Long term in situ atmospheric observation of the landfast ice nearby Zhongshan Station in the Prydz Bay was performed from April to November 2016. The in situ observation, including the conventional meteorological ele...Long term in situ atmospheric observation of the landfast ice nearby Zhongshan Station in the Prydz Bay was performed from April to November 2016. The in situ observation, including the conventional meteorological elements and turbulent flux, enabled this study to evaluate the sea ice surface energy budget process. Using in situ observations, three different reanalysis datasets from the European Centre for Medium-Range Weather Forecasts Interim Re-analysis(ERA-Interim), National Centers for Environmental Prediction Reanalysis2(NCEP R2), and Japanese 55-year Reanalysis(JRA55), and the Los Alamos sea ice model, CICE, output for surface fluxes were evaluated. The observed sensible heat flux(SH) and net longwave radiation showed seasonal variation with increasing temperature. Air temperature rose from the middle of October as the solar elevation angle increased.The ice surface lost more energy by outgoing longwave radiation as temperature increased, while the shortwave radiation showed obvious increases from the middle of October. The oceanic heat flux demonstrated seasonal variation and decreased with time, where the average values were 21 W/m^(2) and 11 W/m^(2), before and after August,respectively. The comparisons with in situ observations show that, SH and LE(latent heat flux) of JRA55 dataset had the smallest bias and mean absolute error(MAE), and those of NCEP R2 data show the largest differences.The ERA-Interim dataset had the highest spatial resolution, but performance was modest with bias and MAE between JRA55 and NCEP R2 compare with in situ observation. The CICE results(SH and LE) were consistent with the observed data but did not demonstrate the amplitude of inner seasonal variation. The comparison revealed better shortwave and longwave radiation stimulation based on the ERA-Interim forcing in CICE than the radiation of ERA-Interim. The average sea ice temperature decreased in June and July and increased after September,which was similar to the temperature measured by buoys, with a bias and MAE of 0.9℃ and 1.0℃, respectively.展开更多
A new method of landslip monitoring in open-pit is presented, in which the monitoring data processing and a variety of deformation curvilinear drawings are carried out by microcomputer system, based on the practice in...A new method of landslip monitoring in open-pit is presented, in which the monitoring data processing and a variety of deformation curvilinear drawings are carried out by microcomputer system, based on the practice in Haizhou Open-Mine for many years. Meanwhile, the general regularity on landslip in open-pit is acquired.展开更多
The task of climate observation data processing is central to the quality of an assessment of future climate change impact. The current state-of-the-art is based on the long-running observation records of the meteorol...The task of climate observation data processing is central to the quality of an assessment of future climate change impact. The current state-of-the-art is based on the long-running observation records of the meteorological stations. However, it is common for the developing states to have only relatively short and/or intermittent record histories. The issue becomes even more aggravated under an effort to assess the climatic trends for specific territories with few meteorological stations. The paper offers a simple and effective technique to handle the climate observations; the technique makes the most complete use of an available data set by counting the data provided by all meteorological stations including those with short records and omissions. The method is based on numeric differentiation of source data samples.展开更多
DATA AND COMPUTILITY ISLANDS IN REMOTE SENSING FOR EO The rapid advancement of Earth observation(EO)capabilities is driving an explosive increase in remote sensing data.There is an urgent need for advanced processing ...DATA AND COMPUTILITY ISLANDS IN REMOTE SENSING FOR EO The rapid advancement of Earth observation(EO)capabilities is driving an explosive increase in remote sensing data.There is an urgent need for advanced processing techniques to unleash their application value.1 Generalist EO intelligence refers to the ability to provide unified support for qualitative interpretation,quantitative inversion,and interactive dialogue across diverse EO data and tasks.It has attracted significant attention recently,prompting academia,industry,and government to invest substantial resources.2 Through developing remote sensing foundation models(RSFMs),generalist EO intelligence can ultimately offer humanity a shared spatial-temporal intelligence service in various fields(e.g.,agriculture,forestry,and oceanography).3 However,a critical question remains:have we truly unleashed the potential of RSFMs for generalist EO intelligence?Despite the vast volume of remote sensing data,their distribution is often fragmented and decentralized due to privacy concerns,storage bottlenecks,industrial competition,and geo-information security.This fragmentation leads to data islands,which limit the full utilization of multi-source remote sensing data.Moreover,computility(i.e.,computational resources)typically develops in isolation,inadequately supporting the large-scale training and application of RSFMs.展开更多
