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SSRN 2025年

作者： Peng, Siyuan Yang, Yue Luo, Dengnan Zeng, Xiang Liang, Minqi Tao, Long Zhang, Guangru Li, Pan Liao, Weijie Guo, Qun Cao, Ruochen Li, Yuzhe Zhang, Weirong Hu, Zhongmin Hainan Baoting Tropical Rainforest Ecosystem Observation and Research Station School of Ecology Hainan University Haikou570228 China Department of Geography Faculty of Arts and Sciences Beijing Normal University Zhuhai519087 China Facility of Geographical Science Beijing Normal University Beijing100875 China Zhuhai Branch of State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Zhuhai519087 China School of Geography South China Normal University Shipai Campus Guangzhou510631 China School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Guangdong Zhuhai510245 China Key Lab of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing101408 China International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu210023 China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu210023 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

Study region: The Tibetan Plateau in China, the Third Pole of the *** focus: Accurate descriptions of spatial variation in evapotranspiration (ET) and its components on the Tibetan Plateau (TP) are crucial for understanding the dynamics of the regional water cycle and energy balance. However, how various environmental factors affect ET and its components remains unclear. This study addresses this gap using observational data from 14 sites and employing the Shuttleworth-Wallace-Hu (SWH) model to examine the spatial relationships between ET, its components, and underlying *** hydrological insights for the region: The SWH model parameters were optimized using the Monte Carlo method, achieving a satisfactory model performance with an average R² of 0.75. The ratio of transpiration to ET was generally higher in alpine meadows (0.55) than alpine steppes (0.39). Across the TP, precipitation and the leaf area index together shaped spatial variation in ET and transpiration. Precipitation emerged as the primary driver of interannual variation in ET, while the leaf area index strongly regulated the proportion of ET accounted for by transpiration. Furthermore, above aridity index values of 0.73, grassland ecosystems transitioned from water to energy. This finding is significant as it challenges the common application of an aridity index value of 0.65 to distinguish arid from humid regions. It suggests that TP grasslands, with an AI of 0.65-0.73, remain primarily water-limited. © 2025, The Authors. All rights reserved.

关键词： Monte Carlo methods

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Climatic and Biotic Controls of Evapotranspiration Across Grassland Ecosystems on Tibetan Plateau

SSRN

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SSRN 2023年

作者： Peng, Siyuan Yang, Yue Luo, Dengnan Zeng, Xiang Liang, Minqi Tao, Long Zhang, Guangru Li, Pan Liao, Weijie Guo, Qun Cao, Ruochen Li, Yuzhe Zhang, Weirong Hu, Zhongmin School of Geography South China Normal University Shipai Campus Guangzhou510631 China Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation School of Ecology and Environment Hainan University Haikou570228 China Center for Eco-Environment Restoration Engineering of Hainan Province Hainan University Haikou570228 China Facility of Geographical Science Beijing Normal University Beijing100875 China Zhuhai Branch of State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Zhuhai519087 China School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Guangdong Zhuhai510245 China Key Lab of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing101408 China International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu210023 China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu210023 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

Accurately quantifying spatiotemporal variations in evapotranspiration (ET) and its components on Tibetan Plateau (TP) is crucial for understanding the regional water cycle and energy balance. However, the determinant of spatial variations in ET and its component processes in grassland ecosystems of TP remain unclear. In this study, we used 14 sites observation data and applied Shuttleworth-Wallace-Hu (SWH) model to investigate the spatial relationships between ET, its components, and influencing factors. Our results highlighted the good performance of SWH model. There were corresponding drops in ET on alpine meadow and on alpine steppe. And the ratio of ET and precipitation (ET/PPT) of most sites was less than 1 in alpine meadow. Furthermore, the ratio of transpiration (T) and ET (T/ET) in alpine meadow generally exceeded that in alpine steppe. PPT emerged as the primary driver of interannual spatial variations in ET, while LAI played a crucial role in regulating T/ET. Our results further demonstrated that in the grassland ecosystem of TP, as the aridity index increased, the ET gradually transitioned from being primarily influenced by water supply to energy demand. This transition occurred at an aridity index of 0.73 approximately. The results of this study imply that in the context of global warming, with aridity index in TP decreasing, the ET of more ecosystems will shift from energy-led to water-led. Such findings are of immense significance in enhancing our understanding of the intricate interactions of the water cycle between land and the atmosphere. © 2023, The Authors. All rights reserved.

