Automated mapping of snow/ice surface temperature using Landsat-8 data in Beas River basin, India, and validation with w
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ORIGINAL PAPER
Automated mapping of snow/ice surface temperature using Landsat-8 data in Beas River basin, India, and validation with wireless sensor network data Dhiraj Kumar Singh 1,2 & Hemendra Singh Gusain 1 & Varunendra Mishra 1 & Neena Gupta 2 & Rajiv Kumar Das 1 Received: 31 July 2017 / Accepted: 15 March 2018 # Saudi Society for Geosciences 2018
Abstract In this paper, an automated method for retrieval of snow surface temperature (SST) in Beas River Basin, India, using Landsat-8 thermal data is proposed. Digital number (DN) values of thermal data were converted into Top of Atmospheric (TOA) radiance. Surface radiance has been estimated from TOA radiance using a single channel method. The estimated surface radiance was then converted into SST. Cloud free Landsat-8 data for January and February 2017 has been used to estimate SST. Snow and Avalanche Study Establishment (SASE) has established a wireless sensor network (WSN) in an avalanche prone slope in Beas River Basin, India. Landsat-8 retrieved SST has been compared and validated with recorded SST at WSN stations. The retrieved SST using proposed algorithm was in good agreement with SST recorded on ground by sensor network. The mean absolute error (MAE) and root-mean-square error (RMSE) between estimated and recorded SST has been observed as ~ 1.1 K and ~ 1.5 K for 23 January 2017 and ~ 0.7 and ~ 1.6 K for 24 February 2017. Algorithm has shown a potential for automated mapping of snow and ice surface temperature using Landsat-8 data for snow cover and glaciers in Himalaya. Keywords Surface temperature . Landsat-8 thermal data . Wireless sensor network
Introduction Surface temperature is an important parameter for the study of ecology, environment, climatology, glaciology, hydrology, physical processes, etc. on the earth surface (Cristobal et al. 2008; Kuenzer and Dech 2013; Li et al. 2013). Temporal and spatial changes in surface temperature over a large area are responsible for changes in various physical processes and subsequently changes in ecology, environment, surface characteristics, etc. Cryospheric regions are integral part of the biosphere and surface temperature plays an important role in these regions. Surface temperature retrieval for these regions is essential for climate change monitoring, snow/ice cover studies, melt estimation, flood forecasting, hazard assessment, and many
* Dhiraj Kumar Singh [email protected] 1
Snow and Avalanche Study Establishment, RDC (DRDO), Chandigarh 160037, India
2
PEC University of Technology, Chandigarh 160012, India
other studies. However, due to rugged terrain and harsh climatic conditions, ground observations over vast areas of Himalaya are limited to few observation locations (Gusain et al. 2014). Remote sensing-based techniques have been found useful for collecting information from such inaccessible large areas and to retrieve various surface parameters (Chang and Foster 1991; König et al. 2001; Kulkarni et al. 2006; Singh et al. 2007; Das and Sarwade 2008; Gurung et al. 2011; Bolch et al. 201
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