为实现对无线网络异常数据流的快速辨识,文章基于弱监督学习,设计了一种新的智能辨识方法。基于网络节点连接强度,构建计算机无线网络多状态观测矩阵;引进弱监督学习领域的弱监督数据增强主动学习(Weakly Supervised Data Augmentation ...为实现对无线网络异常数据流的快速辨识,文章基于弱监督学习,设计了一种新的智能辨识方法。基于网络节点连接强度,构建计算机无线网络多状态观测矩阵;引进弱监督学习领域的弱监督数据增强主动学习(Weakly Supervised Data Augmentation Active Learning,WIDS-APL)模型,通过将转换样本映射到超球体空间中进行弱监督学习,实现对观测矩阵中数据的表征处理;将不同状态的数据导入改进后的长短期记忆人工神经网络模型,实现对异常数据流进行检测与辨识。实验表明,该方法不仅可以提高零日威胁响应时效,还能在优化辨识方法吞吐量的基础上,实现对数据流异常幅值的判定。展开更多
We propose the design of an observation station to establish a reliable datum for displacement and deformation analysis at the first working-face subsidence observation station of Liuzhuang Mine. The design considers ...We propose the design of an observation station to establish a reliable datum for displacement and deformation analysis at the first working-face subsidence observation station of Liuzhuang Mine. The design considers various geologic and mining con-ditions. Having analyzed the aims of the joint survey and the comprehensive survey, we propose design principles, and work modes, for adopting GPS technology as the position measuring technique to be used in these two stages. Baseline vectors and spatial ad-justments of the GPS network were calculated after study of data processing and quality estimation methods. A coordinate system transformation and error estimates of the transformed GPS network data are discussed. The error estimates in all stages show that the GPS control network of the observation station has sufficient accuracy and is highly efficient. The network thus provides a reli-able datum for analyzing the laws of surface displacement and deformation induced by mining.展开更多
In the neutral hydrogen(H I)galaxy survey,a significant challenge is to identify and extract the H I galaxy signal from the observational data contaminated by radio frequency interference(RFI).For a drift-scan survey,...In the neutral hydrogen(H I)galaxy survey,a significant challenge is to identify and extract the H I galaxy signal from the observational data contaminated by radio frequency interference(RFI).For a drift-scan survey,or more generally a survey of a spatially continuous region,in the time-ordered spectral data,the H I galaxies and RFI all appear as regions that extend an area in the time-frequency waterfall plot,so the extraction of the H I galaxies and RFI from such data can be regarded as an image segmentation problem,and machine-learning methods can be applied to solve such problems.In this study,we develop a method to effectively detect and extract signals of H I galaxies based on a Mask R-CNN network combined with the PointRend method.By simulating FAST-observed galaxy signals and potential RFI impact,we created a realistic data set for the training and testing of our neural network.We compared five different architectures and selected the best-performing one.This architecture successfully performs instance segmentation of H I galaxy signals in the RFI-contaminated time-ordered data,achieving a precision of 98.64%and a recall of 93.59%.展开更多
基金The National Key R&D Program of China under contract No. 2018YFA0605903the National Natural Science Foundation of China under contract Nos 41941009, 41922044 and 41876212the Guangdong Basic and Applied Basic Research Foundation under contract No. 2020B1515020025。
文摘Long term in situ atmospheric observation of the landfast ice nearby Zhongshan Station in the Prydz Bay was performed from April to November 2016. The in situ observation, including the conventional meteorological elements and turbulent flux, enabled this study to evaluate the sea ice surface energy budget process. Using in situ observations, three different reanalysis datasets from the European Centre for Medium-Range Weather Forecasts Interim Re-analysis(ERA-Interim), National Centers for Environmental Prediction Reanalysis2(NCEP R2), and Japanese 55-year Reanalysis(JRA55), and the Los Alamos sea ice model, CICE, output for surface fluxes were evaluated. The observed sensible heat flux(SH) and net longwave radiation showed seasonal variation with increasing temperature. Air temperature rose from the middle of October as the solar elevation angle increased.The ice surface lost more energy by outgoing longwave radiation as temperature increased, while the shortwave radiation showed obvious increases from the middle of October. The oceanic heat flux demonstrated seasonal variation and decreased with time, where the average values were 21 W/m^(2) and 11 W/m^(2), before and after August,respectively. The comparisons with in situ observations show that, SH and LE(latent heat flux) of JRA55 dataset had the smallest bias and mean absolute error(MAE), and those of NCEP R2 data show the largest differences.The ERA-Interim dataset had the highest spatial resolution, but performance was modest with bias and MAE between JRA55 and NCEP R2 compare with in situ observation. The CICE results(SH and LE) were consistent with the observed data but did not demonstrate the amplitude of inner seasonal variation. The comparison revealed better shortwave and longwave radiation stimulation based on the ERA-Interim forcing in CICE than the radiation of ERA-Interim. The average sea ice temperature decreased in June and July and increased after September,which was similar to the temperature measured by buoys, with a bias and MAE of 0.9℃ and 1.0℃, respectively.