关键词： Water supply

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Coupled Chemical Reactions: Effects of Electric Field, Diffusion and Boundary Control

arXiv

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arXiv 2023年

作者： Xu, Shixin Eisenberg, Robert Song, Zilong Huang, Huaxiong Zu Chongzhi Center for Mathematics and Computational Sciences Duke Kunshan University 8 Duke Ave Jiangsu Kunshan China Department of Applied Mathematics Illinois Institute of Technology ChicagoIL60616 United States Department of Physiology and Biophysics Rush University Chicago IL60612 United States Math and Statistics Department Utah State University Old Main Hill Logan UT84322 United States Research Center for Mathematics Advanced Institute of Natural Sciences Beijing Normal University Guangdong Zhuhai519088 China Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNU-HKBU United International College Guangdong Zhuhai519088 China Laboratory of Mathematics and Complex Systems MOE Beijing Normal University Beijing100875 China Department of Mathematics and Statistics York University TorontoONM3J 1P3 Canada

MSC Codes 92E20, 92B05, 35Q92Chemical reactions involve the movement of charges, and this work presents a mathematical model for describing chemical reactions in electrolytes. The model is developed using an energy variational method that aligns with classical thermodynamics principles. It encompasses both electrostatics and chemical reactions within consistently defined energetic and dissipative functionals. Furthermore, the energy variation method is extended to account for open systems that involve the input and output of charge and mass. Such open systems have the capability to convert one form of input energy into another form of output energy. In particular, a two-domain model is developed to study a reaction system with self-regulation and internal switching, which plays a vital role in the electron transport chain of mitochondria responsible for ATP generation-a crucial process for sustaining life. Simulations are conducted to explore the influence of electric potential on reaction rates and switching dynamics within the two-domain system. It shows that the electric potential inhibits the oxidation reaction while accelerating the reduction reaction. © 2023, CC BY.

关键词： Open systems

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Multidomain Model for Optic Nerve Potassium Clearance: Roles of Glial Cells and Perivascular Spaces

arXiv

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arXiv 2024年

作者： Xiao, Shanfeng Huang, Huaxiong Eisenberg, Robert Song, Zilong Xu, Shixin School of Mathematical Sciences Soochow University 1 Shi-Zi Street Jiangsu Province Suzhou215006 China Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNU-HKBU United International College Zhuhai519088 China Laboratory of Mathematics and Complex Systems MOE Beijing China Normal University Beijing100875 China Department of Mathematics and Statistics York University TorontoONM3J 1P3 Canada Department of Applied Mathematics Illinois Institute of Technology ChicagoIL60616 United States Math and Statistics Department Utah State University Old Main Hill LoganUT84322 United States Zu Chongzhi Center for Mathematics and Computational Sciences Duke Kunshan University 8 Duke Ave Kunshan China

The accumulation of potassium in the extracellular space surrounding nerve cells is a fundamental aspect of biophysics that has garnered significant attention in recent research. This phenomenon holds implications for various neurological conditions, including spreading depression, migraine, certain types of epilepsy, and potentially, learning processes. A quantitative analysis is essential for understanding the dynamics of potassium clearance following a series of action potentials. This clearance process involves multiple structures along the nerve, including glia, the extracellular space, axons, and the perivascular space, necessitating a spatially distributed systems approach akin to the cable equations of nerve physiology. In this study, we propose a multi-domain model for the optic nerve to investigate potassium accumulation and clearance dynamics. The model accounts for the convection, diffusion, and electrical migration of fluid and ions, revealing the significant roles of glia and the perivascular space in potassium buffering. Specifically, our findings suggest that potassium clearance primarily occurs through convective flow within the syncytia of glia, driven by osmotic pressure differences. Additionally, the perivascular space serves as a crucial pathway for potassium buffering and fluid circulation, further contributing to the overall clearance process. Importantly, our model’s adaptability allows for its application to diverse structures with distinct channel and transporter distributions across the six compartments, extending its utility beyond the optic nerve. © 2024, CC BY-SA.

