stands exhibit more variation. For thinned stands, coverage of broadleaved trees and detections from certain single dates were found to correlate with the success of the modelling results. In our understanding, this relates mainly to image quality regarding haziness and translucent clouds. However, if the growing season is short and cloudiness frequent, there is a clear trade-off between the availability of good-quality images and their preferred annual span. Gaining optimal results therefore depends both on the targeted change types, and the requirements of the mapping frequency.
Description: Highlights • Forest changes were automatically modelled from multitemporal Sentinel-2 images. • Errors were evaluated based on visually interpreted VHR images. • Extraction of clear-cuts was accurate whereas thinnings had more variation. • Image quality and translucent clouds had most significant effect on errors. • Results were regarded applicable for operational change monitoring.
Subject: change monitoring
forest management
accuracy assessment
errors
error evaluation
evaluation
visual evaluation
automation
satellites
satellite-based
satellite images
detection
satellite-based detection
forests
boreal forests
real-time tool
monitoring
management
automatic change detection modelling chain
Sentinel-2
automatized workflow
change detections
VHR
VHR images
clear-cut
thinned
unchanged
forest characteristics
evaluation of forest characteristics
validation data
classification
change categories
trees
broadleaved trees
image quality
clouds
mapping
mapping frequency
trade-off
cloud cover
growing season
modeling
prediction
material
remote sensing
Earth & Environmental Sciences
Finland
Subject (ysa): muutosten seuranta
metsän hoito
tarkkuuden arviointi
virheet
virheiden arviointi
arviointi
visuaalinen arviointi
automaatio
satelliitit
kaukokartoitus
tunnistus
tunnistaminen
metsät
boreaaliset metsät
reaaliaikaisuus
reaaliaikainen työkalu
monitorointi
hallinta
muutosten tunnistaminen
metsien ominaisuudet
luokittelu
muutoskategoriat
puut
kuvanlaatu
pilvet
pilvipeite
kartoitus
kartoitusfrekvenssi
kasvukausi
mallintaminen
ennustaminen
materiaali
Suomi
Rights: CC BY 4.0


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