Using Long-Term SAR Backscatter Data to Monitor Post-Fire Vegetation Recovery in Tundra Environment
Wildfires could have a strong impact on tundra environment by combusting surface vegetation and soil organic matter. For surface vegetation, many years are required to recover to pre-fire level. In this paper, by using C-band (VV/HV polarization) and L-band (HH polarization) synthetic aperture radar...
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ftdoajarticles:oai:doaj.org/article:90e633267ab04f6da0dcdf17eef273e5 2023-05-15T14:54:20+02:00 Using Long-Term SAR Backscatter Data to Monitor Post-Fire Vegetation Recovery in Tundra Environment Zhiwei Zhou Lin Liu Liming Jiang Wanpeng Feng Sergey V. Samsonov 2019-09-01T00:00:00Z https://doi.org/10.3390/rs11192230 https://doaj.org/article/90e633267ab04f6da0dcdf17eef273e5 EN eng MDPI AG https://www.mdpi.com/2072-4292/11/19/2230 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs11192230 https://doaj.org/article/90e633267ab04f6da0dcdf17eef273e5 Remote Sensing, Vol 11, Iss 19, p 2230 (2019) arctic tundra fire vegetation recovery c- and l-band sar sar backscatter Science Q article 2019 ftdoajarticles https://doi.org/10.3390/rs11192230 2022-12-30T20:28:42Z Wildfires could have a strong impact on tundra environment by combusting surface vegetation and soil organic matter. For surface vegetation, many years are required to recover to pre-fire level. In this paper, by using C-band (VV/HV polarization) and L-band (HH polarization) synthetic aperture radar (SAR) images acquired before and after fire from 2002 to 2016, we investigated vegetation change affected by the Anaktuvuk River Fire in Arctic tundra environment. Compared to the unburned areas, C- and L-band SAR backscatter coefficients increased by up to 5.5 and 4.4 dB in the severely burned areas after the fire. Then past 5 years following the fire, the C-band SAR backscatter differences decreased to pre-fire level between the burned and unburned areas, suggesting that vegetation coverage in burned sites had recovered to the unburned level. This duration is longer than the 3-year recovery suggested by optical-based Normalized Difference Vegetation Index (NDVI) observations. While for the L-band SAR backscatter after 10-year recovery, about 2 dB higher was still found in the severely burned area, compared to the unburned area. The increased roughness of the surface is probably the reason for such sustained differences. Our analysis implies that long records of space-borne SAR backscatter can monitor post-fire vegetation recovery in Arctic tundra environment and complement optical observations. Article in Journal/Newspaper Arctic Tundra Directory of Open Access Journals: DOAJ Articles Arctic Remote Sensing 11 19 2230 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
arctic tundra fire vegetation recovery c- and l-band sar sar backscatter Science Q |
spellingShingle |
arctic tundra fire vegetation recovery c- and l-band sar sar backscatter Science Q Zhiwei Zhou Lin Liu Liming Jiang Wanpeng Feng Sergey V. Samsonov Using Long-Term SAR Backscatter Data to Monitor Post-Fire Vegetation Recovery in Tundra Environment |
topic_facet |
arctic tundra fire vegetation recovery c- and l-band sar sar backscatter Science Q |
description |
Wildfires could have a strong impact on tundra environment by combusting surface vegetation and soil organic matter. For surface vegetation, many years are required to recover to pre-fire level. In this paper, by using C-band (VV/HV polarization) and L-band (HH polarization) synthetic aperture radar (SAR) images acquired before and after fire from 2002 to 2016, we investigated vegetation change affected by the Anaktuvuk River Fire in Arctic tundra environment. Compared to the unburned areas, C- and L-band SAR backscatter coefficients increased by up to 5.5 and 4.4 dB in the severely burned areas after the fire. Then past 5 years following the fire, the C-band SAR backscatter differences decreased to pre-fire level between the burned and unburned areas, suggesting that vegetation coverage in burned sites had recovered to the unburned level. This duration is longer than the 3-year recovery suggested by optical-based Normalized Difference Vegetation Index (NDVI) observations. While for the L-band SAR backscatter after 10-year recovery, about 2 dB higher was still found in the severely burned area, compared to the unburned area. The increased roughness of the surface is probably the reason for such sustained differences. Our analysis implies that long records of space-borne SAR backscatter can monitor post-fire vegetation recovery in Arctic tundra environment and complement optical observations. |
format |
Article in Journal/Newspaper |
author |
Zhiwei Zhou Lin Liu Liming Jiang Wanpeng Feng Sergey V. Samsonov |
author_facet |
Zhiwei Zhou Lin Liu Liming Jiang Wanpeng Feng Sergey V. Samsonov |
author_sort |
Zhiwei Zhou |
title |
Using Long-Term SAR Backscatter Data to Monitor Post-Fire Vegetation Recovery in Tundra Environment |
title_short |
Using Long-Term SAR Backscatter Data to Monitor Post-Fire Vegetation Recovery in Tundra Environment |
title_full |
Using Long-Term SAR Backscatter Data to Monitor Post-Fire Vegetation Recovery in Tundra Environment |
title_fullStr |
Using Long-Term SAR Backscatter Data to Monitor Post-Fire Vegetation Recovery in Tundra Environment |
title_full_unstemmed |
Using Long-Term SAR Backscatter Data to Monitor Post-Fire Vegetation Recovery in Tundra Environment |
title_sort |
using long-term sar backscatter data to monitor post-fire vegetation recovery in tundra environment |
publisher |
MDPI AG |
publishDate |
2019 |
url |
https://doi.org/10.3390/rs11192230 https://doaj.org/article/90e633267ab04f6da0dcdf17eef273e5 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Tundra |
genre_facet |
Arctic Tundra |
op_source |
Remote Sensing, Vol 11, Iss 19, p 2230 (2019) |
op_relation |
https://www.mdpi.com/2072-4292/11/19/2230 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs11192230 https://doaj.org/article/90e633267ab04f6da0dcdf17eef273e5 |
op_doi |
https://doi.org/10.3390/rs11192230 |
container_title |
Remote Sensing |
container_volume |
11 |
container_issue |
19 |
container_start_page |
2230 |
_version_ |
1766326056881487872 |