{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T07:23:23Z","timestamp":1725693803663},"reference-count":39,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2020,10,14]],"date-time":"2020-10-14T00:00:00Z","timestamp":1602633600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41531069","41941010","41874031"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Fundamental Research Funds for the Central Universities of China","award":["2042019kf0220","2018AAA070","2018CFA007"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"Snow plays a critical role in hydrological monitoring and global climate change, especially in the Arctic region. As a novel remote sensing technique, global navigation satellite system interferometric reflectometry (GNSS-IR) has shown great potential for detecting reflector characteristics. In this study, a field experiment of snow depth sensing with GNSS-IR was conducted in Ny-Alesund, Svalbard, and snow depth variations over the 2014\u20132018 period were retrieved. First, an improved approach was proposed to estimate snow depth with GNSS observations by introducing wavelet decomposition before spectral analysis, and this approach was validated by in situ snow depths obtained from a meteorological station. The proposed approach can effectively separate the noise power from the signal power without changing the frequency composition of the original signal, particularly when the snow depth changes sharply. Second, snow depth variations were analyzed at three stages including snow accumulation, snow ablation and snow stabilization, which correspond to different snow-surface-reflection characteristics. For these three stages of snow depth variations, the mean absolute errors (MAE) were 4.77, 5.11 and 3.51 cm, respectively, and the root mean square errors (RMSE) were 6.00, 6.34 and 3.78 cm, respectively, which means that GNSS-IR can be affected by different snow surface characteristics. Finally, the impact of rainfall on snow depth estimation was analyzed for the first time. The results show that the MAE and RMSE were 2.19 and 2.08 cm, respectively, when there was no rainfall but 5.63 and 5.46 cm, respectively, when it was rainy, which indicates that rainfall reduces the accuracy of snow depth estimation by GNSS-IR.<\/jats:p>","DOI":"10.3390\/rs12203352","type":"journal-article","created":{"date-parts":[[2020,10,15]],"date-time":"2020-10-15T01:24:39Z","timestamp":1602725079000},"page":"3352","source":"Crossref","is-referenced-by-count":7,"title":["Snow Depth Variations in Svalbard Derived from GNSS Interferometric Reflectometry"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-3106-0714","authenticated-orcid":false,"given":"Jiachun","family":"An","sequence":"first","affiliation":[{"name":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}]},{"given":"Pan","family":"Deng","sequence":"additional","affiliation":[{"name":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-5438-8723","authenticated-orcid":false,"given":"Baojun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"},{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}]},{"given":"Jingbin","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-6677-3899","authenticated-orcid":false,"given":"Songtao","family":"Ai","sequence":"additional","affiliation":[{"name":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}]},{"given":"Zemin","family":"Wang","sequence":"additional","affiliation":[{"name":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}]},{"given":"Qiuze","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Electronic Information, Wuhan University, Wuhan 430072, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,10,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"045010","DOI":"10.1088\/1748-9326\/aafc1b","article-title":"Key indicators of Arctic climate change: 1971\u20132017","volume":"14","author":"Box","year":"2019","journal-title":"Environ. Res. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Ai, S., Ding, X., An, J., Lin, G., Wang, Z., and Yan, M. (2019). Discovery of the Fastest Ice Flow along the Central Flow Line of Austre Lov\u00e9nbreen, a Poly-thermal Valley Glacier in Svalbard. Remote Sens., 11.","DOI":"10.3390\/rs11121488"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2166\/nh.2001.0001","article-title":"Snow Distribution at a High Arctic Site at Svalbard","volume":"32","author":"Bruland","year":"2001","journal-title":"Hydrol. Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"516","DOI":"10.1007\/s13280-016-0770-0","article-title":"Changing Arctic snow cover: A review of recent developments and assessment of future needs for observations, modelling, and impacts","volume":"45","author":"Bokhorst","year":"2016","journal-title":"Ambio"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Zhu, Y., and Shen, F. (2019, January 22\u201325). Snow Depth Determination Based on GNSS-IR. Proceedings of the China Satellite Navigation Conference (CSNC), Beijing, China.","DOI":"10.1007\/978-981-13-7751-8_10"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3516","DOI":"10.3390\/rs5073516","article-title":"Soil Moisture & Snow Properties Determination with GNSS in Alpine Environments: Challenges, Status, and Perspectives","volume":"5","author":"Botteron","year":"2013","journal-title":"Remote Sens."},{"key":"ref_7","unstructured":"Komjathy, A., Zavorotny, V., Axelrad, P., Born, G., and Garrison, J. (1998, January 5\u20137). Gps Signal Scattering From Sea Surface: Comparison Between Experimental Data And Theoretical Model. Proceedings of the Fifth International Conference on Remote Sensing for Mar. and Coastal Environments, San Diego, CA, USA."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1109\/JSTARS.2009.2033608","article-title":"A Physical Model for GPS Multipath Caused by Land Reflections: Toward Bare Soil Moisture Retrievals","volume":"3","author":"Zavorotny","year":"2010","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Boniface, K., Walpersdorf, A., Guyomarc\u2019h, G., Deliot, Y., Karbou, F., Vionnet, V., and Nievinski, F. (2015, January 26\u201331). GNSS reflectometry measurement of snow depth and soil moisture in the French Alps. Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy.","DOI":"10.1109\/IGARSS.2015.7327007"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1109\/LGRS.2008.917130","article-title":"Dielectric-Covered Ground Reflectors in GPS Multipath Reception\u2014Theory and Measurement","volume":"5","author":"Jacobson","year":"2008","journal-title":"Geosci. Remote Sens. Lett. IEEE"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1186\/1687-6180-2014-106","article-title":"Snow depth sensing using the GPS L2C signal with a dipole antenna","volume":"2014","author":"Chen","year":"2014","journal-title":"EURASIP J. Adv. Signal Process."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"7808","DOI":"10.1002\/2017GL074039","article-title":"Snow accumulation variability on a West Antarctic ice stream observed with GPS reflectometry, 2007\u20132017","volume":"44","author":"Siegfried","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"4809","DOI":"10.1109\/JSTARS.2016.2516041","article-title":"Monitoring Snow Depth by GNSS Reflectometry in Built-up Areas: A Case Study for Wettzell, Germany","volume":"9","author":"Vey","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Larson, K.M., Gutmann, E.D., Zavorotny, V.U., Braun, J.J., Williams, M.W., and Nievinski, F.G. (2009). Can we measure snow depth with GPS receivers?. Geophys. Res. Lett., 36.","DOI":"10.1029\/2009GL039430"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"4802","DOI":"10.1109\/JSTARS.2015.2508673","article-title":"Estimation of Snow Depth Using L1 GPS Signal-to-Noise Ratio Data","volume":"9","author":"Larson","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2426","DOI":"10.3390\/rs2102426","article-title":"Inferring Snow Water Equivalent for a Snow-Covered Ground Reflector Using GPS Multipath Signals","volume":"2","author":"Jacobson","year":"2010","journal-title":"Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1007\/s10291-012-0259-7","article-title":"GPS snow sensing: Results from the EarthScope Plate Boundary Observatory","volume":"17","author":"Larson","year":"2013","journal-title":"GPS Solut."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"6555","DOI":"10.1109\/TGRS.2013.2297681","article-title":"Inverse Modeling of GPS Multipath for Snow Depth Estimation-Part I: Formulation and Simulations","volume":"52","author":"Nievinski","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3773","DOI":"10.1109\/TGRS.2017.2679899","article-title":"Statistical Comparison and Combination of GPS, GLONASS, and Multi-GNSS Multipath Reflectometry Applied to Snow Depth Retrieval","volume":"55","author":"Tabibi","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_20","first-page":"8","article-title":"Snow depth detection and error analysis derived from SNR of GPS and BDS","volume":"47","author":"Wang","year":"2018","journal-title":"Acta Geod. Cartogr. Sin."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"102840","DOI":"10.1016\/j.coldregions.2019.102840","article-title":"GPS reflectometry study detecting snow height changes in the Southern Patagonia Icefield","volume":"166","author":"Durand","year":"2019","journal-title":"Cold Reg. Sci. Technol."