Top

Earth Science Informatics

Published in:

20-03-2023 | RESEARCH

Inversion model for snow geophysical parameters estimation using sentinel–1 stokes parameter

Authors: Manmit Kumar Singh, Rishikesh Bharti

Published in: Earth Science Informatics | Issue 2/2023

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

The geophysical properties of snow are essential to study the mountain snow/glacier system and can be used as an indicator for any related hazard. In this study, an attempt has been made to model the geophysical properties of snow, such as dielectric, density, and wetness using the Sentinel–1 dual-polarized SLC product. A state-of-the-art inversion model has been developed using Sentinel–1 derived stokes parameters to estimate snow dielectric and subsequently used to model density and wetness employing Looyega's and Denoth's equations. The proposed inclusion of stokes parameters in the inversion model has significantly predicted the results. The respective modeled and in-situ snow dielectric, density, and wetness show a good coefficient of determination (R² > 0.7) with 95% confidence. Utilizing the field-measured values, the estimated root mean squared error (RMSE) of snow dielectric, density, and wetness, is 0.26, 0.08 g/cm³, and 0.84, respectively. The comparison of the proposed model with some of the existing models reflects its good efficiency in predicting the snow geophysical parameters.

previous article Comparative assessment of surface soil moisture simulations by the coupled wcm-iem vs. data-driven models using the Sentinel 1 and 2 satellite images

next article Towards progressive geospatial information processing on web systems: a case study for watershed analysis in Iowa

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Baghdadi N, Choker M, Zribi M, Hajj ME, Paloscia S, Verhoest NEC, Lievens H, Baup F, Mattia F (2016) A new empirical model for radar scattering from bare soil surfaces. Remote Sens 8(11):920. https://doi.org/10.3390/rs8110920CrossRef

Bahuguna IM, Kulkarni AV, Arrawatia ML, Shresta DG (2001) Glacier atlas of Tista basin (Sikkim Himalaya), SAC/RESA/MWRGGLI/SN/16, Ahmedabad, India

Basnett S, Kulkarni AV, Bolch T (2013) The influence of debris cover and glacial lakes on the recession of glaciers in Sikkim Himalaya. India J Glaciol 59(218):1035–1046. https://doi.org/10.3189/2013JoG12J184CrossRef

Basnett S, Kulkarni AV, Tambe S (2012) Monitoring of seasonal snow cover in Sikkim Himalaya using remote sensing techniques. Climate change in Sikkim: patterns, impacts and initiatives. Information and Public Relations Department, Government of Sikkim, Gangtok, pp 69–80

Carrivick JL, Tweed FS (2016) A global assessment of the societal impacts of glacier outburst floods. Global Planet Change 144:1–16. https://doi.org/10.1016/j.gloplacha.2016.07.001CrossRef

Cox LH, March RS (2004) Comparison of geodetic and glaciological mass-balance techniques, Gulkana Glacier, Alaska, USA. J Glaciol 50(170):363–370. https://doi.org/10.3189/172756504781829855CrossRef

Cuffey KM, Paterson WS (2010) The physics of glaciers, 4th edn. Academic Press, Cambridge

Denoth A (1989) Snow dielectric measurements. Adv Space Res 9(1):233–243. https://doi.org/10.1016/0273-1177(89)90491-2CrossRef

Denoth A (1994) An electronic device for long-term snow wetness recording. Ann Glaciol 19:104–106. https://doi.org/10.3189/S0260305500011058CrossRef

Dietz AJ, Kuenzer C, Gessner U, Dech S (2012) Remote sensing of snow–a review of available methods. Int J Remote Sens 33(13):4094–4134. https://doi.org/10.1080/01431161.2011.640964CrossRef

Dozier J, Painter TH (2004) Multispectral and hyperspectral remote sensing of alpine snow properties. Annu Rev Earth Planet Sci 32:465–494CrossRef

Dozier J, Marks D (1987) Snow mapping and classification from Landsat Thematic Mapper data. Ann Glaciol 9:97–103. https://doi.org/10.3189/S026030550000046XCrossRef

Du J, Shi J, Rott H (2010) Comparison between a multi-scattering and multi-layer snow scattering model and its parameterized snow backscattering model. Remote Sens Environ 114(5):1089–1098. https://doi.org/10.1016/j.rse.2009.12.020CrossRef

Dubey S, Goyal MK (2020) Glacial lake outburst flood hazard, downstream impact, and risk over the Indian Himalayas. Water Resourc Res 56(4), e2019WR026533. https://doi.org/10.1029/2019WR026533

Dumont M, Gascoin S (2016) Optical remote sensing of snow cover. In Land surface remote sensing in continental hydrology (pp. 115–137). Elsevier. https://doi.org/10.1016/B978-1-78548-104-8.50004-8

