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  • 1
    Keywords: remote sensing ; GIS ; water resources mapping ; water resources management ; eduation and outreaches ; water quality ; drought and flooding
    Description / Table of Contents: Perea-Moreno, A.; Aguilera-Ureña, M.; Meroño-De Larriva, J.; Manzano-Agugliaro, F. Assessment of the Potential of UAV Video Image Analysis for Planning Irrigation Needs of Golf Courses. Water 2016, 8(12), 584; https://doi.org/10.3390/w8120584 --- Frappart, F.; Bourrel, L.; Brodu, N.; Riofrío Salazar, X.; Baup, F.; Darrozes, J.; Pombosa, R. Monitoring of the Spatio-Temporal Dynamics of the Floods in the Guayas Watershed (Ecuadorian Pacific Coast) Using Global Monitoring ENVISAT ASAR Images and Rainfall Data. Water 2017, 9(1), 12; https://doi.org/10.3390/w9010012 --- Li, Y.; Gong, H.; Zhu, L.; Li, X. Measuring Spatiotemporal Features of Land Subsidence, Groundwater Drawdown, and Compressible Layer Thickness in Beijing Plain, China. Water 2017, 9(1), 64; https://doi.org/10.3390/w9010064 --- Yang, F.; Guo, J.; Tan, H.; Wang, J. Automated Extraction of Urban Water Bodies from ZY‐3 Multi‐Spectral Imagery. Water 2017, 9(2), 144; https://doi.org/10.3390/w9020144 --- Lee, J.; Choi, H. Improvements to Runoff Predictions from a Land Surface Model with a Lateral Flow Scheme Using Remote Sensing and In Situ Observations. Water 2017, 9(2), 148; https://doi.org/10.3390/w9020148 --- Sharif, H.; Al-Zahrani, M.; Hassan, A. Physically, Fully-Distributed Hydrologic Simulations Driven by GPM Satellite Rainfall over an Urbanizing Arid Catchment in Saudi Arabia. Water 2017, 9(3), 163; https://doi.org/10.3390/w9030163 --- Wang, X.; Chen, H.; Chen, Y. Large Differences between Glaciers 3D Surface Extents and 2D Planar Areas in Central Tianshan. Water 2017, 9(4), 282; https://doi.org/10.3390/w9040282 --- Wang, R.; Chen, J.; Wang, X. Comparison of IMERG Level-3 and TMPA 3B42V7 in Estimating Typhoon-Related Heavy Rain. Water 2017, 9(4), 276; https://doi.org/10.3390/w9040276 --- Pan, C.; Wang, X.; Liu, L.; Huang, H.; Wang, D. Improvement to the Huff Curve for Design Storms and Urban Flooding Simulations in Guangzhou, China. Water 2017, 9(6), 411; https://doi.org/10.3390/w9060411 --- Ouyang, H.; Shih, S.; Wu, C. Optimal Combinations of Non-Sequential Regressors for ARX-Based Typhoon Inundation Forecast Models Considering Multiple Objectives. Water 2017, 9(7), 519; https://doi.org/10.3390/w9070519 --- Lu, Y.; Song, W.; Lu, J.; Wang, X.; Tan, Y. An Examination of Soil Moisture Estimation Using Ground Penetrating Radar in Desert Steppe. Water 2017, 9(7), 521; https://doi.org/10.3390/w9070521 --- Tekeli, A. Exploring Jeddah Floods by Tropical Rainfall Measuring Mission Analysis. Water 2017, 9(8), 612; https://doi.org/10.3390/w9080612 --- Wang, X.; Xie, H. A Review on Applications of Remote Sensing and Geographic Information Systems (GIS) in Water Resources and Flood Risk Management. Water 2018, 10(5), 608; https://doi.org/10.3390/w10050608
    Pages: Online-Ressource (VIII, 222 Seiten) , Illustrationen, Diagramme
    Edition: Printed Edition of the Special Issue Published in Water
    ISBN: 9783038429814
    Language: English
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  • 2
    Publication Date: 2023-11-11
    Description: The thicknesses of sea ice and sub-ice platelet layer were measured at regular intervals on fast ice in McMurdo Sound, Antarctica in November of 2017. Thirty-metre cross-profiles were established at each site, and snow depths were measured at 0.5 m intervals along the transect lines with a MagnaProbe. A mean snow depth for each site was derived from these 120 measurements. Freeboard, sea ice thickness and sub-ice platelet layer thickness were recorded at five locations at each site - at the central crossing point and at the end points of each transect. The mean of these was then calculated and taken as representative of the site. Ice thicknesses were measured by using a tape measure with a brass T-anchor attached at the zero mark. This was deployed vertically through the drill-hole and allowed to rotate to a horizontal alignment when exiting the bottom of the drill-hole at the ice-ocean interface. From this position the anchor is slowly pulled upwards until some resistance is met and the first measurement is taken. This resistance is taken to mark the sub-ice platelet layer/ocean interface. The tape measure is then pulled harder, forcing the bar to pass through the sub-ice platelet layer until it sits flush against the sea ice/sub-ice platelet layer interface where a second measurement is taken. Measurement sites were about 10 km apart.
