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Artificial intelligence for geoscience:Progress,challenges,and perspectives

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The Innovation 2024年第5期5卷 136-160,135页

作者： Tianjie zhao Sheng Wang Chaojun Ouyang Min Chen Chenying liu Jin Zhang Long Yu Fei Wang Yong Xie Jun li Fang Wang Sabine Grunwald Bryan MWong Fan Zhang Zhen Qian Yongjun Xu Chengqing Yu Wei Han Tao Sun Zezhi Shao Tangwen Qian zhao Chen Jiangyuan Zeng Huai Zhang Husi Letu Bing Zhang li Wang Lei Luo Chong shi Hongjun Su Hongsheng Zhang Shuai Yin Ni Huang Wei zhao Nan li Chaolei Zheng Yang Zhou Changping Huang Defeng Feng Qingsong Xu Yan Wu Danfeng Hong Zhenyu Wang Yinyi lin Tangtang Zhang Prashant Kumar Antonio Plaza Jocelyn Chanussot Jiabao Zhang Jiancheng shi lizhe Wang Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China School of Computer science China University of GeosciencesWuhan 430078China State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China Key Laboratory of Virtual Geographic Environment(Ministry of Education of PRC) Nanjing Normal UniversityNanjing 210023China Data science in earth Observation Technical University of Munich80333 MunichGermany The National Key Laboratory of Water Disaster Prevention Yangtze Institute for Conservation and DevelopmentHohai UniversityNanjing 210098China Institute of Computing technology Chinese Academy of SciencesBeijing 100190China School of Geographical sciences Nanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008China Soil Water and Ecosystem Sciences DepartmentUniversity of FloridaPO Box 110290GainesvilleFLUSA Materials science Engineering Program Cooperating Faculty Member in the Department of Chemistry and Department of Physics astronomy University of CaliforniaCaliforniaRiversideCA 92521USA Institute of Remote Sensing and Geographical Information System School of Earth and Space SciencesPeking UniversityBeijing 100871China Key Laboratory of Computational Geodynamics University of Chinese Academy of SciencesBeijing 100049China International Research center of Big Data for Sustainable Development Goals Beijing 100094China College of Geography and Remote Sensing Hohai UniversityNanjing 211100China Department of Geography The University of Hong KongHong Kong 999077SARChina Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Nanjing 210044China School of Environmental science and Engineering Nanjing University of Information Science&TechnologyNanjing 210044China Collaborative Inno

This paper explores the evolution of geoscientific inquiry,tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence(AI)and data collection *** models,which are grounded in physical and numerical frameworks,provide robust explanations by explicitly reconstructing underlying physical ***,their limitations in comprehensively capturing {4.’s complexities and uncertainties pose challenges in optimization and real-world *** contrast,contemporary data-driven models,particularly those utilizing machine learning(ML)and deep learning(DL),leverage extensive geoscience data to glean insights without requiring exhaustive theoretical *** techniques have shown promise in addressing {4. science-related ***,challenges such as data scarcity,computational demands,data privacy concerns,and the“black-box”nature of AI models hinder their seamless integration into *** integration of physics-based and data-driven methodologies into hybrid models presents an alternative *** models,which incorporate domain knowledge to guide AI methodologies,demonstrate enhanced efficiency and performance with reduced training data *** review provides a comprehensive overview of geoscientific research paradigms,emphasizing untapped opportunities at the intersection of advanced AI techniques and *** examines major methodologies,showcases advances in large-scale models,and discusses the challenges and prospects that will shape the future landscape of AI in *** paper outlines a dynamic field ripe with possibilities,poised to unlock new understandings of {4.’s complexities and further advance geoscience exploration.