关键词： Neurons

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Heavy metals prediction in coastal marine sediments using hybridized machine learning models with metaheuristic optimization algorithm

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Chemosphere 2024年 352卷 141329页

作者： Yaseen, Zaher Mundher Melini Wan Mohtar, Wan Hanna Homod, Raad Z. Alawi, Omer A. Abba, Sani I. Oudah, Atheer Y. Togun, Hussein Goliatt, Leonardo Ul Hassan Kazmi, Syed Shabi Tao, Hai Civil and Environmental Engineering Department King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia Interdisciplinary Research Center for Membranes and Water Security King Fahd University of Petroleum & Minerals (KFUPM) Dhahran Saudi Arabia Department of Civil Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia UKM Selangor Bangi 43600 Malaysia Environmental Management Centre Institute of Climate Change Universiti Kebangsaan Malaysia Selangor UKM Bangi 43600 Malaysia Department of Oil and Gas Engineering Basrah University for Oil and Gas Basra Iraq Department of Thermofluids School of Mechanical Engineering Universiti Teknologi Malaysia UTM Skudai Johor Bahru 81310 Malaysia Department of Computer Sciences College of Education for Pure Science University of Thi-Qar Nasiriyah 64001 Iraq Information and Communication Technology Research Group Scientific Research Center Al-Ayen University Nasiriyah 64001 Iraq Department of Mechanical Engineering College of Engineering University of Baghdad Baghdad Iraq Computational and Applied Mechanics Department Federal University of Juiz de Fora 36036-900 Brazil Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Prevention and Guangdong Provincial Key Laboratory of Marine Biotechnology Shantou University Shantou 515063 China School of Computer and Information Qiannan Normal University for Nationalities Guizhou Duyun 558000 China Institute of Big Data Application and Artificial Intelligence Qiannan Normal University for Nationalities Guizhou Duyun 558000 China Faculty of Data Science and Information Technology INTI International University 71800 Malaysia

This study proposes different standalone models viz: Elman neural network (ENN), Boosted Tree algorithm (BTA), and f relevance vector machine (RVM) for modeling arsenic (As (mg/kg)) and zinc (Zn (mg/kg)) in marine sediments owing to anthropogenic activities. A heuristic algorithm based on the potential of RVM and a flower pollination algorithm (RVM-FPA) was developed to improve the prediction performance. Several evaluation indicators and graphical methods coupled with visualized cumulative probability function (CDF) were used to evaluate the accuracy of the models. Akaike (AIC) and Schwarz (SCI) information criteria based on Dickey-Fuller (ADF) and Philip Perron (PP) tests were introduced to check the reliability and stationarity of the data. The prediction performance in the verification phase indicated that RVM-M2 (PBAIS = -o.0465, MAE = 0.0335) and ENN-M2 (PBAIS = 0.0043, MAE = 0.0322) emerged as the best model for As (mg/kg) and Zn (mg/kg), respectively. In contrast with the standalone approaches, the simulated hybrid RVM-FPA proved merit and the most reliable, with a 5 % and 18 % predictive increase for As (mg/kg) and Zn (mg/kg), respectively. The study's findings validated the potential for estimating complex HMs through intelligent data-driven models and heuristic optimization. The study also generated valuable insights that can inform the decision-makers and stockholders for environmental management strategies. © 2024 Elsevier Ltd

关键词： Artificial intelligence Heavy metals Sensitivity analysis Soil contamination

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SRSC: Improving Restore Performance for Deduplication-Based Storage Systems

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ZTE Communications 2019年第2期17卷 59-66页

作者： ZUO Chunxue WANG Fang TANG Xiaolan ZHANG Yucheng FENG Dan Key Laboratory of Information Storage Systems Engineering Research Center of Data Storage Systems and TechnologyHuazhong University of Science and TechnologyWuhanHubei 430074China 5G Application Product Line ZTE CorporationShenzhenGuangdong 518057China

Modern backup systems exploit data deduplication technology to save stor-age space whereas suffering from the fragmentation problem caused by *** degrades the restore performance because of restoring the chunks thatare scattered all over different containers. To improve the restore performance, thestate-of-the-art History Aware Rewriting Algorithm(HAR) is proposed to collect frag-mented chunks in the last backup and rewrite them in the next backup. However, dueto rewriting fragmented chunks in the next backup, HAR fails to eliminate internalfragmentation caused by self-referenced chunks(that exist more than two times in abackup) in the current backup, thus degrading the restore performance. In this paper,we propose Selectively Rewriting Self-Referenced Chunks(SRSC), a scheme that de-signs a buffer to simulate a restore cache, identify internal fragmentation in the cacheand selectively rewrite them. Our experimental results based on two real-world datas-ets show that SRSC improves the restore performance by 45% with an acceptable sac-rifice of the deduplication ratio.