    Keywords: Antarctica; Date/Time of event; Deep South National Science Challenge: Targeted observations and process-informed modeling of Antarctic sea ice; Event label; Fast ice; Freeboard; ICEDRILL; Ice drill; Identification; Latitude of event; Longitude of event; McMurdo-2017_1; McMurdo-2017_11; McMurdo-2017_2; McMurdo-2017_20; McMurdo-2017_21; McMurdo-2017_22; McMurdo-2017_23; McMurdo-2017_24; McMurdo-2017_3; McMurdo-2017_4; McMurdo-2017_5; McMurdo-2017_6; McMurdo-2017_7; McMurdo-2017_70; McMurdo-2017_71; McMurdo-2017_72; McMurdo-2017_73; McMurdo-2017_74; McMurdo-2017_75; McMurdo-2017_76; McMurdo-2017_77; McMurdo-2017_EM31_1; McMurdo-2017_EM31_2; McMurdo Sound; PIPERS; Polynyas, ice production, and seasonal evolution in the Ross Sea; Sea ice thickness; Snow layer; Snow thickness; Sub-ice platelet layer; Sub-ice platelet-layer thickness; TOPOMASI
    Type: Dataset
    Format: text/tab-separated-values, 115 data points
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  • 3
    Publication Date: 2023-11-11
    Description: The thicknesses of sea ice and sub-ice platelet layer were measured at regular intervals on fast ice in McMurdo Sound, Antarctica in November of 2016. Thirty-metre cross-profiles were established at each site, and snow depths were measured at 0.5 m intervals along the transect lines with a MagnaProbe. A mean snow depth for each site was derived from these 120 measurements. Freeboard, sea ice thickness and sub-ice platelet layer thickness were recorded at five locations at each site - at the central crossing point and at the end points of each transect. The mean of these was then calculated and taken as representative of the site. Ice thicknesses were measured by using a tape measure with a brass T-anchor attached at the zero mark. This was deployed vertically through the drill-hole and allowed to rotate to a horizontal alignment when exiting the bottom of the drill-hole at the ice-ocean interface. From this position the anchor is slowly pulled upwards until some resistance is met and the first measurement is taken. This resistance is taken to mark the sub-ice platelet layer/ocean interface. The tape measure is then pulled harder, forcing the bar to pass through the sub-ice platelet layer until it sits flush against the sea ice/sub-ice platelet layer interface where a second measurement is taken. Measurement sites were about 10 km apart.