关键词： earth utilizing landscape

基于半球形瞬时撞击坑的近地天体撞击诱发海啸的深水波模型

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天文学报 2024年第5期65卷 110-120页

作者：李妙蕾史建春马月华张瑞利赵海斌唐梦辉杨大陶中国科学院紫金山天文台行星科学重点实验室南京210023 中国科学技术大学天文与空间科学学院合肥230026 中国科学院上海天文台上海200030 南京大学物理学院南京210093 中国科学院比较行星学卓越创新中心合肥230026 国防科工局重大专项工程中心北京100101

采用初始扰动为半球形瞬时撞击坑作为初始条件,建立了近地天体撞击诱发海啸的深水波模型,应用到特定情形下(小行星直径为14. m、撞击速度与密度采用车里雅宾斯克陨击参数、撞击区域平均海洋深度采用太平洋平均水深4.km)研究了近地天体... 详细信息

采用初始扰动为半球形瞬时撞击坑作为初始条件,建立了近地天体撞击诱发海啸的深水波模型,应用到特定情形下(小行星直径为14. m、撞击速度与密度采用车里雅宾斯克陨击参数、撞击区域平均海洋深度采用太平洋平均水深4.km)研究了近地天体撞击海洋诱发海啸的波高最大值随距离和时间的演化情况.对比不同的瞬时撞击坑模型和传播模型对海啸波高的影响发现:半球形瞬时撞击坑诱发的海啸危害比抛物形瞬时撞击坑更大;相对于深水波模型,浅水波模型给出撞击诱发海啸的规模较大;对于中等尺寸(直径在几百米范围内)的小行星,研究其撞击海洋诱发海啸,更适合采用瞬时撞击坑形状为半球形的深水波模型.

关键词：小行星:普通地球流体力学方法:解析

Assessing the active-passive approach at variant incidence angles for microwave brightness temperature downscaling

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International Journal of Digital earth 2021年第10期14卷 1273-1293页

作者： Peng Guo Tianjie zhao Jiancheng shi Hongxin Xu Xiuwei li Shengda Niu College of Information science and Engineering Shandong Agricultural UniversityTaianPeople’s Republic of China State Key Laboratory of Remote Sensing science Aerospace Information Research InstituteChinese Academy of SciencesBeijingPeople’s Republic of China National space science center Chinese Academy of SciencesBeijingPeople’s Republic of China Shanghai academy of spaceflight technology ShanghaiPeople’s Republic of China

The Terrestrial Water Resources Satellite(TWRS)campaign is a planned Chinese candidate satellite mission,and a one-dimensional synthetic aperture technology will be used,resulting in variant incidence angles for collecting synchronous active-passive observations at L-band,which would make brightness temperature(T_(b))downscaling especially challenging when aiming to improve the spatial resolution of soil moisture *** this study,two active-passive T_(b) downscaling algorithms,the time-series regression(TSR)and spectral analysis(SA)algorithms,are assessed comprehensively based on airborne experimental *** results with data collected during the Soil Moisture Experiment 2002(SMEX02)showed that both approaches could provide a reliable downscaled T_(b) at the same incidence *** on the ground and airborne active-passive observations under variant incidence angles from the Soil Moisture Experiment in the Luan River(SMELR)it can be shown that the linear relationship between T_(b) andσis still robust under the case of variant incidence angles,and T_(b)(both h-and v-pol)is better correlated toσvv for most cases thanσ*** downscaling approaches can be applied to active-passive observations under varying incidence ***,SA method performed better than the TSR method according to the lower RMSE values and higher correlation.

关键词： Downscaling brightness temperature active-passive variant incidence angle SMELR

Seamless maps of major elements of the Moon:Results from high-resolution geostationary satellite

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Research in astronomy and Astrophysics 2021年第2期21卷 52-60页

作者： Yu Lu Yun-zhao Wu Cui li Jin-Song Ma Wen-Wen Qi Wei Tan Xiao-Man li Zhi-Cheng shi Hong-Yan He Shu-Wu Dai Guo li Feng-Jing liu Jing-Qiao Wang Xiao-Yan Wang Qi Wang ling-Jie Meng Key Laboratory of Planetary sciences Purple Mountain ObservatoryChinese Academy of SciencesNanjing 210034China School of astronomy and space science University of Science and Technology of ChinaHefei 230026China CAS center for Excellence in Comparative Planetology Hefei 230026China space science Institute Macao University of Science and TechnologyMacaoChina School of Geography and Ocean science Nanjing UniversityNanjing 210023China Jiangsu center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023China Beijing Institute of space Mechanics and Electricity Beijing 100076China Beijing Institute of spacecraft System Engineering Beijing 100076China china Centre for Resources Satellite Data and Application Beijing 100094China earth Observation System and Data center China National Space AdministrationBeijing 100010China