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Wei, H., He, X., Feng, Y., Jin, S., and Shen, F. (2019). Snow Depth Estimation on Slopes Using GPS-Interferometric Reflectometry. Sensors, 19.","DOI":"10.3390\/s19224994"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1007\/s00190-011-0511-x","article-title":"GPS snow depth meter with geometry-free linear combinations of carrier phases","volume":"86","author":"Ozeki","year":"2012","journal-title":"J. Geod."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1623","DOI":"10.1016\/j.asr.2014.03.005","article-title":"Sensing snow height and surface temperature variations in Greenland from GPS reflected signals","volume":"53","author":"Jin","year":"2014","journal-title":"Adv. Space Res."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Yu, K., Wang, S., Li, Y., Chang, X., and Li, J. (2019). Snow Depth Estimation with GNSS-R Dual Receiver Observation. Remote Sens., 11.","DOI":"10.3390\/rs11172056"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1007\/BF00648343","article-title":"Least-squares frequency analysis of unequally spaced data","volume":"39","author":"Lomb","year":"1976","journal-title":"Astrophys. Space Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"835","DOI":"10.1086\/160554","article-title":"Studies in astronomical time series analysis. II\u2014Statistical aspects of spectral analysis of unevenly spaced data","volume":"263","author":"Scargle","year":"1982","journal-title":"Astrophys. J."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Wang, X., Zhang, Q., and Zhang, S. (2018). Water levels measured with SNR using wavelet decomposition and Lomb\u2013Scargle periodogram. GPS Solut., 22.","DOI":"10.1007\/s10291-017-0684-8"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"RS6003","DOI":"10.1029\/2007RS003652","article-title":"Mapping the GPS multipath environment using the signal-to-noise ratio (SNR)","volume":"42","author":"Bilich","year":"2007","journal-title":"Radio Sci."},{"key":"ref_30","first-page":"723","article-title":"Decomposition of Hardy Functions into Square Integrable Wavelets of Constant Shape","volume":"4","author":"Grossmann","year":"1984","journal-title":"Soc. Ind. Appl. Math."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1109\/34.192463","article-title":"A Theory for Multiresolution Signal Decomposition: The Wavelet Representation","volume":"11","author":"Mallat","year":"1989","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Daubechies, I. (1992). Ten Lectures on Wavelets, Society for Industrial and Applied Mathematics.","DOI":"10.1137\/1.9781611970104"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2951","DOI":"10.1002\/hyp.8329","article-title":"Snow measurement by GPS interferometric reflectometry: An evaluation at Niwot Ridge, Colorado","volume":"26","author":"Gutmann","year":"2012","journal-title":"Hydrol. Process."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/0169-2070(92)90008-W","article-title":"Error measures for generalizing about forecasting methods: Empirical comparisons","volume":"8","author":"Armstrong","year":"1992","journal-title":"Int. J. Forecast."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1080\/13658810500286976","article-title":"On the use of dimensioned measures of error to evaluate the performance of spatial interpolators","volume":"20","author":"Willmott","year":"2006","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1111\/j.1467-9639.1980.tb00398.x","article-title":"Upper and Lower Bounds for the Sample Standard Deviation","volume":"2","author":"Shiffler","year":"1980","journal-title":"Teach. Stat."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"3561","DOI":"10.1109\/TGRS.2018.2802494","article-title":"Snow Water Equivalent of Dry Snow Derived From GNSS Carrier Phases","volume":"56","author":"Henkel","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2646","DOI":"10.1109\/TAP.2015.2414950","article-title":"Validating the Variability of Snow Accumulation and Melting From GPS-Reflected Signals: Forward Modeling","volume":"63","author":"Najibi","year":"2015","journal-title":"IEEE Trans. Antennas Propag."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"4465","DOI":"10.1029\/2018WR024431","article-title":"Retrieval of Snow Water Equivalent, Liquid Water Content, and Snow Height of Dry and Wet Snow by Combining GPS Signal Attenuation and Time Delay","volume":"55","author":"Koch","year":"2019","journal-title":"Water Resour. Res."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/20\/3352\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,4]],"date-time":"2024-07-04T05:47:55Z","timestamp":1720072075000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/20\/3352"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,14]]},"references-count":39,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2020,10]]}},"alternative-id":["rs12203352"],"URL":"https:\/\/doi.org\/10.3390\/rs12203352","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,14]]}}}