    Keywords: Antarctica; Date/Time of event; Deep South National Science Challenge: Targeted observations and process-informed modeling of Antarctic sea ice; Event label; Fast ice; Freeboard; ICEDRILL; Ice drill; Identification; Latitude of event; Longitude of event; McMurdo-2016_1; McMurdo-2016_10; McMurdo-2016_11; McMurdo-2016_12; McMurdo-2016_13; McMurdo-2016_14; McMurdo-2016_15; McMurdo-2016_16; McMurdo-2016_17; McMurdo-2016_18; McMurdo-2016_19; McMurdo-2016_2; McMurdo-2016_3; McMurdo-2016_4; McMurdo-2016_5; McMurdo-2016_6; McMurdo-2016_7; McMurdo-2016_8; McMurdo-2016_9; McMurdo Sound; PIPERS; Polynyas, ice production, and seasonal evolution in the Ross Sea; Sea ice thickness; Snow layer; Snow thickness; Sub-ice platelet layer; Sub-ice platelet-layer thickness; TOPOMASI
    Type: Dataset
    Format: text/tab-separated-values, 95 data points
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  • 4
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    PANGAEA
    In:  Supplement to: Xie, Hongjie; Ackley, Stephen F; Yi, D; Zwally, H Jay; Wagner, P; Weissling, Blake P; Lewis, M; Ye, K (2011): Sea-ice thickness distribution of the Bellingshausen Sea from surface measurements and ICESat altimetry. Deep Sea Research Part II: Topical Studies in Oceanography, 58(9-10), 1039-1051, https://doi.org/10.1016/j.dsr2.2010.10.038
    Publication Date: 2023-12-13
    Description: Although sea-ice extent in the Bellingshausen-Amundsen (BA) seas sector of the Antarctic has shown significant decline over several decades, there is not enough data to draw any conclusion on sea-ice thickness and its change for the BA sector, or for the entire Southern Ocean. This paper presents our results of snow and ice thickness distributions from the SIMBA 2007 experiment in the Bellingshausen Sea, using four different methods (ASPeCt ship observations, downward-looking camera imaging, ship-based electromagnetic induction (EM) sounding, and in situ measurements using ice drills). A snow freeboard and ice thickness model generated from in situ measurements was then applied to contemporaneous ICESat (satellite laser altimetry) measured freeboard to derive ice thickness at the ICESat footprint scale. Errors from in situ measurements and from ICESat freeboard estimations were incorporated into the model, so a thorough evaluation of the model and uncertainty of the ice thickness estimation from ICESat are possible. Our results indicate that ICESat derived snow freeboard and ice thickness distributions (asymmetrical unimodal tailing to right) for first-year ice (0.29 ± 0.14 m for mean snow freeboard and 1.06 ± 0.40 m for mean ice thickness), multi-year ice (0.48 ± 0.26 and 1.59 ± 0.75 m, respectively), and all ice together (0.42 ± 0.24 and 1.38 ± 0.70 m, respectively) for the study area seem reasonable compared with those values from the in situ measurements, ASPeCt observations, and EM measurements. The EM measurements can act as an appropriate supplement for ASPeCt observations taken hourly from the ship's bridge and provide reasonable ice and snow distributions under homogeneous ice conditions. Our proposed approaches: (1) of using empirical equations relating snow freeboard to ice thickness based on in situ measurements and (2) of using isostatic equations that replace snow depth with snow freeboard (or empirical equations that convert freeboard to snow depth), are efficient and important ways to derive ice thickness from ICESat altimetry at the footprint scale for Antarctic sea ice. Spatial and temporal snow and ice thickness from satellite altimetry for the BA sector and for the entire Southern Ocean is therefore possible.
    Keywords: Bellingshausen Sea; Event label; Freeboard; ICE; Ice station; International Polar Year (2007-2008); IPY; Latitude of event; Longitude of event; Nathaniel B. Palmer; NBP0709; Number of measurements; Sea ice thickness; SIMBA; SIMBA_Brussels; SIMBA_Fabra; SIMBA_Station-1; SIMBA_Station-2; SIMBA_Station-3; Snow thickness
    Type: Dataset
    Format: text/tab-separated-values, 30 data points
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  • 5
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    PANGAEA
    In:  Supplement to: Tekeli, Ahmet E; Kern, Stefan; Ackley, Stephen F; Ozsoy-Cicek, Burcu; Xie, Hongjie (2011): Summer Antarctic sea ice as seen by ASAR and AMSR-E and observed during two IPY field cruises: a case study. Annals of Glaciology, 52(57), 327-336, https://doi.org/10.3189/172756411795931697
    Publication Date: 2024-02-17
    Description: Envisat Advanced Synthetic Aperture Radar (ASAR) Wide Swath Mode (WSM) images are used to derive C-band HH-polarization normalized radar cross sections (NRCS). These are compared with ice-core analysis and visual ship-based observations of snow and ice properties observed according to the Antarctic Sea Ice Processes and Climate (ASPeCt) protocol during two International Polar Year summer cruises (Oden 2008 and Palmer 2009) in West Antarctica. Thick first-year (TFY) and multi-year (MY) ice were the dominant ice types. The NRCS value ranges between -16.3 ± 1.1 and -7.6 ± 1.0 dB for TFY ice, and is -12.6 ± 1.3 dB for MY ice; for TFY ice, NRCS values increase from ~-15 dB to -9 dB from December/January to mid-February. In situ and ASPeCt observations are not, however, detailed enough to interpret the observed NRCS change over time. Co-located Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) vertically polarized 37 GHz brightness temperatures (TB37V), 7 day and 1 day averages as well as the TB37V difference between ascending and descending AMSR-E overpasses suggest the low NRCS values (-15 dB) are associated with snowmelt being still in progress, while the change towards higher NRCS values (-9dB) is caused by commencement of melt-refreeze cycles after about mid-January.