Major elements such as Fe,Ti,Mg,Al,Ca and Si play very important roles in understanding the origin and evolution of the *** maps of these major elements derived from orbital data are based on mosaic images or low-resolution gamma-ray *** hue variations and gaps among orbital boundaries in the mosaic images are not conducive to geological *** paper aims to produce seamless and homogenous distribution maps of major elements using the single-exposure image of the whole lunar disk obtained by china’s high-resolution geostationary satellite,Gaofen-4.with a spatial resolution of500 *** elemental contents of soil samples returned by Apollo and Luna missions are regarded as ground truth,and are correlated with the reflectance of the sampling sites extracted from Gaofen-4.*** final distribution maps of these major oxides are generated with the statistical regression *** these products,the average contents and proportions of the major elements for maria and highlands were estimated and *** results showed that Si O2 and Ti O2 have the highest and lowest fractions in mare and highland areas,***,the relative concentrations of these elements could serve as indicators of geologic processes,e.g.,the obviously asymmetric distributions of Al2 O3,Ca O and Si O2 around Tycho crater may suggest that Tycho crater was formed by an oblique impact from the southwest direction.

关键词： Moon-Data analysis-Imaging spectroscopy

A fundamental theorem for eco-environmental surface modelling and its applications

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science china earth sciences 2020年第8期63卷 1092-1112页

作者： Tianxiang YUE Na zhao Yu liU Yifu WANG Bin ZHANG Zhengping DU Zemeng FAN Wenjiao shi Chuanfa CHEN Mingwei zhao Dunjiang SONG shihai WANG Yinjun SONG Changqing YAN Qiquan li Xiaofang SUN lili ZHANG Yongzhong TIAN Wei WANG Ying’an WANG Shengnan MA Hongsheng HUANG Yimin LU Qing WANG Chenliang WANG Yuzhu WANG Ming LU Wei ZHOU Yi liU Xiaozhe YIN Zong WANG Zhengyi BAO Miaomiao zhao Yapeng zhao Yimeng JIAO Ufra NASEER Bin FAN Saibo li Yang YANG John PWILSON State Key L aboratory of Resources and Environment Information System Institute of Geographical Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China College of Land Resources and Environment Jiangxi Agricultural UniversityNanchang 330045China College of Geomatics Shandong University of Science and TechnologyQingdao 266590China College of Forestry Beijing Forestry UniversityBeijing 100083China School of Land and Resources China West Normal UniversityNanchong 637002China College of Geographical Information and Tourism Chuzhou UniversityChuzhou 239000China Institutes of science and Development Chinese Academy of SciencesBeijing 100190China Department of Information Engineering Shandong University of Science and TechnologyTai'an 271019China College of Resources Sichuan Agricultural UniversityChengdu 611130China College of Geography and Tourism Qufu Normal UniversityRizhao 276828China Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100101China School of Geographical science Southwest UniversityChongqing 400715China National Disaster Reduction center of china Ministry of Emergency ManagementBeijing 100721China Department for Population Data China Population and Development Research CenterBeijing 100081China Department for Industrial Standard China Standardization AdministrationBeijing 100088China The academy of Digital china Fuzhou UniversityFuzhou 350002China National Institute of Environmental Health Chinese Center for Disease Control and PreventionBeijing 100021China School of Information Engineering China University of GeoscienceBeijing 100083China Qian Xuesen Laboratory of space technology Beijing 100094China College of Architecture and Urban Planning Chongqing Jiaotong UniversityChongqing 400074China Jiangsu center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing

We propose a fundamental theorem for eco-environmental surface modelling(FTEEM) in order to apply it into the fields of ecology and environmental science more easily after the fundamental theorem for earth’s surface system modeling(FTESM). The Beijing-Tianjin-Hebei(BTH) region is taken as a case area to conduct empirical studies of algorithms for spatial upscaling, spatial downscaling, spatial interpolation, data fusion and model-data assimilation, which are based on high accuracy surface modelling(HASM), corresponding with corollaries of FTEEM. The case studies demonstrate how eco-environmental surface modelling is substantially improved when both extrinsic and intrinsic information are used along with an appropriate method of HASM. Compared with classic algorithms, the HASM-based algorithm for spatial upscaling reduced the root-meansquare error of the BTH elevation surface by 9 m. The HASM-based algorithm for spatial downscaling reduced the relative error of future scenarios of annual mean temperature by 16%. The HASM-based algorithm for spatial interpolation reduced the relative error of change trend of annual mean precipitation by 0.2%. The HASM-based algorithm for data fusion reduced the relative error of change trend of annual mean temperature by 70%. The HASM-based algorithm for model-data assimilation reduced the relative error of carbon stocks by 4.%. We propose five theoretical challenges and three application problems of HASM that need to be addressed to improve FTEEM.

关键词： HASM FTEEM Spatial upscaling Spatial downscaling Spatial interpolation Data fusion Model-data assimilation Model coupling

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中子辐照对掺镱光纤材料光学特性的影响

物理学报 2021年第19期70卷 1-7页

作者：李奋飞周晓燕张魁宝石兆华陈进湛叶鑫吴卫东李波西南科技大学环境友好能源材料国家重点实验室绵阳621010 中国工程物理研究院激光聚变研究中心绵阳621900

采用改进型化学气相沉积法结合稀土螯合物掺杂制备了系列掺镱光纤预制棒及光纤,并测试了光纤(预制棒)辐照、退火前后的光学性能.结果表明:中子辐照后掺镱光纤材料中与Al相关的缺陷浓度增多,导致光纤材料在可见光区域吸收损耗增加.Ce离... 详细信息

采用改进型化学气相沉积法结合稀土螯合物掺杂制备了系列掺镱光纤预制棒及光纤,并测试了光纤(预制棒)辐照、退火前后的光学性能.结果表明:中子辐照后掺镱光纤材料中与Al相关的缺陷浓度增多,导致光纤材料在可见光区域吸收损耗增加.Ce离子的掺杂可缓减铝氧空位中心(Al-OHC)等色心缺陷的增加,从而有效抑制掺镱光纤的辐致暗化效应.热退火可降低中子辐致色心缺陷的浓度从而降低光纤材料的吸收,在一定程度上消除暗化效应.

关键词：掺镱光纤辐照光谱热退火

FY3C卫星星载BDS与GPS数据质量分析与融合定轨

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测绘学报 2018年第B12期47卷 9-17页

作者：李文文李敏赵齐乐施闯郭向孟祥广杨忠东武汉大学卫星导航定位技术研究中心湖北武汉430079 地球空间信息技术协同创新中心湖北武汉430079 中国科学院国家空间科学中心北京100190 天基空间环境北京重点实验室北京100029 中国气象局国家卫星气象中心北京100081

本文基于FY3C卫星2015年5月的星载GPS与BDS双频观测数据,开展了FY3C卫星星载BDS与GPS数据融合精密定轨研究。星载GPS和BDS数据质量分析表明,98%以上的历元能观测到4.及以上的GPS卫星,而仅有35%的历元能观测到4.以上的BDS卫星,且星载BD... 详细信息

本文基于FY3C卫星2015年5月的星载GPS与BDS双频观测数据,开展了FY3C卫星星载BDS与GPS数据融合精密定轨研究。星载GPS和BDS数据质量分析表明,98%以上的历元能观测到4.及以上的GPS卫星,而仅有35%的历元能观测到4.以上的BDS卫星,且星载BDS数据的伪距多路径存在随高度角、方位角和频率变化的bias。精密定轨研究表明,基于单独GPS数据精密定轨的重叠弧段三维RMS平均RMS优于20mm,表明其轨道一致性较好,可作为融合精密定轨检核的参考轨道。等权处理GPS和BDS数据时,由于BDSGEO轨道与钟差误差会引起所有卫星观测值模型化误差增加,联合定轨精度仅在80mm量级。禁用BDSGEO观测值或者对其进行降权后,联合定轨的重叠弧段比较均在18mm,与GPS轨道相比的轨道差异均仅在10mm,表明其和单独GPS定轨精度一致。

