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Towards seamless environmental prediction-development of Pan-Eurasian EXperiment(PEEX)modelling platform

Big Earth Data 2024年第2期8卷 189-230页

作者： Alexander Mahura Alexander Baklanov Risto Makkonen Michael Boy Tuukka Petäjä Hanna KLappalainen Roman Nuterman Veli-Matti Kerminen Stephen R.Arnold Markus Jochum Anatoly Shvidenko Igor Esau Mikhail Sofiev Andreas Stohl Tuula Aalto Jianhui Bai Chuchu Chen Yafang Cheng Oxana Drofa Mei Huang Leena Järvi Harri Kokkola Rostislav Kouznetsov Tingting Li Piero Malguzzi Sarah Monks Mads Bruun Poulsen Steffen M.Noe Yuliia Palamarchuk Benjamin Foreback Petri Clusiu Till Andreas Soya Rasmussen Jun She Jens Havskov Sørensen Dominick Spracklen Hang Su Juha Tonttila Siwen Wang Jiandong Wang Tobias Wolf-Grosse Yongqiang Yu Qing Zhang Wei Zhang Wen Zhang Xunhua Zheng Siqi Li Yong Li Putian Zhou Markku Kulmala Faculty of Science Institute for Atmospheric and Earth System Research(INAR)/PhysicsUniversity of Helsinki(UHEL)HelsinkiFinland Science and Innovation Department World Meteorological Organization(WMO)GenevaSwitzerland Niels Bohr institute University of CopenhagenCopenhagenDenmark Climate system Research Finnish Meteorological Institute(CSR-FMI)HelsinkiFinland School of Engineering Sciences Lappeenranta University of TechnologyLappeenrantaFinland institute for Climate and Atmospheric Science School of Earth and EnvironmentUniversity of LeedsLeedsUK Biodiversity and Natural Resources Program International Institute for Applied Systems Analysis(IIASA)LaxenburgAustria Department of Physics and Technology UiT-The Arctic University of NorwayTromsoNorway Nansen Environmental and remote {1. Center(NERSC) BergenNorway Atmospheric Composition Finnish Meteorological Institute(AC-FMI)HelsinkiFinland Norwegian institute for Air Research(NILU) KjellerNorway LAGEO Institute of Atmospheric PhysicsChinese Academy of Sciences(IAP-CAS)BeijingChina Max Planck institute for Chemistry(MPI-Chem) MainzGermany institute of Atmospheric Sciences and Climate National Research Council of Italy(CNR-15SAC)BolognaItaly institute of Geographic Sciences and Natural Resources Research(IGSNRR) Chinese Academy of Sciences(CAS)BeijingChina Faculty of Science Helsinki Institute of Sustainability Science(HELSUS)University of Helsinki(UHEL)HelsinkiFinland Atmospheric Research Centre of Eastern Finland Finnish Meteorological Institute(ARCEF-FMI)KuopioFinland institute of Atmospheric Physics Chinese Academy of Sciences(IAP-CAS)BeijingChina Department of Plant Physiology Estonian University of Life Sciences(EULS)Institute of Agricultural and Environmental Sciences(IAES)TartuEstonia Danish Meteorological institute(DMI) CopenhagenDenmark State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry LAPC) Institute of Atmospheric Physics(IAP)Chinese Academy of Sciences(CAS)BeijingChina Uni

The Pan-Eurasian Experiment Modelling Platform(PEEX-MP)is one of the key blocks of the PEEX Research *** PEEX MP has more than 30 models and is directed towards seamless envir-onmental *** main focus area is the Arctic-boreal regions and *** models used in PEEX-MP cover several main components of the Earth’s system,such as the atmosphere,hydrosphere,pedosphere and biosphere,and resolve the physicalchemicalbiological processes at different spatial and temporal scales and *** paper introduces and discusses PEEX MP multi-scale modelling concept for the Earth system,online integrated,forward/inverse,and socioeconomical modelling,and other approaches with a particular focus on applications in the PEEX geographical *** employed high-performance com-puting facilities,capabilities,and PEEX dataflow for modelling results are *** virtual research platforms(PEEXView,Virtual Research Environment,Web-based Atlas)for handling PEEX modelling and observational results are *** over-all approach allows us to understand better physical-chemicalbiological processes,Earth’s system interactions and feedbacks and to provide valuable information for assessment studies on evaluating risks,impact,consequences,*** population,envir-onment and climate in the PEEX *** work was also one of the last projects of *** Zilitinkevich,who passed away on 1. February *** the finalization took time,the paper was actually submitted in 2023 and we could not argue that the final paper text was agreed with him.

