Spatio-temporal patterns of optimal Landsat data for burn severity index calculations: Implications for high northern latitudes wildfire research

Chen, Dong; Fu, Cheng; Hall, Joanne V.; Hoy, Elizabeth; Loboda, Tatiana V.

doi:10.1016/j.rse.2021.112393

Cited by 16 publications

(13 citation statements)

References 54 publications

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“…More generally, the hybrid composite method used here demonstrates that rapidly evolving technologies may help overcome certain challenges for using remote sensing to assess fire severity in northern latitudes. One challenge of the paired‐scene approach is obtaining high‐quality Landsat scenes with similar phenological timing (Chen et al., 2021). Cloud cover and smoke is a common issue for acquiring imagery in boreal regions, and cloud shadows can have greater effects due to low solar angle at high latitudes (Verbyla et al., 2008).…”

Section: Discussionmentioning

confidence: 99%

“…We tested model skill by comparing observed and predicted CBI using linear regression for each severity metric, reporting the coefficient of determination (i.e. R 2 of linear regression (Chen et al, 2021). Therefore, we also included analyses restricted to fires from the 2002-2019 time period, such that all pre-and post-fire imagery were acquired from 2001 onward.…”

Section: Discussionmentioning

confidence: 99%

“…Availability of Landsat imagery began consistently increasing in boreal regions in 2001 with both Landsat 5 and 7 satellites operational (note, Landsat 7 was launched in 1999 nearly doubling image availability but Landsat 5 TM acquisition declined markedly for 1 year in 2000 in boreal regions, cf. Sulla‐Menashe et al., 2016); correspondingly, satellite measures of burn severity improved with the greater image availability (Chen et al., 2021). Therefore, we also included analyses restricted to fires from the 2002–2019 time period, such that all pre‐ and post‐fire imagery were acquired from 2001 onward.…”

Section: Methodsmentioning

confidence: 99%

“…Multispectral imagery, such as Landsat data, has been widely used in research and management to characterize fire effects due to its ability to isolate signals directly resulting from fire (Chen et al., 2021). Spectral imagery from before and after a fire can be compared and integrated into indices (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Improved fire severity mapping in the North American boreal forest using a hybrid composite method

Holsinger

Parks

Saperstein

et al. 2021

Remote Sens Ecol Conserv

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Fire severity is a key driver shaping the ecological structure and function of North American boreal ecosystems, a biome dominated by large, high-intensity wildfires. Satellite-derived burn severity maps have been an important tool in these remote landscapes for both fire and resource management. The conventional methodology to produce satellite-inferred fire severity maps generally involves comparing imagery from 1 year before and 1 year after a fire, yet environmental conditions unique to the boreal have limited the accuracy of resulting products. We introduce an alternative methodthe 'hybrid composite'based on deriving mean severity over time on a per-pixel basis within the cloud-computing environment of Google Earth Engine. It constructs the postfire image from satellite data composited from all valid images (i.e., clear-sky and snow-free) acquired in the time period immediately after fire through the early growing season of the following year. We compare this approach to paired-scene and composite approaches where the post-fire time period is from the growing season 1 year after fire. Validation statistics based on field-derived data for 52 fires across Alaska and Canada indicate that the hybrid composite method outperforms the other approaches. This approach presents an efficient and cost-effective means to monitor and explore trends and patterns across broad spatial domains, and could be applied to fires in other regions, especially those with frequent cloud cover or rapid vegetation recovery.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Improved fire severity mapping in the North American boreal forest using a hybrid composite method

Holsinger

Parks

Saperstein

et al. 2021

Remote Sens Ecol Conserv

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“…Now containing more than forty years of multi-spectral reflectance observations, the Landsat data archive represents an unparalleled record of change on Earth's surface. The spatial (30 m) and temporal (8-16 day) resolution of Landsat make it a unique resource for anyone interested in the status and dynamics of land cover at local and regional scales [54][55][56][57]. With the entire sequence of Landsat imagery now freely available through the USGS delivered via Google Earth Engine, we can address questions related to the dynamics of LULCC in Semarang.…”

