Identification of Snow Using Fully Polarimetric SAR Data Based On Entropy and Anisotropy

Varade, Divyesh; Singh, Gulab; Dikshit, Onkar; Manickam, Surendar

doi:10.1029/2019wr025449

Cited by 16 publications

(3 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Use of these parameters is of interest e.g. for terrain classification in snow-covered or frozen areas [39]- [41], [59], [60].…”

Section: Scattering Characteristics Of Snowmentioning

confidence: 99%

Polarimetric Analysis of Biseasonal Monostatic and Bistatic Radar Observations of a Glacier Accumulation Zone at Ku-Band

Stefko,

Bernhard,

Frey

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

We present ground-based Ku-band radar observations of the snow cover on top of the Great Aletsch Glacier carried out over two observation periods, in August 2021 and in March 2022. The observations were carried out with the combined mono/bistatic version of KAPRI, a full-polarimetric radar system, and revealed substantial differences between the scattering behaviour of the snow cover between the two seasons. We analyze the spatial and temporal behaviour of parameters including temporal decorrelation, the scattering entropy, the mean polarimetric alpha angle, and the co-and cross-polarized phase differences. The results indicate that snow cover decorrelates at Ku-band on the timescales of 4-12 hours in winter and summer, which has implications for repeat-pass methods with long temporal baselines. The analysis of the co-polarized phase difference in winter indicates that the parameter is prone to phase wrapping. In summer, its value exhibits smooth spatial trend and a strong sensitivity to changes in incidence angle and liquid water content. The bistatic cross-polarized phase difference also acquires a non-zero value, indicating the presence of non-reciprocal scattering, which has implications for possible calibration procedures of bistatic systems. The presented results aim to serve as a reference for snow scattering behaviour at Ku-band, which can aid planning of future data acquisition campaigns and satellite missions.

show abstract

“…Use of these parameters is of interest e.g. for terrain classification in snow-covered or frozen areas [39]- [41], [59], [60].…”

Section: Scattering Characteristics Of Snowmentioning

confidence: 99%

Polarimetric Analysis of Biseasonal Monostatic and Bistatic Radar Observations of a Glacier Accumulation Zone at Ku-Band

Stefko,

Bernhard,

Frey

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Enhancing the The Cloude-Pottier Entropy-based decomposition is widely employed in various applications. The H/A/a approach has found utility in land cover classification [60,61] across diverse terrain types, including forested areas [62], snow-covered terrains [63,64], wetlands [65][66][67], and agricultural regions [68,69]. Although Cloude-Pottier is a noncoherent method, it has also been evaluated for target detection procedures despite not being endorsed for such applications [70,71].…”

Section: H/alpha Feature Spacementioning

confidence: 99%

A Review on PolSAR Decompositions for Feature Extraction

Karachristos,

Koukiou,

Anastassopoulos

2024

J. Imaging

View full text Add to dashboard Cite

Feature extraction plays a pivotal role in processing remote sensing datasets, especially in the realm of fully polarimetric data. This review investigates a variety of polarimetric decomposition techniques aimed at extracting comprehensive information from polarimetric imagery. These techniques are categorized as coherent and non-coherent methods, depending on their assumptions about the distribution of information among polarimetric cells. The review explores well-established and innovative approaches in polarimetric decomposition within both categories. It begins with a thorough examination of the foundational Pauli decomposition, a key algorithm in this field. Within the coherent category, the Cameron target decomposition is extensively explored, shedding light on its underlying principles. Transitioning to the non-coherent domain, the review investigates the Freeman–Durden decomposition and its extension, the Yamaguchi’s approach. Additionally, the widely recognized eigenvector–eigenvalue decomposition introduced by Cloude and Pottier is scrutinized. Furthermore, each method undergoes experimental testing on the benchmark dataset of the broader Vancouver area, offering a robust analysis of their efficacy. The primary objective of this review is to systematically present well-established polarimetric decomposition algorithms, elucidating the underlying mathematical foundations of each. The aim is to facilitate a profound understanding of these approaches, coupled with insights into potential combinations for diverse applications.

show abstract

“…Remote sensing techniques have been frequently used to monitor the climate conditions such as precipitation and temperature (Rees, 2005; Varade & Dikshit, 2019; Varade et al., 2020). The radio detection and ranging has been used in weather monitoring and forecasting (e.g., Bevis et al., 1992; Massonnet & Feigl, 1998).…”

Section: Introductionmentioning

confidence: 99%

Machine‐Learning Estimation of Snow Depth in 2021 Texas Statewide Winter Storm Using SAR Imagery

Wang

et al. 2022

Geophysical Research Letters

View full text Add to dashboard Cite

Climate change has been modifying our Earth system with an increasing number of extreme precipitation events, such as droughts, floods, tropical cyclones (hurricanes or typhoons), and winter storms (Stott, 2016). The National Oceanic and Atmospheric Administration (NOAA) reported 308 climate disasters in the U.S. from 1980 to 2021 that cost more than $2 trillion (US dollars) (NOAA, 2021; https://www.ncdc.noaa.gov/billions/). The 2000s witnessed 63 climate events with a loss of $538.7 billion and 3,091 deaths, and the 2010s experienced 123 climate events with a loss of $844.7 billion and 5,224 deaths (NOAA). In the past year of 2021, there have been 20 lethal climate disasters in the U.S. that claimed 688 lives, in which 14 events occurred around the western and southern coasts, including the winter storm Uri in February 2021. Informing the mitigation measures for extreme precipitation events has become an urgent socioeconomic mission.Winter storms are listed as one of the most catastrophic hazards in the U.S., especially to the agriculture, public health, transportation, and critical lifelines (Zhang & Liang, 2021). The mid-and high-latitude areas are more vulnerable to winter storms with high severity and frequency (Vose et al., 2014). Winter storm damage estimations often consider the precipitation distribution, intensity, frequency, wind, temperature, power outage, and death toll (e.g.,

show abstract

Identification of Snow Using Fully Polarimetric SAR Data Based On Entropy and Anisotropy

Cited by 16 publications

References 58 publications

Polarimetric Analysis of Biseasonal Monostatic and Bistatic Radar Observations of a Glacier Accumulation Zone at Ku-Band

Polarimetric Analysis of Biseasonal Monostatic and Bistatic Radar Observations of a Glacier Accumulation Zone at Ku-Band

A Review on PolSAR Decompositions for Feature Extraction

Machine‐Learning Estimation of Snow Depth in 2021 Texas Statewide Winter Storm Using SAR Imagery

Contact Info

Product

Resources

About