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Retrieval of Antarctic sea ice freeboard and thickness from HY-2B satellite altimeter data

Acta Oceanologica Sinica 2024年第3期43卷 87-101页

作者： Yizhuo Chen Xiaoping Pang Qing Ji Zhongnan Yan Zeyu Liang Chenlei Zhang Chinese Antarctic Center of surveying and mapping Wuhan UniversityWuhan 430079China key laboratory of polar surveying and mapping science Ministry of Natural ResourcesWuhan 430079China key laboratory of polar Environment Monitoring and Public Governance Ministry of EducationWuhan 430079China 4 School of Geography and Tourism Anhui Normal UniversityWuhu 241002China

Antarctic sea ice is an important part of the Earth’s atmospheric system,and satellite remote sensing is an important technology for observing Antarctic sea ice.Whether Chinese Haiyang-2B(HY-2B)satellite altimeter data could be used to estimate sea ice freeboard and provide alternative Antarctic sea ice thickness information with a high precision and long time series,as other radar altimetry satellites can,needs further investigation.This paper proposed an algorithm to discriminate leads and then retrieve sea ice freeboard and thickness from HY-2B radar altimeter data.We first collected the Moderate-resolution Imaging Spectroradiometer ice surface temperature(IST)product from the National Aeronautics and Space Administration to extract leads from the Antarctic waters and verified their accuracy through Sentinel-1 Synthetic Aperture Radar images.Second,a surface classification decision tree was generated for HY-2B satellite altimeter measurements of the Antarctic waters to extract leads and calculate local sea surface heights.We then estimated the Antarctic sea ice freeboard and thickness based on local sea surface heights and the static equilibrium equation.Finally,the retrieved HY-2B Antarctic sea ice thickness was compared with the CryoSat-2 sea ice thickness and the Antarctic Sea Ice Processes and Climate(ASPeCt)ship-based observed sea ice thickness.The results indicate that our classification decision tree constructed for HY-2B satellite altimeter measurements was reasonable,and the root mean square error of the obtained sea ice thickness compared to the ship measurements was 0.62 m.The proposed sea ice thickness algorithm for the HY-2B radar satellite fills a gap in this application domain for the HY-series satellites and can be a complement to existing Antarctic sea ice thickness products;this algorithm could provide long-time-series and large-scale sea ice thickness data that contribute to research on global climate change.

关键词： HY-2B satellite altimeter classification decision tree sea ice freeboard and thickness Antarctic waters

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ST-LSTM-SA:A New Ocean Sound Velocity Field Prediction Model Based on Deep Learning

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Advances in Atmospheric sciences 2024年第7期41卷 1364-1378页

作者： Hanxiao YUAN Yang LIU Qiuhua TANG Jie LI Guanxu CHEN Wuxu CAI First Institute of Oceanography Ministry of Natural ResourcesQingdao 266061China key laboratory of Oceanic surveying and mapping Ministry of Natural ResourcesQingdao 266061China

The scarcity of in-situ ocean observations poses a challenge for real-time information acquisition in the ocean,Among the crucial hydroacoustic environmental parameters,ocean sound velocity exhibits significant spatial and temporal variability and it is highly relevant io oceanic research.In this study,we propose a new data-driven approach,leveraging deep learning techniques,for the prediction of sound velocity fields(SVFs).Our novel spatiotemporal prediction model,ST-LSTM-SA,combincs Spatiotemporal Long Short-Tcrm Mcmory(ST-LSTM)with a sclf-attention mcchanism to cnablc accurate and real-time prediction of svFs.To circumvent the limited amount of observational data,we employ transfer learning by first training the model using reanalysis datasets,followed by fine-luning it using in-silu analysis dala lo obtain the final prediction model.By utilizing the historical 12-month SVFs as input,our model predicts the SVFs for the subsequent three months.We compare the performance of five models:Artificial Neural Networks(ANN),Long Short-Term Memory(LSTM).Convolutional LSTM(ConvLSTM),ST-LSTM,and our proposed ST-LSTM-SA model in a iest experiment spanning 2019 to 2022.Our results demonstrate that the ST-LSTM-SA model significantly improves the prcdiction accuracy and stability of sound velocity in both tcmporal and spatial dimcnsions.Thc ST-LSTM-SA model not only accurately predicts the ocean sound velocity field(SVF),but also provides valuable insights for spatiotemporal prediclion of other oceanic environmental variables.

