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Monitoring of the Groundwater Level using GRACE with GLDAS Satellite Data in Ganga Plain, India to Understand the Challenges of Groundwater, Depletion, Problems, and Strategies for Mitigation

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Environmental Challenges 2024年 15卷

作者： Gautam, Pawan Kumar Chandra, Sushil Henry, Pradnita Komal Remote Sensing Applications Centre U.P. Department of Science & Technology Govt. of U.P. India

A sub-surface hydrogeological investigation conducted in the Gangetic Plain of India would involve studying the groundwater resources, aquifer characteristics, and overall hydrogeological conditions in the region. The Gangetic Plain is a vast alluvial plain formed by the sediments deposited by the Ganges and its tributaries, making it a significant groundwater (GW) bearing region, which is surrounded by a thick stratum of unconsolidated Alluvial deposits and comprises rich aquifer systems. This study describes a procedure for estimation of the subsurface GW levels for pre-monsoon, 2021 which has been determined by JPL, RL05, temporal datasets of Gravity Recovery and Climate Experiment (GRACE), and Global Land Data Assimilation System (GLDAS). The water level observed ranged from 2.3 m to 13 m in the Bhabhar and Terai Belt, 14 to 23 m in the Central Alluvial Plain and Khadar Belt, and 24 m to 31 m in the Marginal Alluvial Plain. Two types of variation are seen: local and geological variation. The GW storage justifies the remote sensing perspective and further validates our research study that regional terristrial water storage mapping can be expeditiously and accurately cognizable by the GRACE/GLDAS mission. This method is used to estimate changes in regional GW, it is a very accurate and time-limited method rather than the traditional method of GW estimation. The use of this technology will help in knowing the discharge status of GW in the state and make policies for its over-exploitation. Drinking water can be conserved to a great extent and monitoring of GW can also be done in the time frame. And attention can be given to those districts where water is being exploited more. In view of the increasing impact of climate change on water resources, this modeling will prove vital for understanding future scenarios and planning sustainable management strategies that will aid in the development of adaptation and mitigation measures. © 2024

关键词： Ganga Plain GLDAS GRACE Groundwater level Uttar Pradesh

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Navigating through Complexity by Profiling the Main Threats to Sustainable Tropical Wetlands Management and Governance: A Case Study of Mityana District, Uganda

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Discover Environment 2024年第1期2卷 1-23页

作者： Matovu, Baker Sarfo, Isaac Bbira, Yasin Yeboah, Emmanuel Muhoozi, Yosia Lukambagire, Isaac Amrita School for Sustainable Futures Amrita Vishwa Vidyapeetham Amritapuri Campus Kerala Kollam India College of Geography and Environmental Science Henan University Henan Kaifeng 475004 China District Natural Resources Officer (DNRO) Mityana District Local Government Mityana Uganda School of Remote Sensing and Geomatics Engineering Nanjing University of Information Science and Technology Jiangsu Nanjing 210044 China College of Agricultural and Environmental Sciences (CAES) Makerere University Kampala Uganda

Wetlands are crucial ecosystems that promote sustainable livelihood and biodiversity conservation, especially in tropical regions. However, recent studies have reported increasing threats to wetlands both environmental and human which threaten the provision and acquisition of several wetland benefits. Though there is recognition of the value of wetlands, in most local communities in Uganda;especially around the Lake Wamala region in Mityana district, there is still limited knowledge and research on the benefits of wetlands and the level of threat thus affecting wetland governance. This research addresses this gap by using participatory research to create a baseline inventory that could be used by wetland managers to identify the main wetlands threats to inform policy on how to develop participatory actions and local area-based management practices. The study was conducted in 14 sub-counties and a sample of 105 wetlands along the wetlands of Lake Wamala and River Mayanja wetlands system in Mityana District was captured. Study findings revealed increased human threats to wetlands especially in the River Mayanja seasonal wetlands zone. The increased effects of environmental threats such as climate change are also altering permanent wetlands along Lake Wamala. Our developed inventory based on local participants' perspectives revealed that since the level of damage to wetlands in Mityana especially the permanent wetlands is relatively low, a focus on developing new mapping, and a decentralized approach to wetland management that focuses on capacity building, development of wetlands action plans, increased support to local wetland authorities, and a system thinking approach in wetland threat identification and management could help in the regeneration of most wetlands zones. © The Author(s) 2024.

