Solar Potential in the Himalayan Landscape

Ramachandra, T. V.; Krishnadas, Gautham; Jain, Rishabh

doi:10.5402/2012/203149

Cited by 18 publications

(1 citation statement)

References 22 publications

(21 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The average winter and spring season temperatures in the Indian Pir Pranjal Ranges for Gulmarg and Pahalgam regions are around (1 °C, 0.9 °C) and (1.4 °C, 1.3 °C), respectively (Zaz et al, 2019). In the state of Himachal Pradesh in India, during the early winter season, the average temperature varies between 12 °C and −1 °C (Ramachandra et al, 2012). The expected snow wetness during the early winter season in these areas is around 2% to 6% by volume because of fresh snowfall and diurnal melt and refreeze processes (Surendar, Bhattacharya, Singh, Yamaguchi, et al, 2015).…”

Section: Water Resources Researchmentioning

confidence: 99%

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

Varade

Singh

Dikshit

et al. 2020

Water Resources Research

View full text Add to dashboard Cite

Recently, with the extensive availability of fully polarimetric synthetic aperture radar (SAR) data, methods that are simple and efficient, and involve lesser computation and data processing, are needed to be explored for snow cover mapping. This paper analyzes different polarimetric parameters such as entropy, anisotropy, and the mean scattering angle for the identification of snow cover area. We present a novel index for mapping snow cover based on the assessment of entropy (H) and anisotropy (A) using fully polarimetric SAR data and refer to it as the radar snow fraction (RSF). The RSF is proposed as an extension of the H(1‐A) metric by applying a sigmoidal function to this metric. The experiments to evaluate the applicability of the proposed RSF are carried out using fully polarimetric SAR data of L‐band ALOS‐2/PALSAR‐2 and C‐band RADARSAT‐2 data sets corresponding to different geographical locations in the Indian Himalayas. The developed snow cover maps from the proposed method were validated with respect to reference snow cover maps derived by thresholding the Normalized Differenced Snow Index developed from multispectral data (e.g., Landsat‐8 imagery). These maps were also statistically compared with those obtained from the conventional radar snow index, which is based on the polarization fraction. We determined a mean overall accuracy of 0.8 between the developed snow cover maps and the reference maps for the different data sets used for experiments. The results showed that, in general, the RSF outperformed the other polarimetric parameters for snow cover detection.

show abstract

Section: Water Resources Researchmentioning

confidence: 99%