关键词： Multi-scale and-processes modelling concept seamless coupling high-performance computing data infrastructure virtual research platforms

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GPU ray casting method for visualizing 3D pipelines in a virtual globe

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International Journal of Digital Earth 2019年第4期12卷 428-441页

作者： Zhaocong Wu Nan Wang Jie Shao Guohui Deng School of remote {1. and information Engineering Wuhan UniversityWuhanPeople’s Republic of China State Key Laboratory of remote {1. Science Institute of Remote Sensing Science and EngineeringFaculty of Geographical ScienceBeijing Normal UniversityBeijingPeople’s Republic of China

Pipelines are an important part of urban infrastructure *** part of a virtual globe(VG),the high-efficiency and high-quality visualization of 3D large-scale and high-density urban pipelines is of great *** paper proposes a GPU-based pipeline ray casting method for the visualization of urban-scale pipelines in the framework of a *** method involves the initial partitioning of the pipeline data into tiles,based on the relationship between the pipeline layer scale and the discrete global grid system(DGGSs).The pipeline centerline in each tile is then segmented and encoded,and a coarser pipeline bounding volume is subsequently constructed using a geometry ***,the fine 3D pipeline is rendered using a pixel *** results of the experimental implementation of the proposed method show that it satisfies the requirements for the multiscale visualization of pipelines in a ***,compared with the traditional polygon-based method,the method facilitates a 20%increase in rendering frame rate for the same pixel level accuracy display *** also enables the visualization of the thickness of the 3D pipeline without any obvious effect on the rendering efficiency。

关键词： Virtual globe multiscale visualization ray casting method massive pipeline 3D visualization

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Multi-year monitoring of paddy rice planting area in Northeast China using MODIS time series data

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2013年第10期14卷 934-946页

作者： Jing-jing SHI Jing-feng HUANG Feng ZHANG institute of Agricultural {1. sensing and information Application Zhejiang University Key Laboratory of Agricultural remote {1. and information system of Zhejiang Province Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health Zhejiang University

e The objective of this study was to investigate the tempo-spatial distribution of paddy rice in Northeast China using moderate resolution imaging spectroradiometer （MODIS） data. We developed an algorithm for detection and estimation of the transplanting and flooding periods of paddy rice with a combination of enhanced vegetation index （EVI） and land surface water index with a central wavelength at 21.0 nm （LSW1.1.0）. In two intensive sites in Northeast China, fine resolution satellite imagery was used to validate the performance of the algorithm at pixel and 3x3 pixel window levels, respectively. The commission and omission errors in both of the intensive sites were approximately less than 20%. Based on the algorithm, annual distribution of paddy rice in Northeast China from 2001.to 2009 was mapped and analyzed. The results demonstrated that the MODIS-derived area was highly correlated with published agricultural statistical data with a coefficient of determination （R^2） value of 0.847. It also revealed a sharp decline in 2003, especially in the Sanjiang Plain located in the northeast of Heilongjiang Province, due to the oversupply and price decline of rice in 2002. These results suggest that the approaches are available for accurate and reliable monitoring of rice cultivated areas and variation on a large scale.

关键词： Paddy rice Moderate resolution imaging spectroradiometer(MODIS) Northeast China Enhanced vegetation index Land surface water index

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A New Approach to Simulate Positional Error of Line Segment in GIS

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Geo-Spatial information Science 2006年第2期9卷 142-146页

作者： ZHANG Lei DENG Min CHEN Xiaoyong Department of remote {1. and Geographic information system Asian Institute of Technology Bangkok 12120 Thailand

To determine the distribution of positional error of a line segment, Monte Carlo approach is applied to simulate the probability density function of a line segment with the assumption that the error of endpoints in a line segment follows a two-dimensional normal distribution. For such purpose, a stochastic generator used for uncertain endpoints with the two-dimensional normal distribution is presented. This forms the basis of the generation of random line segment for the simulation of the error model of a whole line segment. The error models cover the cases where two endpoints are either independent or dependent to each other, also including a special case that the distance between two random endpoints in a line segment is close enough.

关键词： positional error Monte Carlo simulation line segment stochastic point generator

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Research of Software Complexity Metrics with Security Indicator

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Journal of Donghua University(English Edition) 2011年第5期28卷 460-464页

作者：付剑晶王珂 institute of {1. sensing and information system Zhejiang University School of information Technology Zhejiang University of Finances and Economics

Software protection technology has been universally emphasized, with the development of reverse engineering and static analysis techniques. So, it is important to research how to quantitatively evaluate the security of the protected software. However, there are some researchers evaluating the security of the proposed protect techniques directly by the traditional complexity metrics, which is not suffident. In order to better reflect security from software complexity, a multi-factor complexity metric based on control flow graph （CFG） is proposed, and the corresponding calculating procedures are presented in detail. Moreover, complexity density models are constructed to indicate the strength of software resisting reverse engineering and code analysis. Instance analysis shows that the proposed method is simple and practical, and can more objectively reflect software security from the perspective of the complexity.