Dyer JL, Mote TL (2006) Spatial variability and trends in observed snow depth over North America. Geophys Res Lett 33(16)

Elkharrouba E, Sekertekin A, Fathi J, Tounsi Y, Bioud H, Nassim A (2022) Surface soil moisture estimation using dual-Polarimetric Stokes parameters and backscattering coefficient. Remote Sensing Appl: Soc Environ 26, 100737. https://doi.org/10.1016/j.rsase.2022.100737

Emmer A, Vilímek V, Huggel C, Klimeš J, Schaub Y (2016) Limits and challenges to compiling and developing a database of glacial lake outburst floods. Landslides 13(6):1579–1584. https://doi.org/10.1007/s10346-016-0686-6CrossRef

Foster JL, Hall DK, Chang ATC, Rango A (1984) An overview of passive microwave snow research and results. Rev Geophys 22(2):195–208. https://doi.org/10.1029/RG022i002p00195CrossRef

Frey H, Haeberli W, Linsbauer A, Huggel C, Paul F (2010) A multi-level strategy for anticipating future glacier lake formation and associated hazard potentials. Nat Hazard 10(2):339–352. https://doi.org/10.5194/nhess-10-339-2010CrossRef

Frolov AD, Ya. Macheret Y (1999) On dielectric properties of dry and wet snow. Hydrol Process 13(12‐13), 1755-1760. https://doi.org/10.1002/(SICI)1099-1085(199909)13

Hajnsek I, Pottier E, Cloude SR (2003) Inversion of surface parameters from polarimetric SAR. IEEE Trans Geosci Remote Sens 41(4):727–744. https://doi.org/10.1109/TGRS.2003.810702CrossRef

Hajnsek I, Desnos YL (Eds.) (2021) Polarimetric synthetic aperture radar: principles and application (Vol. 25). Springer Nature

Huss M (2013) Density assumptions for converting geodetic glacier volume change to mass change. Cryosphere 7(3):877–887. https://doi.org/10.5194/tc-7-877-2013CrossRef

Jonas T, Marty C, Magnusson J (2009) Estimating the snow water equivalent from snow depth measurements in the Swiss Alps. J Hydrol 378(1–2):161–167. https://doi.org/10.1016/j.jhydrol.2009.09.021CrossRef

Kendra JR, Ulaby FT, Sarabandi K (1994) Snow probe for in situ determination of wetness and density. IEEE Trans Geosci Remote Sens 32(6):1152–1159. https://doi.org/10.1109/36.338363CrossRef

König M, Winther JG, Isaksson E (2001) Measuring snow and glacier ice properties from satellite. Rev. Geophys 39(1):1–27. https://doi.org/10.1029/1999RG000076CrossRef

Kulkarni AV, Rathore BP, Singh SK (2010) Distribution of seasonal snow cover in central and western Himalaya. Ann Glaciol 51(54):123–128. https://doi.org/10.3189/172756410791386445CrossRef

Landes T, Gay M, Trouve E, Nicolas JM, Bombrun L, Vasile G, Hajnsek I (2007) Monitoring temperate glaciers by high resolution pol-InSAR data: first analysis of Argentière E-SAR acquisitions and in-situ measurements. In: IGARSS 2007 IEEE. International geoscience and remote sensing symposium. IEEE, pp 184–187. https://doi.org/10.1109/IGARSS.2007.4422760CrossRef

Lee JS, Pottier E (2017) Polarimetric radar imaging: from basics to applications. CRC PressCrossRef

Lei Y, Siqueira P (2015, July) A dense-medium InSAR correlation model with its application to the problem of snow characteristics retrieval. In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 263–266). IEEE. https://doi.org/10.1109/IGARSS.2015.7325750

Lenormand F, Duguay CR, Gauthier R (2002) Development of a historical ice database for the study of climate change in Canada. Hydrol Process 16(18):3707–3722. https://doi.org/10.1002/hyp.1235CrossRef

Looyenga H (1965) Dielectric constants of homogeneous mixture. molecular Physics 9(6), 501–511. https://doi.org/10.1080/00268976500100671

Li M, Xiao P, Zhang X, Feng X, Zhu L (2022) An improved approach of dry snow density estimation using C-band synthetic aperture radar data. ISPRS J Photogramm Remote Sens 191:49–67. https://doi.org/10.1016/j.isprsjprs.2022.07.002CrossRef

Liu J, Wu Y, Gao X (2021) Increase in occurrence of large glacier-related landslides in the high mountains of Asia. Sci Rep 11(1):1–12. https://doi.org/10.1038/s41598-021-81212-9CrossRef