关键词： sound velocity field spatiotemporal prediction deep learning self-allention

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Predicting bathymetry based on vertical gravity gradient anomaly and analyses for various influential factors

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Geodesy and Geodynamics 2024年第4期15卷 386-396页

作者： Huan Xu Jinhai Yu Yanyan Zeng Qiuyu Wang Yuwei Tian Zhongmiao Sun College of Earth and Planetary sciences University of Chinese Academy of Sciences Beijing Institute of surveying and mapping National key laboratory of Geoinformation Engineering

The prediction of bathymetry has advanced significantly with the development of satellite altimetry.However, the majority of its data originate from marine gravity anomaly. In this study, based on the expression of vertical gravity gradient(VGG) of a rectangular prism, the governing equations for determining sea depths to invert bathymetry. The governing equation is solved by linearization through an iterative process, and numerical simulations verify its algorithm and its stability. We also study the processing methods of different interference errors. The regularization method improves the stability of the inversion process for errors. A piecewise bilinear interpolation function roughly replaces the lowfrequency error, and numerical simulations show that the accuracy can be improved by 41.2 % after this treatment. For variable ocean crust density, simulation simulations verify that the root-mean-square(RMS) error of prediction is approximately 5 m for the sea depth of 6 km if density is chosen as the average one. Finally, two test regions in the South China Sea are predicted and compared with ship soundings data, RMS errors of predictions are 71.1 m and 91.4 m, respectively.

关键词： Rectangular prism Vertical gravity gradient Bathymetry Numerical simulation Prediction error

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Demand and key technology for a LEO constellation as augmentation of satellite navigation systems

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Satellite Navigation 2024年第1期5卷 1-9页

作者： Yuanxi Yang Yue Mao Xia Ren Xiaolin Jia Bjiao Sun Xi’an Research Institute of surveying and mapping Xi’an710054ShaanxiChina State National key laboratory of Geo-Information Engineering Xi’an710054ShaanxiChina

A Low Earth Orbit(LEO)constellation augmenting satellite navigation is important in the future development of Global Navigation Satellite System(GNSS).GNSS augmented by LEO constellations can improve not only the accuracy of Positioning,Navigation,and Timing(PNT),but also the consistency and reliability of secure PNT system.This paper mainly analyzes the diverse demands of different PNT users for LEO augmented GNSS,including the precision demand in real-time,the availability demand in special areas,the navigation signal enhancement demand in complex electromagnetic environments,and the integrity demand with high security.Correspondingly,the possible contributions of LEO constellations to PNT performance are analyzed from multiple aspects.A particular attention is paid to the special PNT user requirements that cannot be fulfilled with existing GNSS,such as the PNT service demand in the polar regions and the onboard GNSS orbit determination demand of some LEO satellites.The key technologies to be considered in the constellation design,function realization,and payload development of the LEO-augmented navigation system are summarized.

关键词： Low earth orbit navigation constellation Accuracy augmentation Orbit determination Integrity

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Urban growth scenario projection using heuristic cellular automata in arid areas considering the drought impact

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Journal of Arid Land 2024年第4期16卷 580-601页

作者： TANG Xiaoyan FENG Yongjiu LEI Zhenkun CHEN Shurui WANG Jiafeng WANG Rong TANG Panli WANG Mian JIN Yanmin TONG Xiaohua College of surveying&Geo-Informatics Tongji UniversityShanghai 200092China Shanghai key laboratory of Space mapping and Remote Sensing for Planetary Exploration Tongji UniversityShanghai 200092China

Arid areas with low precipitation and sparse vegetation typically yield compact urban pattern,and drought directly impacts urban site selection,growth processes,and future scenarios.Spatial simulation and projection based on cellular automata(CA)models is important to achieve sustainable urban development in arid areas.We developed a new CA model using bat algorithm(BA)named bat algorithm-probability-of-occurrence-cellular automata(BA-POO-CA)model by considering drought constraint to accurately delineate urban growth patterns and project future scenarios of Urumqi City and its surrounding areas,located in Xinjiang Uygur Autonomous Region,China.We calibrated the BA-POO-CA model for the drought-prone study area with 2000 and 2010 data and validated the model with 2010 and 2020 data,and finally projected its urban scenarios in 2030.The results showed that BA-POO-CA model yielded overall accuracy of 97.70%and figure-of-merits(FOMs)of 35.50%in 2010,and 97.70%and 26.70%in 2020,respectively.The inclusion of drought intensity factor improved the performance of BA-POO-CA model in terms of FOMs,with increases of 5.50%in 2010 and 7.90%in 2020 than the model excluding drought intensity factor.This suggested that the urban growth of Urumqi City was affected by drought,and therefore taking drought intensity factor into account would contribute to simulation accuracy.The BA-POO-CA model including drought intensity factor was used to project two possible scenarios(i.e.,business-as-usual(BAU)scenario and ecological scenario)in 2030.In the BAU scenario,the urban growth dominated mainly in urban fringe areas,especially in the northern part of Toutunhe District,Xinshi District,and Midong District.Using exceptional and extreme drought areas as a spatial constraint,the urban growth was mainly concentrated in the"main urban areas-Changji-Hutubi"corridor urban pattern in the ecological scenario.The results of this research can help to adjust urban planning and development policies.Our model is readily applicable to simulating urban grow