    Keywords: International Polar Year (2007-2008); IPY
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 6
    Publication Date: 2024-02-17
    Keywords: Angle; Campaign; DATE/TIME; DynaLiFe; Echo backscatter; Event label; Ice concentration; ICESUR; Ice survey; Ice thickness; Ice type; Latitude of event; Longitude of event; Nathaniel B. Palmer; NBP0901; NBP0901_Ao1; NBP0901_Ao2; NBP0901_Ao3; NBP0901_Ao4; NBP0901_Ao5; NBP0901_Ao6; NBP0901_Ao7; Number of pixels; Oden; OSO08/09; OSO0809_Ao1; OSO0809_Ao2; OSO0809_Ao3; Snow thickness; SouthernOcean; Southern Ocean; Standard deviation; Time point, descriptive
    Type: Dataset
    Format: text/tab-separated-values, 115 data points
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  • 7
    Publication Date: 2024-02-17
    Keywords: Campaign; Comment; DATE/TIME; DynaLiFe; Echo backscatter; Event label; Freeboard; ICESUR; Ice survey; Ice thickness; Ice type; Latitude of event; Longitude of event; Nathaniel B. Palmer; NBP0901; NBP0901_IC1; NBP0901_IC2; Oden; OSO08/09; OSO0809_IC1; OSO0809_IC2; Snow thickness; SouthernOcean; Southern Ocean; Temperature, air; Time point, descriptive
    Type: Dataset
    Format: text/tab-separated-values, 34 data points
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  • 8
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    PANGAEA
    In:  Supplement to: Zhang, Guoqing; Xie, Hongjie; Kang, Shichang; Yi, Donghui; Ackley, Stephen F (2011): Monitoring lake level changes on the Tibetan Plateau using ICESat altimetry data (2003-2009). Remote Sensing of Environment, 115(7), 1733-1742, https://doi.org/10.1016/j.rse.2011.03.005
    Publication Date: 2023-12-13
    Description: In this study, ICESat altimetry data are used to provide precise lake elevations of the Tibetan Plateau (TP) during the period of 2003-2009. Among the 261 lakes examined ICESat data are available on 111 lakes: 74 lakes with ICESat footprints for 4-7 years and 37 lakes with footprints for 1 -3 years. This is the first time that precise lake elevation data are provided for the 111 lakes. Those ICESat elevation data can be used as baselines for future changes in lake levels as well as for changes during the 2003-2009 period. It is found that in the 74 lakes (56 salt lakes) examined, 62 (i.e. 84%) of all lakes and 50 (i.e. 89%) of the salt lakes show tendency of lake level increase. The mean lake water level increase rate is 0.23 m/year for the 56 salt lakes and 0.27 m/year for the 50 salt lakes of water level increase. The largest lake level increase rate (0.80 m/year) found in this study is the lake Cedo Caka. The 74 lakes are grouped into four subareas based on geographical locations and change tendencies in lake levels. Three of the four subareas show increased lake levels. The mean lake level change rates for subareas I, II, III, IV, and the entire TP are 0.12, 0.26, 0.19, -0.11, and 0.2 m/year, respectively. These recent increases in lake level, particularly for a high percentage of salt lakes, supports accelerated glacier melting due to global warming as the most likely cause.
