Mapping Tree Mortality Caused by Siberian Silkmoth Outbreak Using Sentinel-2 Remote Sensing Data
The Siberian silkmoth is one of the most dangerous coniferous forests pests. Siberian silkmoth outbreaks cause massive defoliation and subsequent forest fires over vast areas. Remote forest disturbance assessments performed after an outbreak make it possible to assess carbon emissions and the potent...
Published in: | Forests |
---|---|
Main Authors: | , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
MDPI AG
2023
|
Subjects: | |
Online Access: | https://doi.org/10.3390/f14122436 https://doaj.org/article/7020f52d1af4434ca381d6ce11316671 |
id |
ftdoajarticles:oai:doaj.org/article:7020f52d1af4434ca381d6ce11316671 |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:7020f52d1af4434ca381d6ce11316671 2024-01-21T10:07:53+01:00 Mapping Tree Mortality Caused by Siberian Silkmoth Outbreak Using Sentinel-2 Remote Sensing Data Olga A. Slinkina Pavel V. Mikhaylov Svetlana M. Sultson Denis A. Demidko Natalia P. Khizhniak Andrey I. Tatarintsev 2023-12-01T00:00:00Z https://doi.org/10.3390/f14122436 https://doaj.org/article/7020f52d1af4434ca381d6ce11316671 EN eng MDPI AG https://www.mdpi.com/1999-4907/14/12/2436 https://doaj.org/toc/1999-4907 doi:10.3390/f14122436 1999-4907 https://doaj.org/article/7020f52d1af4434ca381d6ce11316671 Forests, Vol 14, Iss 12, p 2436 (2023) Siberian silkmoth damaged stands remote sensing spectral indices Plant ecology QK900-989 article 2023 ftdoajarticles https://doi.org/10.3390/f14122436 2023-12-24T01:37:18Z The Siberian silkmoth is one of the most dangerous coniferous forests pests. Siberian silkmoth outbreaks cause massive defoliation and subsequent forest fires over vast areas. Remote forest disturbance assessments performed after an outbreak make it possible to assess carbon emissions and the potential for natural regeneration, estimate forest fire danger, and reveal the need to implement forest management practices. The goal of the present research was to investigate the use of modern satellite imagery of medium spatial resolution to estimate the percentage of dead trees in a given area. The subject of this study is the Siberian silkmoth outbreak that occurred in 2018–2020 and covered 42 thousand ha in the Irbey region of the Krasnoyarsk Krai. Imagery from the Sentinel-2/MSI sensor was used to calculate a number of spectral indices for images received before and after the outbreak. Field study data were used to create regression models relating the index values to the percentage of dead trees. A number of spectral indices, such as NDVI, dNDVI, NBR, dNBR, NDMI, EVI, and TCG, were used. As a result, spectral indices based on the data from NIR/SWIR bands (NBR, NDMI, dNBR) demonstrated the best correlations with field-measured tree mortality. Therefore, these indices may be used to accurately estimate the percentage of dead trees by remote sensing data. The best was the NBR index with an R 2 equal to 0.87, and the lowest RMSE and MAE errors. Consequently, Sentinel-2 imagery can be successfully used for tree mortality assessment over large inaccessible areas disturbed by Siberian silkmoth outbreaks at a relatively low cost. Article in Journal/Newspaper Krasnoyarsk Krai Directory of Open Access Journals: DOAJ Articles The Sentinel ENVELOPE(73.317,73.317,-52.983,-52.983) Forests 14 12 2436 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Siberian silkmoth damaged stands remote sensing spectral indices Plant ecology QK900-989 |
spellingShingle |