关键词：低轨卫星精密定轨 BDS GPS 轨道精度

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高分遥感共性产品生成和真实性检验技术体系

遥感学报 2023年第3期27卷 544-562页

作者：柳钦火闻建光周翔赵坚李增元李新马明国王维真廖小罕刘绍民范闻捷肖青仲波李静辛晓洲李丽贾立高志海金家栋梁师邢进廖楚江吴一戎中国科学院空天信息创新研究院遥感科学国家重点实验室北京100101 国家国防科技工业局对地观测与数据中心北京100101 中国林业科学院资源信息研究所北京100191 中国科学院青藏高原研究所国家青藏高原科学数据中心北京100101 西南大学地理科学学院重庆金佛山喀斯特生态系统国家野外科学观测研究站重庆400715 中国科学院西北生态环境资源研究院中国科学院黑河遥感试验研究站兰州730000 中国科学院地理科学与资源研究所北京100101 北京师范大学地理科学学部地表过程与资源生态国家重点实验室北京100875 北京大学遥感与地理信息系统研究所北京100871 中科星图股份有限公司北京101399 航天宏图信息技术股份有限公司北京100195 中国科学院大学资源与环境学院北京100049

随着高分辨率对地观测系统重大专项的成功实施,GF-1—GF-7七型卫星共19种主要载荷发射升空,形成了中国遥感卫星多谱段、多模式的观测能力,可为各种科研和行业遥感应用提供源源不断的高空间、高时间和高光谱分辨率的高质量遥感数据。如... 详细信息

随着高分辨率对地观测系统重大专项的成功实施,GF-1—GF-7七型卫星共19种主要载荷发射升空,形成了中国遥感卫星多谱段、多模式的观测能力,可为各种科研和行业遥感应用提供源源不断的高空间、高时间和高光谱分辨率的高质量遥感数据。如何打通高分卫星遥感数据到信息的转换链,降低高分卫星数据应用门槛、提升高分卫星应用服务成效已成为急需破解的迫切问题。遥感定量产品的误差来源包括传感器成像、几何与辐射定标、数据预处理、定量反演与产品检验等各个环节,提高定量遥感产品精度是一个复杂的系统工程,各行业应用部门和多领域用户难以独立完成全流程数据处理、产品生产和检验。本文在分析高分卫星遥感产品体系的基础上,针对多用户共同需求,梳理了7大类共4.种共性定量遥感产品;从全链条误差溯源和质量检验需要出发,提出了高分遥感共性产品生成和检验的技术体系,分析了算法测评—算法优化—产品生产—真实性检验等环节面临的关键技术;进而提出了高分遥感共性产品真实性检验平台与产品定型分系统的初步设计方案,并介绍了系统研发的最新进展;最后对高分共性产品应用前景进行了展望,构建高分遥感共性产品生成与真实性检验技术体系,对于保障高分卫星遥感共性产品精度和质量、提升高分卫星应用服务效益具有重要的意义。

关键词：高分卫星遥感反演遥感共性产品算法测评像元真值真实性检验

面向天地一体化信息网络的在轨信息处理机制设计

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中国电子科学研究院学报 2020年第6期15卷 580-585页

作者：岳兆娟秦智超李俊时月茹中国科学院计算机网络信息中心北京100190 中国电子科学研究院北京100041 中国科学院大学北京100049

随着组网技术和传输技术的发展,提高信息的在轨处理和多源信息融合能力是提升天地一体化信息网络服务能力急需解决的重点问题。针对目前卫星具有的处理和存储能力,文中研究天基信息业务流程及处理模式,可有效简化传统卫星的通信过程,降... 详细信息

随着组网技术和传输技术的发展,提高信息的在轨处理和多源信息融合能力是提升天地一体化信息网络服务能力急需解决的重点问题。针对目前卫星具有的处理和存储能力,文中研究天基信息业务流程及处理模式,可有效简化传统卫星的通信过程,降低星地传输链路带宽损耗。文中设计一种分布式、网络化天基信息在轨处理系统,该处理系统基于CPU、DSP、GPU等不同的异构资源搭建,通过虚拟化技术将不同轨道、不同类型的卫星资源逻辑上形成一个大的资源池,实现处理系统的灵活扩展、互为备份、协同服务等。

关键词：信息在轨处理天地一体化信息网络分层架构处理模式