文摘A new method of landslip monitoring in open-pit is presented, in which the monitoring data processing and a variety of deformation curvilinear drawings are carried out by microcomputer system, based on the practice in Haizhou Open-Mine for many years. Meanwhile, the general regularity on landslip in open-pit is acquired.
文摘The task of climate observation data processing is central to the quality of an assessment of future climate change impact. The current state-of-the-art is based on the long-running observation records of the meteorological stations. However, it is common for the developing states to have only relatively short and/or intermittent record histories. The issue becomes even more aggravated under an effort to assess the climatic trends for specific territories with few meteorological stations. The paper offers a simple and effective technique to handle the climate observations; the technique makes the most complete use of an available data set by counting the data provided by all meteorological stations including those with short records and omissions. The method is based on numeric differentiation of source data samples.
基金supported by the National Natural Science Foundation of China under grants 42030102 and 42371321 and by the Ant Group。
文摘DATA AND COMPUTILITY ISLANDS IN REMOTE SENSING FOR EO The rapid advancement of Earth observation(EO)capabilities is driving an explosive increase in remote sensing data.There is an urgent need for advanced processing techniques to unleash their application value.1 Generalist EO intelligence refers to the ability to provide unified support for qualitative interpretation,quantitative inversion,and interactive dialogue across diverse EO data and tasks.It has attracted significant attention recently,prompting academia,industry,and government to invest substantial resources.2 Through developing remote sensing foundation models(RSFMs),generalist EO intelligence can ultimately offer humanity a shared spatial-temporal intelligence service in various fields(e.g.,agriculture,forestry,and oceanography).3 However,a critical question remains:have we truly unleashed the potential of RSFMs for generalist EO intelligence?Despite the vast volume of remote sensing data,their distribution is often fragmented and decentralized due to privacy concerns,storage bottlenecks,industrial competition,and geo-information security.This fragmentation leads to data islands,which limit the full utilization of multi-source remote sensing data.Moreover,computility(i.e.,computational resources)typically develops in isolation,inadequately supporting the large-scale training and application of RSFMs.
文摘为实现对无线网络异常数据流的快速辨识,文章基于弱监督学习,设计了一种新的智能辨识方法。基于网络节点连接强度,构建计算机无线网络多状态观测矩阵;引进弱监督学习领域的弱监督数据增强主动学习(Weakly Supervised Data Augmentation Active Learning,WIDS-APL)模型,通过将转换样本映射到超球体空间中进行弱监督学习,实现对观测矩阵中数据的表征处理;将不同状态的数据导入改进后的长短期记忆人工神经网络模型,实现对异常数据流进行检测与辨识。实验表明,该方法不仅可以提高零日威胁响应时效,还能在优化辨识方法吞吐量的基础上,实现对数据流异常幅值的判定。
文摘We propose the design of an observation station to establish a reliable datum for displacement and deformation analysis at the first working-face subsidence observation station of Liuzhuang Mine. The design considers various geologic and mining con-ditions. Having analyzed the aims of the joint survey and the comprehensive survey, we propose design principles, and work modes, for adopting GPS technology as the position measuring technique to be used in these two stages. Baseline vectors and spatial ad-justments of the GPS network were calculated after study of data processing and quality estimation methods. A coordinate system transformation and error estimates of the transformed GPS network data are discussed. The error estimates in all stages show that the GPS control network of the observation station has sufficient accuracy and is highly efficient. The network thus provides a reli-able datum for analyzing the laws of surface displacement and deformation induced by mining.
基金support by the National SKA Program of ChinaNo.2022SKA0110100+1 种基金the CAS Interdisciplinary Innovation Team(JCTD-2019-05)the science research grants from the China Manned Space Project with No.CMS-CSST-2021-B01。
文摘In the neutral hydrogen(H I)galaxy survey,a significant challenge is to identify and extract the H I galaxy signal from the observational data contaminated by radio frequency interference(RFI).For a drift-scan survey,or more generally a survey of a spatially continuous region,in the time-ordered spectral data,the H I galaxies and RFI all appear as regions that extend an area in the time-frequency waterfall plot,so the extraction of the H I galaxies and RFI from such data can be regarded as an image segmentation problem,and machine-learning methods can be applied to solve such problems.In this study,we develop a method to effectively detect and extract signals of H I galaxies based on a Mask R-CNN network combined with the PointRend method.By simulating FAST-observed galaxy signals and potential RFI impact,we created a realistic data set for the training and testing of our neural network.We compared five different architectures and selected the best-performing one.This architecture successfully performs instance segmentation of H I galaxy signals in the RFI-contaminated time-ordered data,achieving a precision of 98.64%and a recall of 93.59%.