Luitel KK, Shrestha DG, Sharma NP, Sharma RK (2012) Impact of climate change on east-Rathong glacier in Rangit Basin, West Sikkim. Climate change in Sikkim patterns, impacts and initiatives. Information and Public Relations Department, Government of Sikkim, Gangtok, pp 57–68

Ma W, Xiao P, Zhang X, Song Y, Ma T, Ye L (2020) Retrieving snow wetness based on surface and volume scattering simulation. ISPRS J Photogramm Remote Sens 169:17–28. https://doi.org/10.1016/j.isprsjprs.2020.08.021CrossRef

Manickam S, Bhattacharya A, Singh G, Yamaguchi Y (2016) Estimation of snow surface dielectric constant from polarimetric SAR data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10(1):211–218. https://doi.org/10.1109/JSTARS.2016.2588531CrossRef

Mascolo L, Cloude SR, Lopez-Sanchez JM (2021) Model-based decomposition of dual-pol sar data: application to sentinel-1. In: IGARSS 2021 IEEE international geoscience and remote sensing symposium. IEEE, pp 1–19. https://doi.org/10.1109/TGRS.2021.3137588CrossRef

Meløysund V, Leira B, Høiseth KV, Lisø KR (2007) Predicting snow density using meteorological data. Meteorological Applications: A journal of Forecasting, Practical Applications, Training Techniques and Modelling 14(4):413–423. https://doi.org/10.1002/met.40CrossRef

Mondal SK, Bharti R (2023) Spatio-temporal variations in the effective snow/glacier coverage in the Sikkim Himalayas. J Indian Soc Remote Sens. https://doi.org/10.1007/s12524-022-01643-3

Mukhopadya SC (1982) The Teesta Basin, a study in fluvial geomorphology. K. P. Bagchi and Company, Calcutta, pp 1–308

Negi HS, Shekhar C, Singh SK (2015) Snow and glacier investigations using hyperspectral data in the Himalaya. Curr Sci 892–902

Patil A, Singh G, Rüdiger C, Mohanty S, Kumar S (2020) A novel approach for the snow water equivalent retrieval using X-band polarimetric synthetic aperture radar data. IEEE Trans Geosci Remote Sens 59(5):3753–3763. https://doi.org/10.1109/TGRS.2020.3016527CrossRef

Ponnurangam GG, Jagdhuber T, Hajnsek I, Rao YS (2015) Soil moisture estimation using hybrid polarimetric SAR data of RISAT-1. IEEE Trans Geosci Remote Sens 54(4):2033–2049. https://doi.org/10.1109/TGRS.2015.2494860CrossRef

Rai SC, Mukherjee NR (2021) Spatio-temporal change delineation and forecasting of snow/ice-covered areas of Sikkim Himalaya using multispectral and thermal band combinations of Landsat imagery. Environmental Challenges 4(100163). https://doi.org/10.1016/j.envc.2021.100163

Raney RK (2006) Dual-polarized SAR and stokes parameters. IEEE Geosci Remote Sens Lett 3(3):317–319. https://doi.org/10.1109/LGRS.2006.871746CrossRef

Raney RK (2019) Hybrid dual-polarization synthetic aperture radar. Remote Sensing 11(13):1521. https://doi.org/10.3390/rs11131521CrossRef

Rees WG (2005) Remote sensing of snow and ice. CRC PressCrossRef

Singh G, Venkataraman G (2009, July) Snow density estimation using Polarimitric ASAR data. In 2009 IEEE International Geoscience and Remote Sensing Symposium (Vol. 2, pp. II-630). IEEE. https://doi.org/10.1109/IGARSS.2009.5418165

Singh G, Kumar V, Mohite K, Venkatraman G, Rao YS (2006, December) Snow wetness estimation in Himalayan snow covered regions using ENVISAT-ASAR data. In Microwave Remote Sensing of the Atmosphere and Environment V (Vol. 6410, pp. 67–78). SPIE. https://doi.org/10.1117/12.693690

Singh G, Verma A, Kumar S, Ganju A, Yamaguchi Y, Kulkarni AV (2017) Snowpack density retrieval using fully polarimetric TerraSAR-X data in the Himalayas. IEEE Trans Geosci Remote Sens 55(11):6320–6329. https://doi.org/10.1109/TGRS.2017.2725979CrossRef

Singh MK, Bharti R (2022, July) Snow permittivity and density estimation using C-band dual polarimetric sentinel-1A data. In IGARSS 2022–2022 IEEE International Geoscience and Remote Sensing Symposium (pp. 2526–2529). IEEE. https://doi.org/10.1109/IGARSS46834.2022.9884072

Snehmani, Venkataraman G, Nigam AK, Singh G (2010) Development of an inversion algorithm for dry snow density estimation and its application with ENVISAT-ASAR dual co-polarization data. Geocarto International, 25(8), 597-616. https://doi.org/10.1080/10106049.2010.516843