关键词： data deduplication fragmentation restore performance

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Pretreatment MRI radiomics analysis allows for reliable prediction of local recurrence in non-metastatic T4 nasopharyngeal carcinoma

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EBioMedicine 2019年 42卷 270-280页

作者： Zhang, Lu-Lu Huang, Meng-Yao Li, Yan Liang, Jin-Hui Gao, Tian-Sheng Deng, Bin Yao, Ji-Jin Lin, Li Chen, Fo-Ping Huang, Xiao-Dan Kou, Jia Li, Chao-Feng Xie, Chuan-Miao Lu, Yao Sun, Ying Department of Radiation Oncology Sun Yat-sen University Cancer Center State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy Guangzhou 510060 China School of Mathematics Sun Yat-Sen University Guangzhou 510060 China School of Data and Computer Science Sun Yat-sen University Guangzhou 510060 China Department of Radiation Oncology Wuzhou Red Cross Hospital 543002 Guangxi Province China Department of Radiation Oncology The Fifth Affiliated Hospital of Sun Yat-sen University Zhuhai 519000 Guangdong Province China Department of Information Technology Sun Yat-sen University Cancer Center State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy Guangzhou 510060 China Imaging Diagnosis and Interventional Center Sun Yat-sen University Cancer Center State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy Guangzhou 510060 China

Background: To identify a radiomics signature to predict local recurrence in patients with non-metastatic T4 nasopharyngeal carcinoma (NPC). Methods: A total of 737 patients from Sun Yat-sen University Cancer Center (training cohort: n = 360;internal validation cohort: n = 120)and Wuzhou Red cross Hospital (external validation cohort: n = 257)underwent feature extraction from the largest axial area of the tumor on pretreatment magnetic resonance imaging scans. Feature selection was based on the prognostic performance and feature stability in the training cohort. Radscores were generated using the Cox proportional hazards regression model with the selected features in the training cohort and then validated in the internal and external validation cohorts. We also constructed a nomogram for predicting local recurrence-free survival (LRFS). Findings: Eleven features were selected to construct the Radscore, which was significantly associated with LRFS. For the training, internal validation, and external validation cohorts, the Radscore (C-index: 0.741 vs. 0.753 vs. 0.730)outperformed clinical prognostic variables (C-index for primary gross tumor volume: 0.665 vs. 0.672 vs. 0.577;C-index for age: 0.571 vs. 0.629 vs. 0.605)in predicting LRFS. The generated radiomics nomogram, which integrated the Radscore and clinical variables, exhibited a satisfactory prediction performance (C-index: 0.810 vs. 0.807 vs. 0.753). The nomogram-defined high-risk group had a shorter LRFS than did the low-risk group (5-year LRFS: 73.6% vs. 95.3%, P <.001;79.6% vs 95.8%, P =.006;85.7% vs 96.7%, P =.005). Interpretation: The Radscore can reliably predict LRFS in patients with non-metastatic T4 NPC, which might guide individual treatment decisions. Fund: This study was funded by the Health & Medical Collaborative Innovation Project of Guangzhou City, China. © 2019

关键词： Local recurrence Magnetic resonance imaging Nasopharyngeal carcinoma Radiomics T4 disease

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H2O2-Responsive NIR-II AIE Nanobomb for Carbon Monoxide Boosting Low-Temperature Photothermal Therapy

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Angewandte Chemie 2022年第36期134卷