关键词： complexity metric software protection complexity density control flow graph

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Loose architecture of multi-level massive geospatial data based on virtual quadtree

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Science China(Technological Sciences) 2008年第S1期51卷 114-123页

作者： YANG ChongJun,WU Sheng,REN YingChao,FU Li,ZHANG FuQing,WANG Gang,TAN Jian,LIU DongLin,MA ChaoJi & LIANG Li State Key Laboratory of remote {1. Science,Jointly Sponsored by the institute of remote {1. Applications of Chinese Academy of Sciences and Beijing Normal University,Beijing 1.01.1.China 1. State Key Laboratory of remote {1. Science Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China

This paper proposed a virtual quadtree (VQT) based loose architecture of multi-level massive geospatial data for integrating massive geospatial data dispersed in the departments of different hierarchies in the same sector into a unified GIS (Geographic information {1.) platform. By virtualizing the nodes of the quad-tree,the VQT separates the structure of data organization from data storage,and screens the difference between the data storage in local computer and in the re-mote computers in network environment. And by mounting,VQT easily integrates the data from the remote computers into the local VQT so as to implement seam-less integration of distributed multi-level massive geospatial data. Based on that mode,the paper built an application {1. with geospatial data over 1.00 GB distributed in 1. servers deployed in 1. cities. The experiment showed that all data can be seamlessly rapidly traveled and performed zooming in and zooming out smoothly.

关键词： massive geospatial data virtual quadtree loose architecture

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Estimation of vegetation biophysical parameters by remote {1. using radial basis function neural network

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2007年第6期8卷 883-895页

作者： YANG Xiao-hua HUANG Jing-feng WANG Jian-wen WANG Xiu-zhen LIU Zhan-yu institute of Agricultural {1. sensing ＆ information Application Zhejiang University Hangzhou 310029 China Key Laboratory of Agricultural remote {1. ＆ information system Hangzhou 310029 China Communication Training Base of General Staff Headquarters Beijing 102400 China Zhejiang Meteorological institute Hangzhou 310004 China

Hyperspectral reflectance (350~2500 nm) data were recorded at two different sites of rice in two experiment fields including two cultivars, and three levels of nitrogen (N) application. Twenty-five Vegetation Indices (VIs) were used to predict the rice agronomic parameters including Leaf Area Index (LAI, m2 green leaf/m2 soil) and Green Leaf Chlorophyll Density (GLCD, mg chlorophyll/m2 soil) by the traditional regression models and Radial Basis Function Neural Network (RBF). RBF emerged as a variant of Artificial Neural Networks (ANNs) in the late 1.80’s. A large variety of training algorithms has been tested for training RBF networks. In this study, Original RBF (ORBF), Gradient Descent RBF (GDRBF), and Generalized Regression Neural Network (GRNN) were employed. Results showed that green waveband Normalized Difference Vegetation Index (NDVIgreen) and TCARI/OSAVI have the best prediction power for LAI by exponent model and ORBF respectively, and that TCARI/OSAVI has the best prediction power for GLCD by exponent model and GDRBF. The best performances of RBF are compared with the traditional models, showing that the relationship between VIs and agronomic variables are further improved when RBF is used. Compared with the best traditional models, ORBF using TCARI/OSAVI improves the prediction power for LAI by lowering the Root Mean Square Error (RMSE) for 0.1.1., and GDRBF using TCARI/OSAVI improves the prediction power for GLCD by lowering the RMSE for 26.7853. It is concluded that RBF provides a useful exploratory and predictive tool when applied to the sensitive VIs.