Section: Geospatial Data For Monitoring Lulccmentioning

confidence: 99%

Analysis of Land Use and Land Cover Changes through the Lens of SDGs in Semarang, Indonesia

et al. 2022

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Land Use and Land Cover Changes (LULCC) are occurring rapidly around the globe, particularly in developing island nations. We use the lens of the United Nations’ Sustainable Development Goals (SDG) to determine potential policies to address LULCC due to increasing population, suburbia, and rubber plantations in Semarang, Indonesia between 2006 and 2015. Using remote sensing, overlay analysis, optimized hot spot analysis, expert validation, and Continuous Change Detection and Classification, we found that there was a spread of urban landscapes towards the southern and western portions of Semarang that had previously been occupied by forests, plantations, agriculture, and aquaculture. We also witnessed a transition in farming from agriculture to rubber plantations, a cash crop. The implications of this study show that these geospatial analyses and big data can be used to characterize the SDGs, the complex interplay of these goals, and potentially alleviate some of the conflicts between disparate SDGs. We recommend certain policies that can assist in preserving the terrestrial ecosystem of Semarang (SDG 15) while creating a sustainable city (SDG 11, SDG 9) and providing sufficient work for individuals (SDG 1) in a growing economy (SDG 8) while simultaneously maintaining a sufficient food supply (SDG 2).

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Mapping burn severity and monitoring CO content in Türkiye’s 2021 Wildfires, using Sentinel-2 and Sentinel-5P satellite data on the GEE platform

et al. 2023

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This study investigated forest fires in the Mediterranean of Türkiye between July 28, 2021, and August 11, 2021. Burn severity maps were produced with the difference normalised burned ratio index (dNBR) and difference normalised difference vegetation index (dNDVI) using Sentinel-2 images on the Google Earth Engine (GEE) cloud platform. The burned areas were estimated based on the determined burning severity degrees. Vegetation density losses in burned areas were analysed using the normalised difference vegetation index (NDVI) time series. At the same time, the post-fire Carbon Monoxide (CO) column number densities were determined using the Sentinel-5P satellite data. According to the burn severity maps obtained with dNBR, the sum of high and moderate severity areas constitutes 34.64%, 20.57%, 46.43%, 51.50% and 18.88% of the entire area in Manavgat, Gündoğmuş, Marmaris, Bodrum and Köyceğiz districts, respectively. Likewise, according to the burn severity maps obtained with dNDVI, the sum of the areas of very high severity and high severity constitutes 41.17%, 30.16%, 30.50%, 42.35%, and 10.40% of the entire region, respectively. In post-fire NDVI time series analyses, sharp decreases were observed in NDVI values from 0.8 to 0.1 in all burned areas. While the Tropospheric CO column number density was 0.03 mol/m 2 in all regions burned before the fire, it was observed that this value increased to 0.14 mol/m 2 after the fire. Moreover, when the area was examined more broadly with Sentinel 5P data, it was observed that the amount of CO increased up to a maximum value of 0.333 mol/m 2 . The results of this study present significant information in terms of determining the severity of forest fires in the Mediterranean region in 2021 and the determination of the CO column number density after the fire. In addition, monitoring polluting gases with RS techniques after forest fires is essential in understanding the extent of the damage they can cause to the environment.

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Spatio-temporal patterns of optimal Landsat data for burn severity index calculations: Implications for high northern latitudes wildfire research

Cited by 16 publications

References 54 publications

Improved fire severity mapping in the North American boreal forest using a hybrid composite method

Improved fire severity mapping in the North American boreal forest using a hybrid composite method

Analysis of Land Use and Land Cover Changes through the Lens of SDGs in Semarang, Indonesia

Mapping burn severity and monitoring CO content in Türkiye’s 2021 Wildfires, using Sentinel-2 and Sentinel-5P satellite data on the GEE platform

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