关键词： Mityana district Uganda Wetland Wetland action plans Wetland resources and ecosystems Wetland threats

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Relative Impacts of Sea Ice Loss and Atmospheric Internal Variability on the Winter Arctic to East Asian Surface Air Temperature Based on Large-Ensemble Simulations with NorESM2

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Advances in Atmospheric sciences 2024年第8期41卷 1511-1526页

作者： Shengping HE Helge DRANGE Tore FUREVIK Huijun WANG Ke FAN Lise Seland GRAFF Yvan J.ORSOLINI Geophysical Institute University of Bergen and Bjerknes Centre for Climate ResearchBergen 5020Norway Nansen Environmental and Remote Sensing Center Bergen 5007Norway Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science&TechnologyNanjing 211544China Nansen-Zhu International Research Center Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 511458China School of Atmospheric Science Sun Yat-Sen Universityand Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 519082China Norwegian Meteorological Institute Oslo 0313Norway Norwegian Institute for Air Research Kjeller 2007Norway

To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia”(WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day(or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day(or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four(ten) times larger than the ice-induced East Asian cooling in the present-day(future) experiment;the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60%(80%) to the Arctic winter warming in the present-day(future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-lossinduced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.

关键词： Arctic sea ice loss warm Arctic–cold East Asia atmospheric internal variability large-ensemble simulation NorESM2 PAMIP

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Leader-Follower Consensus Control For Multi-Spacecraft With The Attitude Observers On SO(3) 4

Leader-Follower Consensus Control For Multi-Spacecraft With ...

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4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Yang, Nanji Wang, Zhifu Huang, Di Beijing Institute of Control Engineering Beijing100190 China Wuhan University School of Cyber Science and Engineering Wuhan China Institute of Aerospace Science and Technology Wuhan University School of Remote Sensing and Information Engineering Hubei Province Wuhan430072 China

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

The issue of leader-follower consensus control for the multi-spacecraft structure on SO(3) has been studied in this article. An attitude observer has been utilized to reckon the attitude information of the reference spacecraft, which is not available for all followers. A new attitude error has been proposed. With the observer and the proposed attitude error, sliding mode control has been exploited to investigate a distributed control protocol for the leader-follower systems. Both the availability of the observer and the feasibility of the control approach are rigorously mathematically proven. Finally, a simulation outcomes confirm the superiority and validity of the protocols. © 2022 IEEE.

关键词： Spacecraft

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The shifts of precipitation phases and their impacts

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science China Earth sciences 2025年第2期68卷 425-443页

作者： Xuemei LI Tao CHE Yuanlong TANG Huan’e DUAN Guigang WANG Xu ZHANG Chuanming YANG Jun WU Yue ZHANG Lanhai LI Faculty of Geomatics Lanzhou Jiaotong UniversityLanzhou 730070China National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring Lanzhou 730070China Key Laboratory of Science and Technology in Surveying&Mapping Gansu Province Lanzhou 730070China Key Laboratory of Cryospheric Science and Frozen Soil Engineering Heihe Remote Sensing Experimental Research StationNorthwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000China Xinjiang Key Laboratory of Water Cycle and Utilization in Arid Zone Xinjiang Institute of Ecology and Geography Chinese academy of SciencesUrumqi 830011China Tianshan Snow Cover and Avalanche Observation and Research Station of Xinjiang Xinyuan 835800China

Precipitation comes in various phases, including rainfall, snowfall, sleet, and hail. Shifts of precipitation phases, as well as changes in precipitation amount, intensity, and frequency, have significant impacts on regional climate, hydrology,ecology, and the energy balance of the land-atmosphere system. Over the past century, certain progress has been achieved in aspects such as the observation, discrimination, transformation, and impact of precipitation phases. Mainly including: since the1980s, studies on the observation, formation mechanism, and prediction of precipitation phases have gradually received greater attention and reached a certain scale. The estimation of different precipitation phases using new detection theories and methods has become a research focus. Avariety of discrimination methods or schemes, such as the potential thickness threshold method of the air layer, the temperature threshold method of the characteristic layer, and the near-surface air temperature threshold method,have emerged one after another. Meanwhile, comparative studies on the discrimination accuracy and applicability assessment of multiple methods or schemes have also been carried out simultaneously. In recent years, the shift of precipitation from solid to liquid(SPSL) in the mid-to-high latitudes of the Northern Hemisphere has become more pronounced due to global warming and human activities. It leads to an increase in rain-on-snow(ROS) events and avalanche disasters, affecting the speed, intensity, and duration of spring snow-melting, accelerating sea ice and glacier melting, releasing carbon from permafrost, altering soil moisture, productivity, and phenological characteristics of ecosystems, and thereby affecting their structures, processes, qualities, and service functions. Although some progress has been made in the study of precipitation phases, there remains considerable research potential in terms of completeness of basic data, reliability of discrimination schemes, a

