Monitoring freeze/thaw cycles using ENVISAT ASAR Global Mode

Park, Sang-Eun; Bartsch, Annett; Sabel, Daniel; Wagner, Wolfgang; Naeimi, Vahid; Yamaguchi, Yoshio

doi:10.1016/j.rse.2011.08.009

Cited by 54 publications

(73 citation statements)

References 22 publications

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“…Backscatter can increase during the course of the winter by about 1 dB at some locations (Naeimi et al, 2012). In a case study for Yakutia, no increase in ASAR GM backscatter with increasing SWE (snow water equivalent) could be observed (Park et al, 2011). In order to account for possible contributions by snow cover, (1) only December data should be used, assuming that there are frozen conditions and snow depth is still limited, and (2) the minimum from as many years as possible should be calculated in order to have the lowest possible impact (this also accounts for the GM-specific noise).…”

Section: Introductionmentioning

confidence: 93%

“…This is a collection of routines which manages SAR geocoding and radiometric calibration by calling other non-commercial and commercial software packages. By incorporating orbit information (DORIS (Doppler Orbitography and Radiopositioning Integrated by Satellite) orbit files) and digital elevation data (US Geological Survey GTOPO30 digital elevation model, improved by Shuttle Radar Topography Mission data), geocoded images were produced with sub-pixel accuracy (Park et al, 2011;Pathe et al, 2009). The data are resampled into a fixed 15 arcsec grid (datum WGS-84), within 0.5 • by 0.5 • tiles, to allow for efficient spatial and temporal analysis.…”

Section: Sar Data Processingmentioning

confidence: 99%

“…Since GM data exhibit comparably high noise (Park et al, 2011), temporal and/or spatial statistical measures (averaging, filtering etc.) need to be applied.…”

Section: Sar Data Processingmentioning

confidence: 99%

“…It is larger than for other common C-band backscatter-based applications. In comparison, freeze-thaw detection algorithms rely on a difference of about 1-3 dB between frozen and unfrozen conditions (Park et al, 2011). On average, backscatter decreases about 1-1.5 dB during freeze-up for wetlands compared to dry land cover types with about 0.5 dB over the CAVM domain (Widhalm et al, 2015a).…”

Section: Representativeness Of C-band Backscattermentioning

confidence: 99%

“…Frozen soils cause therefore similar backscatter like dry soils which has been specifically exploited for Cband applications (e.g. Wagner et al, 1999;Park et al, 2011). Winter backscatter is thus determined by the above-surface remains of vascular plants, surface roughness, near-surface soil texture and, if present, also snow cover.…”

Section: Introductionmentioning

confidence: 99%

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Can C-band synthetic aperture radar be used to estimate soil organic carbon storage in tundra?

et al. 2016

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Abstract.A new approach for the estimation of soil organic carbon (SOC) pools north of the tree line has been developed based on synthetic aperture radar (SAR; ENVISAT Advanced SAR Global Monitoring mode) data. SOC values are directly determined from backscatter values instead of upscaling using land cover or soil classes. The multi-mode capability of SAR allows application across scales. It can be shown that measurements in C band under frozen conditions represent vegetation and surface structure properties which relate to soil properties, specifically SOC. It is estimated that at least 29 Pg C is stored in the upper 30 cm of soils north of the tree line. This is approximately 25 % less than stocks derived from the soil-map-based Northern Circumpolar Soil Carbon Database (NCSCD). The total stored carbon is underestimated since the established empirical relationship is not valid for peatlands or strongly cryoturbated soils. The approach does, however, provide the first spatially consistent account of soil organic carbon across the Arctic. Furthermore, it could be shown that values obtained from 1 km resolution SAR correspond to accounts based on a high spatial resolution (2 m) land cover map over a study area of about 7 × 7 km in NE Siberia. The approach can be also potentially transferred to medium-resolution C-band SAR data such as ENVISAT ASAR Wide Swath with ∼ 120 m resolution but it is in general limited to regions without woody vegetation. Global Monitoring-mode-derived SOC increases with unfrozen period length. This indicates the importance of this parameter for modelling of the spatial distribution of soil organic carbon storage.

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Section: Introductionmentioning

confidence: 93%

Section: Sar Data Processingmentioning

confidence: 99%

“…Since GM data exhibit comparably high noise (Park et al, 2011), temporal and/or spatial statistical measures (averaging, filtering etc.) need to be applied.…”

Section: Sar Data Processingmentioning

confidence: 99%

Section: Representativeness Of C-band Backscattermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Can C-band synthetic aperture radar be used to estimate soil organic carbon storage in tundra?

et al. 2016

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Remote sensing of permafrost and frozen ground

Westermann

Duguay

Grosse

et al. 2014

Remote Sensing of the Cryosphere

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Remote Sensing Time Series Revealing Land Surface Dynamics: Status Quo and the Pathway Ahead

Kuenzer

Dech

Wagner

2015

Remote Sensing Time Series

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The face of our planet is changing at an unprecedented rate. Forest ecosystems diminish at alarming speed, urban and agricultural areas expand into the surrounding natural space, aquaculture is spreading, sea level rise leads to changes in coastal ecosystems, and even without obvious land cover change, land use intensity may change and complex ecosystems may undergo transient changes in composition. Satellite based earth observation is a powerful means to monitor these changes, and especially time series analysis holds the potential to reveal long term land surface dynamics. Whereas in past decades time series analysis was an elaborate undertaking mostly performed by a limited number of experts using coarse resolution data, attention shifts nowadays to open source tools and novel techniques for analyzing time series and the utilization of the same for numerous environmental applications. The reasons are the pressing call for climate-relevant, long term data analyses and value added products revealing past land surface dynamics and trends, the growing demand for global data sets, and the opening up of multidecadal remote sensing data archives, all at a time of considerablyimproved hardware power, computer literacy, and a general trend towards cloud solutions and available open source algorithms and programming languages. This chapter presents a comprehensive overview of time series analysis. We introduce currently orbiting optical, radar, and thermal infrared sensors and elucidate which of them are suitable for long term monitoring tasks based on remote sensing time

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Monitoring freeze/thaw cycles using ENVISAT ASAR Global Mode

Cited by 54 publications

References 22 publications

Can C-band synthetic aperture radar be used to estimate soil organic carbon storage in tundra?

Can C-band synthetic aperture radar be used to estimate soil organic carbon storage in tundra?

Remote sensing of permafrost and frozen ground

Remote Sensing Time Series Revealing Land Surface Dynamics: Status Quo and the Pathway Ahead

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