关键词： bat algorithm cellular automata(CA) probability-of-occurrence drought intensity algorithm-probability-of-occurrence-cellular automata(BA-POO-CA)model arid areas

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The variation in basal channels and basal melt rates of Pine Island Ice Shelf

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Acta Oceanologica Sinica 2024年第1期43卷 22-34页

作者： Mingliang Liu Zemin Wang Baojun Zhang Xiangyu Song Jiachun An Chinese Antarctic Center of surveying and mapping Wuhan UniversityWuhan 430079China key laboratory of polar Environment Monitoring and Public Governance(Wuhan University) Ministry of EducationWuhan 430079China School of Civil Engineering Shijiazhuang Tiedao UniversityShijiazhuang 050043China key laboratory of Roads and Railway Engineering Safety Control(Shijiazhuang Tiedao University) Ministry of EducationShijiazhuang 050043China

In recent years,there has been a significant acceleration in the thinning,calving and retreat of the Pine Island Ice Shelf(PIIS).The basal channels,results of enhanced basal melting,have the potential to significantly impact the stability of the PIIS.In this study,we used a variety of remote sensing data,including Landsat,REMA DEM,ICESat-1 and ICESat-2 satellite altimetry observations,and Ice Bridge airborne measurements,to study the spatiotemporal changes in the basal channels from 2003 to 2020 and basal melt rate from 2010 to 2017 of the PIIS under the Eulerian framework.We found that the basal channels are highly developed in the PIIS,with a total length exceeding 450 km.Most of the basal channels are ocean-sourced or groundingline-sourced basal channels,caused by the rapid melting under the ice shelf or near the groundingline.A raised seabed prevented warm water intrusion into the eastern branch of the PIIS,resulting in a lower basal melt rate in that area.In contrast,a deepsea trough facilitates warm seawater into the mainstream and the western branch of the PIIS,resulting in a higher basal melt rate in the main-stream,and the surface elevation changes above the basal channels of the mainstream and western branch are more significant.The El Ni?o event in 2015–2016 possibly slowed down the basal melting of the PIIS by modulating wind field,surface sea temperature and depth seawater temperature.Ocean and atmospheric changes were driven by El Ni?o,which can further explain and confirm the changes in the basal melting of the PIIS.

关键词： Pine Island Ice Shelf basal channel basal melt rate digital elevation models(DEMs) satellite altimetry

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Effects of coal-fired power plants on soil microbial diversity and community structures

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Journal of Environmental sciences 2024年第3期137卷 206-223页

作者： Bowen Sun Renbin Zhu Yu Shi Wanying Zhang Zeming Zhou Dawei Ma Runfang Wang Haitao Dai Chenshuai Che Institute of polar Environment&Anhui key laboratory of polar Environment and Global Change School of Earth and Space SciencesUniversity of Science and Technology of ChinaHefei 230026China State key laboratory of Crop Stress Adaptation and Improvement School of Life SciencesHenan UniversityKaifeng 450046China State Grid Anhui Electric Power Research Institute Hefei 230601China

Long-term deposition of atmospheric pollutants emitted from coal combustion and their effects on the eco-environment have been extensively studied around coal-fired power plants.However,the effects of coal-fired power plants on soil microbial communities have received little attention through atmospheric pollutant deposition and coal-stacking.Here,we collected the samples of power plant soils(PS),coal-stacking soils(CSS)and agricultural soils(AS)around three coal-fired power plants and background control soils(BG)in Huainan,a typical mineral resource-based city in East China,and investigated the microbial diversity and community structures through a high-throughput sequencing technique.Coal-stacking significantly increased(pkey factors associated with stacking coal and heavy metal deposition from power plants.This study provided useful insight into better understanding of the relationships between soil microbial communities and long-term disturbances from coal-fired power plants.

关键词： Coal-fired power plants Soil microbial communities Coal-stacking Heavy metals Environmental variables

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The connection of phytoplankton biomass in the Marguerite Bay polynya of the western Antarctic Peninsula to the Southern Annular Mode

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Acta Oceanologica Sinica 2024年第1期43卷 35-47页

作者： Ning Jiang Zhaoru Zhang Ruifeng Zhang Chuning Wang Meng Zhou School of Oceanography Shanghai Jiao Tong UniversityShanghai 200240China key laboratory for polar science Polar Research Institute of ChinaMinistry of Natural ResourcesShanghai 200136China