作者： Gongcheng Ma Zhongke Liu Chunguang Zhu Prof. Huajie Chen Prof. Ryan T. K. Kwok Prof. Pengfei Zhang Ben Zhong Tang Prof. Lintao Cai Prof. Ping Gong Guangdong Key Laboratory of Nanomedicine Shenzhen Engineering Laboratory of Nanomedicine and Nanoformulations CAS-HK Joint Lab for Biomaterials Research Laboratory for Biomedical Optics and Molecular Imaging Shenzhen Key Laboratory for Molecular Imaging CAS Key Lab for Health Informatics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China University of Chinese Academy of Sciences Beijing 100049 China Contribution: Data curation (lead) Validation (lead) Writing - original draft (lead) Nano Science and Technology Institute University of Science & Technology of China Suzhou 215123 China Contribution: Data curation (equal) Investigation (equal) Key Laboratory of Environmentally Friendly Chemistry and Application of the Ministry of Education College of Chemistry Xiangtan University Xiangtan 411105 China Contribution: Data curation (supporting) Methodology (supporting) Contribution: Project administration (supporting) Resources (supporting) Supervision (supporting) Writing - review & editing (equal) Department of Chemistry Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction and Institute for Advanced Study The Hong Kong University of Science and Technology (HKUST) Clear Water Bay Kowloon Hong Kong China Contribution: Funding acquisition (equal) Supervision (equal) Writing - review & editing (equal) Contribution: Conceptualization (lead) Formal analysis (lead) Methodology (equal) Project administration (lead) Resources (equal) Supervision (equal) Writing - original draft (equal) Writing - review & editing (lead) School of Science and Engineering Shenzhen Institute of Aggregate Science and Technology The Chinese University of Hong Kong Shenzhen Guangdong 518172 China Contribution: Formal analysis (supporting) Funding acquisition (equal) Writing - review & editing (supporting) Contribution: Funding acquisition (lead) Project administration (lead) Supervision (lead) Writing - revi

Low-temperature photothermal therapy (PTT), which circumvents the limitations of conventional PTT (e.g., thermotolerance and adverse effects), is an emerging therapeutic strategy which shows great potential for future clinical applications. The expression of heat shock proteins (HSPs) can dramatically impair the therapeutic efficacy of PTT. Thus, inhibition of HSPs repair and reducing the damage of nearby normal cells is crucial for improving the efficiency of low-temperature PTT. Herein, we developed a nanobomb based on the self-assembly of NIRII AIE polymer PBPTV and carbon monoxide (CO) carrier polymer mPEG(CO). This smart nanobomb can be exploded in a tumor microenvironment in which hydrogen peroxide is overexpressed and release CO into cancer cells to significantly inhibit the expression of HSPs and hence improve the antitumor efficiency of the low-temperature PTT.

关键词： Aggregation Induced Emission Gas Therapy Heat Shock Protein NIR-II Photothermal Therapy

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Mapping essential urban land use categories in China(EULUC-China):preliminary results for 2018

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science Bulletin 2020年第3期65卷 182-187页