关键词： Precipitation phases Shift of precipitation from solid to liquid(SPSL) Climate change Water cycle processes Snowandicepr sses Snow and ice-related disasters Carbon emission from permafrost Ecosystems

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Three-dimensional modelling of soil organic carbon density and carbon sequestration potential estimation in a dryland farming region of China

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Journal of Geographical sciences 2021年第10期31卷 1453-1468页

作者： SUN Zhongxiang BAI Huiqing YE Huichun ZHUO Zhiqing HUANG Wenjiang State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteCASBeijing 100094China Key Laboratory of Plant Resources Institute of BotanyCASBeijing 100093China Key Laboratory of Earth Observation of Hainan Province Sanya 572029HainanChina Institute of Agricultural Remote Sensing and Institute of Agricultural Remote Sensing and Information Technology Application Zhejiang UniversityHangzhou 310058China University of Chinese Academy of Sciences Beijing 100049China

Soil organic carbon density(SOCD)and soil organic carbon sequestration potential(SOCP)play an important role in carbon cycle and mitigation of greenhouse gas ***,the majority of studies focused on a two-dimensional scale,especially lacking of field measured *** employed the interpolation method with gradient plane nodal function(GPNF)and Shepard(SPD)across a range of parameters to simulate SOCD with a 40 cm soil layer depth in a dryland farming region(DFR)of *** SOCP was estimated using a carbon saturation *** demonstrated the GPNF method was proved to be more effective in simulating the spatial distribution of SOCD at the vertical magnification multiple and search point values of 3.0×106 and 25,*** soil organic carbon storage(SOCS)of 40 cm and 20 cm soil layers were estimated as 22.28×10^(11)kg and 13.12×10^(11)kg simulated by GPNF method in *** SOCP was estimated as 0.95×10^(11)kg considered as a carbon sink at the 20–40 cm soil ***,the SOCP was estimated as–2.49×10^(11)kg considered as a carbon source at the 0–20 cm soil *** research has important values for the scientific use of soil resources and the mitigation of greenhouse gas emissions.

关键词： soil organic carbon density gradient plane nodal function soil organic carbon storage soil organic carbon sequestration potential

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Impact of EnKF assimilating Himawari-8 all-sky infrared radiance on the forecasting of a warm-sector rainstorm event

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science China Earth sciences 2024年第10期67卷 3110-3127页

作者： Shanshan LOU Lei ZHU Xuexing QIU Guangzhou CHEN Song YUAN Shengnan ZHOU Anhui Meteorological Observatory Hefei 230031China Key Laboratory of Meteorological Disaster Ministry of Education(KLME)Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Joint International Research Laboratory of Climate and Environment Change(ILCEC)Nanjing University of Information Science&TechnologyNanjing 210044China Huaihe River Basin Meteorological Center Hefei 230031China Shouxian National Climatology Observatory Huaihe River Basin Typical Farm Eco-Meteorological Experiment Field of CMAShouxian National Comprehensive Meteorological Observation Special Experimental OutfieldShouxian 232200China Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing Hefei 230031China

Warm-sector rainstorms are highly localized events, with weather systems and triggering mechanisms are not obvious,leading to limited forecasting capabilities in numerical models. Based on the ensemble Kalman filter(PSU-En KF) assimilation system and the regional mesoscale model WRF, this study conducted a simulation experiment assimilating all-sky infrared(IR)radiance for a warm-sector rainstorm in East China and investigated the positive impact of assimilating the Himawari-8 moisture channel all-sky IR radiance on the forecast of the rainstorm. Results indicate that hourly cycling assimilation of all-sky IR radiance can significantly improve the forecast accuracy of this warm-sector rainstorm. There is a notable increase in the Threat Score(TS), with the simulated location and intensity of the 3-hour precipitation aligning more closely with observations. These improvements result from the assimilation of cloud-affected radiance, which introduces more mesoscale convective information into the model's initial fields. The adjustments include enhancements to the moisture field, such as increased humidity and moisture transport, and modifications to the wind field, including the intrusion of mid-level cold air and the strengthening of lowlevel convergent shear. These factors are critical in improving the forecast of this warm-sector rainstorm event.

关键词： Ensemble Kalman filter WRF model Himawari-8 All-sky radiance Warm-sector rainstorm

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Lightweight Synthetic Aperture Radar Image Transmission Facility Detection Method Based on YOLOv5

Lightweight Synthetic Aperture Radar Image Transmission Faci...

