Monitoring permafrost changes in central Yakutia using optical and polarimetric SAR data

Park, Sang-Eun; Jung, Yoon Taek; Kim, Hyuncheol

doi:10.1016/j.rse.2022.112989

Cited by 6 publications

(2 citation statements)

References 74 publications

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“…The RVI was calculated over all the above dates, except for 25 February 2015. This is because seasonal soil and vegetation freezing/thawing processes greatly affect the radar backscattering value, γ 0 [28,29]. Therefore, same-season radar data are to be used.…”

Section: Materials 321 Landsat Datamentioning

confidence: 99%

A Novel Method of Boreal Zone Reforestation/Afforestation Estimation Using PALSAR-1,2 and Landsat-5,8 Data

Bondur,

Chimitdorzhiev,

Kirbizhekova

et al. 2024

Forests

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Nowadays, global remote sensing studies of tropical forest parameters are relevant for assessing carbon sequestration, whereas boreal forests receive little attention. This is due to the current idea that forests with greater aboveground biomass absorb more carbon. However, new research indicates that rapidly growing young forests take up more carbon than mature ones. Therefore, it is necessary to develop universal methods of remote reforestation/afforestation monitoring. The existing reforestation methods rely on the separate analysis of multispectral optical images and radar data. Here, we propose a method for analyzing the joint dynamics of NDVI (or the Normalized Burn Ratio, NBR) and the radar vegetation index (RVI) on a 2D plot for a test reforestation site. NDVI and NBR time series were derived from Landsat-5,8 data, and the RVI was derived from ALOS-1,2 and PALSAR-1,2 for 2007–2020 using the resources of Google Earth Engine. The quantitative parameters to evaluate the degree of reforestation and changes in the species composition of young trees have been suggested. The suggested method enables a more thorough evaluation of reforestation by measuring the coupled dynamics of the projective cover of young trees and aboveground biomass.

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Section: Materials 321 Landsat Datamentioning

confidence: 99%

A Novel Method of Boreal Zone Reforestation/Afforestation Estimation Using PALSAR-1,2 and Landsat-5,8 Data

Bondur,

Chimitdorzhiev,

Kirbizhekova

et al. 2024

Forests

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“…The above surface deformation survey methods require a lot of time, money and labour costs, making them unable to meet the needs of the entire city's surface deformation monitoring. For the spatial scale of surface deformation investigations, most of the current studies on surface deformation in Yakutsk and its surrounding areas focus on the local-scale surface deformation characteristics during the occurrence of thermokarst (Abe et al, 2020;Aoki et al, 2021;Desyatkin et al, 2022;Park et al, 2022); these local regions deformation data do not provide enough detailed information to infer the overall ground deformation condition of the city. (Gabriel et al, 1989;Zebker et al, 1997), while time-series InSAR (TS-InSAR) can overcome these limitations, the current TS-InSAR can be divided into two main categories, PS-InSAR and small baselines subset InSAR (SBAS-InSAR) (Berardino et al, 2002;Ferretti et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

Time‐series InSAR monitoring of surface deformation in Yakutsk, a city located on continuous permafrost

Li,

Zhang,

Zheleznyak

et al. 2023

Earth Surf Processes Landf

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Permafrost, known for its high sensitivity to climate change and human activities, plays a crucial role in comprehending the environmental sustainability of Arctic cities. Yakutsk, being the largest city situated in continuous permafrost, has suffered irreversible damage to surface buildings due to the widespread permafrost thaw. Therefore, it is imperative to conduct detailed monitoring and assessment of surface deformation to ensure the stable operation of building facilities and to plan urban development situated above the permafrost. This study utilized 138 scenes of Sentinel‐1B images captured between 2017 and 2021 to process the surface deformation variations of Yakutsk using the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS‐InSAR) method. The surface deformation rate map reflects that the study area is undergoing extensive surface subsidence. The cumulative deformation time series maps effectively trace the temporal and spatial evolution of surface deformation, with the highest surface subsidence rates exceeding 40 mm/year and maximum cumulative subsidence exceeding 250 mm. In‐depth analysis of the obtained results indicated that the permafrost in Yakutsk is undergoing degradation, and the primary reason for surface subsidence is the thawing of foundation soils and the degradation of ice‐bearing permafrost. This study provides basic data for the investigation of geohazards caused by surface subsidence in Yakutsk.

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Observation of spatial and temporal patterns of seasonal ground deformation in central Yakutia using time series InSAR data in the freezing season

Jung

Park

Kim

2023

Remote Sensing of Environment

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Monitoring permafrost changes in central Yakutia using optical and polarimetric SAR data

Cited by 6 publications

References 74 publications

A Novel Method of Boreal Zone Reforestation/Afforestation Estimation Using PALSAR-1,2 and Landsat-5,8 Data

A Novel Method of Boreal Zone Reforestation/Afforestation Estimation Using PALSAR-1,2 and Landsat-5,8 Data

Time‐series InSAR monitoring of surface deformation in Yakutsk, a city located on continuous permafrost

Observation of spatial and temporal patterns of seasonal ground deformation in central Yakutia using time series InSAR data in the freezing season

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