Sugiyama S, Enomoto H, Fujita S, Fukui K, Nakazawa F, Holmlund P (2010) Dielectric permittivity of snow measured along the route traversed in the Japanese–Swedish Antarctic expedition 2007/08. Ann Glaciol 51(55):9–15. https://doi.org/10.3189/172756410791392745CrossRef

Surendar M, Bhattacharya A, Singh G, Venkataraman G (2015) Estimation of snow density using full-polarimetric synthetic aperture radar (SAR) data. Phys Chem Earth, Parts a/b/c 83:156–165. https://doi.org/10.1016/j.pce.2015.07.001CrossRef

Thakur PK, Aggarwal SP, Garg PK, Garg RD, Mani S, Pandit A, Kumar S (2012) Snow physical parameters estimation using space-based Synthetic Aperture Radar. Geocarto Int 27(3):263–288. https://doi.org/10.1080/10106049.2012.672477CrossRef

Thakur PK, Aggarwal SP, Arun G, Sood S, Senthil KA, Mani S, Dobhal DP (2017) Estimation of snow cover area, snow physical properties and glacier classification in parts of Western Himalayas using C-band SAR data. J Indian Soc Remote Sens 45:525–539. https://doi.org/10.1007/s12524-016-0609-yCrossRef

Tiuri M, Sihvola A, Nyfors EG, Hallikaiken M (1984) The complex dielectric constant of snow at microwave frequencies. IEEE J Oceanic Eng 9(5):377–382. https://doi.org/10.1109/JOE.1984.1145645CrossRef

Varade D, Dikshit O (2019) Improved assessment of atmospheric water vapor content in the Himalayan regions around the Kullu valley in India using Landsat-8 data. Water Resour Res 55(1):462–475. https://doi.org/10.1029/2018WR023806CrossRef

Varade D, Dikshit O (2020) Potential of multispectral reflectance for assessment of snow geophysical parameters in Solang valley in the lower Indian Himalayas. Giscience & Remote Sensing 57(1):107–126. https://doi.org/10.1080/15481603.2019.1672365CrossRef

Varade D, Dikshit O, Manickam S (2019) Dry/wet snow mapping based on the synergistic use of dual polarimetric SAR and multispectral data. J Mt Sci 16(6):1435–1451. https://doi.org/10.1007/s11629-019-5373-3CrossRef

Varade D, Manickam S, Dikshit O, Singh G (2020) Modelling of early winter snow density using fully polarimetric C-band SAR data in the Indian Himalayas. Remote Sens Environ 240, 111699. https://doi.org/10.1016/j.rse.2020.111699

Vilímek V, Emmer A, Huggel C, Schaub Y, Würmli S (2014) Database of glacial lake outburst floods (GLOFs)–IPL project No. 179. Landslides 11(1), 161–165. https://doi.org/10.1007/s10346-013-0448-7

Worni R, Stoffel M, Huggel C, Volz C, Casteller A, Luckman B (2012) Analysis and dynamic modeling of a moraine failure and glacier lake outburst flood at Ventisquero Negro, Patagonian Andes (Argentina). J Hydrol 444:134–145. https://doi.org/10.1016/j.jhydrol.2012.04.013CrossRef

Worni R, Huggel C, Stoffel M (2013) Glacial lakes in the Indian Himalayas—From an area-wide glacial lake inventory to on-site and modeling based risk assessment of critical glacial lakes. Sci Total Environ 468:S71–S84. https://doi.org/10.1016/j.scitotenv.2012.11.043CrossRef

Title: Inversion model for snow geophysical parameters estimation using sentinel–1 stokes parameter
Authors: Manmit Kumar Singh
Rishikesh Bharti
Publication date: 20-03-2023
Publisher: Springer Berlin Heidelberg
Published in: Earth Science Informatics / Issue 2/2023
Print ISSN: 1865-0473
Electronic ISSN: 1865-0481
DOI: https://doi.org/10.1007/s12145-023-00984-y

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Other articles of this Issue 2/2023

Identification of The Survey Points from Network RTK Trajectory with Improved DBSCAN Clustering, Case Study on HNCORS

Machine learning for prediction of the uniaxial compressive strength within carbonate rocks

Construction and application of mine water inflow prediction model based on multi-factor weighted regression: Wulunshan Coal Mine case

A comparative and coupled study of the application of Dempster-Shafer, fuzzy overlay and FAHP methods for groundwater potential mapping in a fractured medium of a mine site

Implementation and verification of a real-time system for automatic aftershock forecasting in China

Best worst method-based mineral prospectivity modeling over the Central part of the Southern Kibi-Winneba Belt of Ghana

Premium Partner