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Computer Vision, Image and Deep Learning (CVIDL), International Conference on

作者： Gang Wen Fangrong Zhou Hui Yu Yi Ma Guofang Wang Yifan Wang Hao Geng Jun Cao Power Remote Sensing Technology Joint Laboratory (Yunnan Power Grid Power Science Research Institute of China Southern Power Grid Company) Kunming China

ISBN: (数字)9798350373820

ISBN: (纸本)9798350373837

Transmission facilities play a crucial role in ensuring electrical safety. Implementing remote sensing monitoring for transmission facilities in challenging terrains offers robust support for daily maintenance inspections and early accident warnings. In view of the small scale of power facility targets relative to surrounding terrain features in high-resolution Synthetic Aperture Radar (SAR) images, this paper proposes a lightweight transmission facility target recognition method based on an improved YOLOv5 network. The paper mainly focuses on network improvement and lightweight processing. In the YOLOv5 network, fused dilated convolutions and Convolutional Block Attention Module (CBAM) attention mechanisms are introduced to adjust the weights of small target receptive fields, enhancing the feature extraction of small target power facilities. The Filter Pruning via Geometric Median (FPGM) pruning is used to adjust the network architecture, remove redundant feature modules, and achieve lightweight models. The Varifocal loss is used as the loss function to balance positive and negative classes, highlight the contribution of positive examples, and improve model accuracy. The results show that after optimization, the accuracy can be improved to a maximum of $\mathbf{9 8. 2 \%}$. After pruning, the model size significantly decreases, and the inference time can be reduced to below 3 ms. Compared with current mainstream algorithms, the performance is greatly improved, which can meet the needs of transmission facility target detection in remote sensing SAR images.

关键词： YOLO Accuracy Power transmission lines Target recognition Biological system modeling Network architecture Radar polarimetry

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UDT:U-shaped deformable transformer for subarachnoid haemorrhage image segmentation

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CAAI Transactions on Intelligence technology 2024年第3期9卷 756-768页

作者： Wei Xie Lianghao Jin Shiqi Hua Hao Sun Bo Sun Zhigang Tu Jun Liu Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning Central China Normal UniversityWuhanChina School of Computer Science Central China Normal UniversityWuhanChina National Language Resources Monitoring and Research Center for Network Media Central China Normal UniversityWuhanChina The First Affiliated Hospital of Dalian Medical University DalianChina State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina Information Systems Technology and Design Pillar Singapore University of Technology and DesignSingaporeSingapore

Subarachnoid haemorrhage(SAH),mostly caused by the rupture of intracranial aneu-rysm,is a common disease with a high fatality *** lesions are generally diffusely distributed,showing a variety of scales with irregular *** complex characteristics of lesions make SAH segmentation a challenging *** cope with these difficulties,a u-shaped deformable transformer(UDT)is proposed for SAH ***,first,a multi-scale deformable attention(MSDA)module is exploited to model the diffuseness and scale-variant characteristics of SAH lesions,where the MSDA module can fuse features in different scales and adjust the attention field of each element dynamically to generate discriminative multi-scale ***,the cross deformable attention-based skip connection(CDASC)module is designed to model the irregular edge char-acteristic of SAH lesions,where the CDASC module can utilise the spatial details from encoder features to refine the spatial information of decoder ***,the MSDA and CDASC modules are embedded into the backbone Res-UNet to construct the proposed *** experiments are conducted on the self-built SAH-CT dataset and two public medical datasets(GlaS and MoNuSeg).Experimental results show that the presented UDT achieves the state-of-the-art performance.

关键词： image segmentation medical image processing

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DeepLCZChange: A remote sensing DEEP LEARNING MODEL ARCHITECTURE FOR URBAN CLIMATE RESILIENCE

arXiv

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arXiv 2023年

作者： Sun, Wenlu Sun, Yao Liu, Chenying Albrecht, Conrad M. Data Science in Earth Observation Technical University of Munich Germany Remote Sensing Technology Institute German Aerospace Center Germany

Urban land use structures impact local climate conditions of metropolitan areas. To shed light on the mechanism of local climate wrt. urban land use, we present a novel, data-driven deep learning architecture and pipeline, DeepLCZChange, to correlate airborne LiDAR data statistics with the Landsat 8 satellite's surface temperature product. A proof-of-concept numerical experiment utilizes corresponding remote sensing data for the city of New York to verify the cooling effect of urban forests. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep neural networks

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