关键词： Artificial neural network (ANN) Radial basis function (RBF) remote {1. Rice Vegetation index (VI)

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Detecting Agro-Droughts in Southwest of China Using MODIS Satellite Data

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Journal of Integrative Agriculture 2013年第1期12卷 159-168页

作者： ZHANG Feng ZHANG Li-wen WANG Xiu-zhen HUNG Jing-feng institute of Agricultural {1. sensing & information Application Zhejiang University Key Laboratory of Environmental Remediation and Ecological Health Ministry of Education/College of Natural Resources and Environmental Science Zhejiang University institute of {1. sensing and Earth Sciences Hangzhou Normal University The Provinical Key Laboratories of Agricultural remote {1. and information system Zhejiang Province

The normalized difference vegetation index （NDVI） has proven to be typically employed to assess terrestrial vegetation conditions. However, one limitation of NDVI for drought monitoring is the apparent time lag between rainfall deficit and NDVI response. To better understand this relationship, time series NDVI （2000-201.） during the growing season in Sichuan Province and Chongqing City were analyzed. The vegetation condition index （VCI） was used to construct a new drought index, time-integrated vegetation condition index （TIVCI）, and was then compared with meteorological drought indices-standardized precipitation index （SPI）, a multiple-time scale meteorological-drought index based on precipitation, to examine the sensitivity on droughts. Our research findings indicate the followings：（1. farmland NDVI sensitivity to precipitation in study area has a time lag of 1.-24 d, and it maximally responds to the temperature with a lag of about 1. d. （2） We applied the approach to Sichuan Province and Chongqing City for extreme drought monitoring in 2006 and 2003, and the results show that the monitoring results from TIVCI are closer to the published China agricultural statistical data than VCI. Compared to VCI, the best results from TIVCI3 were found with the relative errors of -4.5 and 6.36% in 2006 for drought affected area and drought disaster area respectively, and 5.1. and -5.95% in 2003. （3） Compared to VCI, TIVCI has better correlation with the SPI, which indicates the lag and cumulative effects of precipitation on vegetation. Our finding proved that TIVCI is an effective indicator of drought detection when the time lag effects between NDVI and climate factors are taken into consideration.

关键词： time-integrated vegetation condition index (TIVCI) time lag normalized difference vegetation index (NDVI) drought monitor standardized precipitation index (SPI)

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Assessing the Response of Seasonal Variation of Net Primary Productivity to Climate Using remote {1. Data and Geographic information system Techniques in Xinjiang

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Journal of Integrative Plant Biology 2008年第12期50卷 1580-1588页

作者： Dai-Liang Peng Jing-Feng Huang Cheng-Xia Cai Rui Deng Jun-Feng Xu institute of Agriculture {1. sensing and information system Application Zhejiang University Hangzhou 310029 China Xinjiang institute of Meteorology Urumchi 830002 China

Net primary productivity （NPP） is a key component of energy and matter transformation in the terrestrial ecosystem, and the responses of NPP to global change locally and regionally have been one of the most important aspects in climatevegetation relationship studies. In order to isolate causal climatic factors, it is very important to assess the response of seasonal variation of NPP to climate. In this paper, NPP in Xinjiang was estimated by NOAA/AVHRR Normalized Difference Vegetation Index （NDVI） data and geographic {1. system （GIS） techniques. The impact of climatic factors （air temperature, precipitation and sunshine percentage） on seasonal variations of NPP was studied by time lag and serial correlation ageing analysis. The results showed that the NPP for different land cover types have a similar correlation with any one of the three climatic factors, and precipitation is the major climatic factor influencing the seasonal variation of NPP in Xinjiang. It was found that the positive correlation at 0lag appeared between NPP and precipitation and the serial correlation ageing was 0 d in most areas of Xinjiang, which indicated that the response of NPP to precipitation was immediate. However, NPP of different land cover types showed significant positive correlation at 2 month lag with air temperature, and the impact of which could persist 1.month as a whole. No correlation was found between NPP and sunshine percentage.

关键词： climate geographic information {1. techniques net primary productivity remote {1. seasonal variation serial correlation ageing time lag.

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GIS-Based Risk Assessment and Regionalization of Drought Hazards in China

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Journal of Donghua University(English Edition) 2012年第6期29卷 455-460页

作者：张峰黄敬峰张丽文王秀珍 institute of Agricultural {1. sensing & information Application Zhejiang University Key Laboratory of Agricultural remote {1. and information system Zhejiang University Key Laboratory of Environmental Remediation and Ecological Health Ministry of EducationZhejiang University institute of {1. sensing and Earth Sciences Hangzhou Normal University

Based on the monthly precipitation (1.60-2009) of China and associated regional socio-economic data, the spatial and temporal pattern of drought in China was assessed by applying a conceptual framework of disaster system theory, which used the hazard and vulnerability as two variables to define the risk of drought. Sichuan province suffered from the severe risk of drought, while Guangxi, Yunnan, Guizhou provinces, and Chongqing city could be classified as the moderate drought risk area of China. Additionally, Tibet plateau in the Northwest of China had the lowest risk of drought. The integrated data from this result provided the valuable {1. to cope with the drought in respect of optimization utilization of land resources at the regional scale.

关键词： drought hazard vulnerability risk geographical {1. system(GIS) China

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