    Keywords: Argog_Co; Baqan_Co; Cedo_Caka; Chaoyang_Co; Co_Nag; Co_Ngoin; Co_Nyi; Co_Rabamgodang; Con_Arimar; Darab_Co; Date/time end; Date/time start; Dawa_Co; Deyu_Co; Dogai_Coring; Dorsoidong_Co; ELEVATION; Elevation 2; Event label; Gopug_Co; Goren_Co; Gyado_Co; Gyarab_Co; Gyaring_Lake; Gyeze_Caka; Har_Lake; Himalaya; Hoh_Sai_Lake; Hoh_Xil_Lake; Hulu_Lake; ICESat satellite data; International Polar Year (2007-2008); IPY; Jang_Co; Kekao_Lake; Kunggyu_Co; Kushuihuan_Lake; Kyobxang_Co; Lagkor_Co; Lake; Lakes_Tibet; Lake type; Latitude of event; Lixi_Oidaim_Co; Longitude of event; Longwei_Co; Mapam_Yumco; Marye_Co; Meriqancomari; MULT; Multiple investigations; Nam_Co; Namka_Co; Ngangla_Ringco; Ngangzi_Co; Number; Number of years; Peiku_Co; Pibi_Lake; Puma_Yumco; Qagain_Co; Qinghai_Lake; Ringco_Ogma; Ringinyubu_Co; Sector; Selin_Co; Serbug_Co; Standard deviation; Suang_Lake; Tangra_Yumco; Taro_Co; Tibetan Plateau; Urru_Co; Water level change; Waxunggabma_Co; Weishan_Lake; Xianhe_Lake; Xijir_Ulan_Lake; Xogor_Co; Yamzhog_Yumco; Yangain_Canco; Yinbo_Lake; Yurbao_Co; Yuye_Lake; Zhangne_Co; Zhari_Namco; Zige_Tangco
    Type: Dataset
    Format: text/tab-separated-values, 814 data points
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  • 9
    Publication Date: 2024-03-19
    Keywords: Bellingshausen Sea; Brussels/Liege; DATE/TIME; Density, snow; Ice_station_Belgica; Layer thickness; MULT; Multiple investigations; Nathaniel B. Palmer; NBP0709; Sample ID; SIMBA; Site; Snow thickness; Temperature, ice/snow; Temperature gradient, snow
    Type: Dataset
    Format: text/tab-separated-values, 183 data points
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  • 10
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    PANGAEA
    In:  Supplement to: Lewis, Michael J; Tison, Jean-Louis; Weissling, Blake P; Delille, Bruno; Ackley, Stephen F; Brabant, F; Xie, Hongjie (2011): Sea ice and snow cover characteristics during the winter–spring transition in the Bellingshausen Sea: An overview of SIMBA 2007. Deep Sea Research Part II: Topical Studies in Oceanography, 58(9-10), 1019-1038, https://doi.org/10.1016/j.dsr2.2010.10.027
    Publication Date: 2024-03-19
    Description: The Sea Ice Mass Balance in the Antarctic (SIMBA) experiment was conducted from the RVIB N.B. Palmer in September and October 2007 in the Bellingshausen Sea in an area recently experiencing considerable changes in both climate and sea ice cover. Snow and ice properties were observed at 3 short-term stations and a 27-day drift station (Ice Station Belgica, ISB) during the winter-spring transition. Repeat measurements were performed on sea ice and snow cover at 5 ISB sites, each having different physical characteristics, with mean ice (snow) thicknesses varying from 0.6 m (0.1 m) to 2.3 m (0.7 m). Ice cores retrieved every five days from 2 sites and measured for physical, biological, and chemical properties. Three ice mass-balance buoys (IMBs) provided continuous records of snow and ice thickness and temperature. Meteorological conditions changed from warm fronts with high winds and precipitation followed by cold and calm periods through four cycles during ISB. The snow cover regulated temperature flux and controlled the physical regime in which sea ice morphology changed. Level thin ice areas had little snow accumulation and experienced greater thermal fluctuations resulting in brine salinity and volume changes, and winter maximum thermodynamic growth of ~0.6 m in this region. Flooding and snow-ice formation occurred during cold spells in ice and snow of intermediate thickness. In contrast, little snow-ice formed in flooded areas with thicker ice and snow cover, instead nearly isothermal, highly permeable ice persisted. In spring, short-lived cold air episodes did not effectively penetrate the sea ice nor overcome the effect of ocean heat flux, thus favoring net ice thinning from bottom melt over ice thickening from snow-ice growth, in all cases. These warm ice conditions were consistent with regional remote sensing observations of earlier ice breakup and a shorter sea ice season, more recently observed in the Bellingshausen Sea.
    Keywords: International Polar Year (2007-2008); IPY
    Type: Dataset
    Format: application/zip, 3 datasets
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