Siberian silkmoth damaged stands remote sensing spectral indices Plant ecology QK900-989 Olga A. Slinkina Pavel V. Mikhaylov Svetlana M. Sultson Denis A. Demidko Natalia P. Khizhniak Andrey I. Tatarintsev Mapping Tree Mortality Caused by Siberian Silkmoth Outbreak Using Sentinel-2 Remote Sensing Data |
topic_facet |
Siberian silkmoth damaged stands remote sensing spectral indices Plant ecology QK900-989 |
description |
The Siberian silkmoth is one of the most dangerous coniferous forests pests. Siberian silkmoth outbreaks cause massive defoliation and subsequent forest fires over vast areas. Remote forest disturbance assessments performed after an outbreak make it possible to assess carbon emissions and the potential for natural regeneration, estimate forest fire danger, and reveal the need to implement forest management practices. The goal of the present research was to investigate the use of modern satellite imagery of medium spatial resolution to estimate the percentage of dead trees in a given area. The subject of this study is the Siberian silkmoth outbreak that occurred in 2018–2020 and covered 42 thousand ha in the Irbey region of the Krasnoyarsk Krai. Imagery from the Sentinel-2/MSI sensor was used to calculate a number of spectral indices for images received before and after the outbreak. Field study data were used to create regression models relating the index values to the percentage of dead trees. A number of spectral indices, such as NDVI, dNDVI, NBR, dNBR, NDMI, EVI, and TCG, were used. As a result, spectral indices based on the data from NIR/SWIR bands (NBR, NDMI, dNBR) demonstrated the best correlations with field-measured tree mortality. Therefore, these indices may be used to accurately estimate the percentage of dead trees by remote sensing data. The best was the NBR index with an R 2 equal to 0.87, and the lowest RMSE and MAE errors. Consequently, Sentinel-2 imagery can be successfully used for tree mortality assessment over large inaccessible areas disturbed by Siberian silkmoth outbreaks at a relatively low cost. |
format |
Article in Journal/Newspaper |
author |
Olga A. Slinkina Pavel V. Mikhaylov Svetlana M. Sultson Denis A. Demidko Natalia P. Khizhniak Andrey I. Tatarintsev |
author_facet |
Olga A. Slinkina Pavel V. Mikhaylov Svetlana M. Sultson Denis A. Demidko Natalia P. Khizhniak Andrey I. Tatarintsev |
author_sort |
Olga A. Slinkina |
title |
Mapping Tree Mortality Caused by Siberian Silkmoth Outbreak Using Sentinel-2 Remote Sensing Data |
title_short |
Mapping Tree Mortality Caused by Siberian Silkmoth Outbreak Using Sentinel-2 Remote Sensing Data |
title_full |
Mapping Tree Mortality Caused by Siberian Silkmoth Outbreak Using Sentinel-2 Remote Sensing Data |
title_fullStr |
Mapping Tree Mortality Caused by Siberian Silkmoth Outbreak Using Sentinel-2 Remote Sensing Data |
title_full_unstemmed |
Mapping Tree Mortality Caused by Siberian Silkmoth Outbreak Using Sentinel-2 Remote Sensing Data |
title_sort |
mapping tree mortality caused by siberian silkmoth outbreak using sentinel-2 remote sensing data |
publisher |
MDPI AG |
publishDate |
2023 |
url |
https://doi.org/10.3390/f14122436 https://doaj.org/article/7020f52d1af4434ca381d6ce11316671 |
long_lat |
ENVELOPE(73.317,73.317,-52.983,-52.983) |
geographic |
The Sentinel |
geographic_facet |
The Sentinel |
genre |
Krasnoyarsk Krai |
genre_facet |
Krasnoyarsk Krai |
op_source |
Forests, Vol 14, Iss 12, p 2436 (2023) |
op_relation |
https://www.mdpi.com/1999-4907/14/12/2436 https://doaj.org/toc/1999-4907 doi:10.3390/f14122436 1999-4907 https://doaj.org/article/7020f52d1af4434ca381d6ce11316671 |
op_doi |
https://doi.org/10.3390/f14122436 |
container_title |
Forests |
container_volume |
14 |
container_issue |
12 |
container_start_page |
2436 |
_version_ |
1788698506862526464 |