Antarctic coastal polynyas are biological hotspots in the Southern Ocean that support the abundance of hightrophic-level predators and are important for carbon cycling in the high-latitude oceans.In this study,we examined the interannual variation of summertime phytoplankton biomass in the Marguerite Bay polynya(MBP)in the western Antarctic Peninsula area,and linked such variability to the Southern Annular Mode(SAM)that dominated the southern hemisphere extratropical climate variability.Combining satellite data,atmosphere reanalysis products and numerical simulations,we found that the interannual variation of summer chlorophyll-a(Chl-a)concentration in the MBP is significantly and negatively correlated with the spring SAM index,and weakly correlated with the summer SAM index.The negative relation between summer Chl-a and spring SAM is due to weaker spring vertical mixing under a more positive SAM condition,which would inhibit the supply of iron from deep layers into the surface euphotic layer.The negative relation between spring mixing and spring SAM results from greater precipitation rate over the MBP region in positive SAM phase,which leads to lower salinity in the ocean surface layer.The coupled physical-biological mechanisms between SAM and phytoplankton biomass revealed in this study is important for us to predict the future variations of phytoplankton biomasses in Antarctic polynyas under climate change.

关键词： Marguerite Bay polynya phytoplankton biomass Southern Annular Mode mixed layer depth interannual variation

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Real-time Rescue Target Detection Based on UAV Imagery for Flood Emergency Response

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Journal of Geodesy and Geoinformation science 2024年第1期7卷 74-89页

作者： ZHAO Bofei SUI Haigang ZHU Yihao LIU Chang WANG Wentao State key laboratory of Information Engineering in surveying Mapping and Remote SensingWuhan UniversityWuhan 430079China

Timely acquisition of rescue target information is critical for emergency response after a flood disaster.Unmanned Aerial Vehicles(UAVs)equipped with remote sensing capabilities offer distinct advantages,including high-resolution imagery and exceptional mobility,making them well suited for monitoring flood extent and identifying rescue targets during floods.However,there are some challenges in interpreting rescue information in real time from flood images captured by UAVs,such as the complexity of the scenarios of UAV images,the lack of flood rescue target detection datasets and the limited real-time processing capabilities of the airborne on-board platform.Thus,we propose a real-time rescue target detection method for UAVs that is capable of efficiently delineating flood extent and identifying rescue targets(i.e.,pedestrians and vehicles trapped by floods).The proposed method achieves real-time rescue information extraction for UAV platforms by lightweight processing and fusion of flood extent extraction model and target detection model.The flood inundation range is extracted by the proposed method in real time and detects targets such as people and vehicles to be rescued based on this layer.Our experimental results demonstrate that the Intersection over Union(IoU)for flood water extraction reaches an impressive 80%,and the IoU for real-time flood water extraction stands at a commendable 76.4%.The information on flood stricken targets extracted by this method in real time can be used for flood emergency rescue.

关键词： UAV ﬂood extraction target rescue detection real time

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Source model of the 2018 MW7.5 Papua New Guinea earthquake constrained by InSAR measurements: Insight into a blind rupture beneath the New Guinea Highlands

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Geodesy and Geodynamics 2024年第4期15卷 315-325页

作者： Wei Chen Tianchen Sheng Wei Xiong key laboratory of Earthquake Geodesy Institute of SeismologyChina Earthquake Administration Qinghai Provincial Basic surveying and mapping Institute School of Geodesy and Geomatics Wuhan University

The Southern Highland Fold and Thrust Belt（SHFTB）, the boundary of the Australian plate and the New Guinea Highland block, significantly contributes to the convergent deformation along the plate boundary. However, due to the lack of observation data, the detailed slip pattern of the SHFTB and the orogenic mechanism beneath the New Guinea Highlands remains controversial. On 25 February 2018, the MW7.5 Papua New Guinea（PNG） earthquake struck the southeastern segment of the SHFTB. The detailed rupture characteristics of this event is significant for further clarifying the inter-seismic slip pattern along the SHFTB. Here, the coseismic deformation field of this earthquake was obtained using high-resolution ALOS-2 satellite images. We find that the 2018 MW7.5 PNG earthquake ruptured a large-scaled fault（SHFTB） extending to the lower crust（deeper than 20 km） beneath the New Guinea Highlands, with a dip angle of 24°. The slips on the fault plane are equivalent to moment magnitudes of MW7.51. Three major asperities with thrust-dominated slip of up to 3.94 m are detected on the fault plane. This finding implies that the slip pattern on the eastern segment of the SHFTB is dominated by thrust, rather than with significant sinistral movement, as previously reported. The tectonic deformation across the New Guinea Highlands is possibly concentrated on the large-scale fault SHFTB and primarily controls the intracontinental orogeny in the central Papua New Guinea.

关键词： 2018 M W 7.5 Papua New Guinea earthquake The Southern Highlands Fold-and-Thrust Belt InSAR Slip distribution Seismic risk

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