作者： Peng Gong Bin Chen Xuecao Li Han Liu Jie Wang Yuqi Bai Jingming Chen Xi Chen Lei Fang Shuailong Feng Yongjiu Feng Yali Gong Hao Gu Huabing Huang Xiaochun Huang Hongzan Jiao Yingdong Kang Guangbin Lei Ainong Li Xiaoting Li Xun Li Yuechen Li Zhilin Li Zhongde Li Chong Liu Chunxia Liu Maochou Liu Shuguang Liu Wanliu Mao Changhong Miao Hao Ni Qisheng Pan Shuhua Qi Zhehao Ren Zhuoran Shan Shaoqing Shen Minjun Shi Yimeng Song Mo Su Hoi Ping Suen Bo Sun Fangdi Sun Jian Sun Lin Sun Wenyao Sun Tian Tian Xiaohua Tong Yihsing Tseng Ying Tu Hong Wang Lan Wang Xi Wan Zongming Wang Tinghai Wu Yaowen Xie Jian Yang Jun Yang Man Yuan Wenze Yue Hongda Zeng Kuo Zhang Neng Zhang Tao Zhang Yu Zhang Feng Zhao Yichen Zheng Qiming Zhou Nicholas Clinton Zhiliang Zhu Bing Xu Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China Tsinghua Urban Institute Tsinghua UniversityBeijing 100084China Center for Healthy Cities Institute for China Sustainable UrbanizationTsinghua UniversityBeijing 100084China Department of Land Air and Water ResourcesUniversity of CaliforniaDavisCA 95616-8627USA Department of Geological and Atmospheric Sciences Iowa State UniversityAmesIA 50011USA State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijing 100101China AI for Earth Laboratory Cross-Strait InstituteTsinghua UniversityBeijing 100084China International Institute for Earth System Sciences Nanjing UniversityNanjing 210093China Research Center for Ecology and Environment of Central Asia Chinese Academy of SciencesUrumchi 830011China Key Laboratory of Forest Ecology and Management Institute of Applied EcologyChinese Academy of SciencesShenyang 110016China National Engineering Laboratory for Applied Technology in Forestry&Ecology in South China College of Life Science and TechnologyCentral South University of Forestry and TechnologyChangsha 410004China College of Surveying&Geo-Informatics Tongji UniversityShanghai 200092China Department of Urban Planning College of Architecture and Urban PlanningTongji UniversityShanghai 200092China Beijing Institute of Urban Planning Beijing 100045China Department of Urban Planning School of Urban DesignWuhan UniversityWuhan 430072China College of Earth Sciences Jilin UniversityChangchun 130061China Research Center for Digital Mountain and Remote Sensing Application Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China Institute of Remote Sensing and Geographic Information System School of Earth and Space SciencesPeking UniversityBeijing 100871China Department of Urban and Regional Planning School of Geography and PlanningSun Yat-sen Univ

Land use reflects human activities on *** land use is the highest level human alteration on Earth,and it is rapidly changing due to population increase and *** areas have widespread effects on local hydrology,climate,biodiversity,and food production[1,2].However,maps,that contain knowledge on the distribution,pattern and composition of various land use types in urban areas,are limited to city *** mapping standard on data sources,methods,land use classification schemes varies from city to city,due to differences in financial input and skills of mapping *** address various national and global environmental challenges caused by urbanization,it is important to have urban land uses at the national and global scales that are derived from the same or consistent data sources with the same or compatible classification systems and mapping *** is because,only with urban land use maps produced with similar criteria,consistent environmental policies can be made,and action efforts can be compared and assessed for large scale environmental ***,despite of the fact that a number of urban-extent maps exist at global scales[3,4],more detailed urban land use maps do not exist at the same *** at big country or regional levels such as for the United States,China and European Union,consistent land use mapping efforts are rare[5,6](e.g.,https://***/open_land_use/).

关键词： EULUC-China 土地利用类型

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Digitizing the thermal and hydrological parameters of land surface in subtropical China using AMSR-E brightness temperatures

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International Journal of Digital Earth 2017年第7期10卷 687-700页

作者： Yongxian Su Xiuzhi Chen Hua Su Liyang Liu Jishan Liao Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and ApplicationGuangzhou Institute of GeographyGuangzhouPeople’s Republic of China Jiangsu Key Laboratory of Agricultural Meteorology College of Applied MeteorologyNanjing University of Information Science and TechnologyNanjingPeople’s Republic of China Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems South China Botanical GardenChinese Academy of SciencesGuangzhouPeople’s Republic of China Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education National Engineering Research Centre of Geo-spatial Information TechnologyFuzhou UniversityFuzhouPeople’s Republic of China

Digitizing the land surface temperature(T_(s))and surface soil moisture(m _(v))is essential for developing the intelligent Digital ***,we developed a two parameter physical-based passive microwave remote sensing model for jointly retrieving T_(s) and m_(v) using the dual-polarized T_(b) of Aqua satellite advanced microwave scanning radiometer(AMSR-E)C-band(6.9 GHz)based on the simplified radiative transfer *** using in situ T_(s) and m_(v) in southern China showed the average root mean square errors(RMSE)of T s and m_(v) retrievals reach 2.42 K(R^(2)=0.61,n=351)and 0.025 g cm^(−3)(R^(2)=0.68,n=663),*** results were also validated using global in situ T_(s)(n=2362)and m_(v)(n=1657)of International Soil Moisture *** corresponding RMSE are 3.44 k(R 2=0.86)and 0.039 g cm^(−3)(R^(2)=0.83),*** monthly variations of model-derived Ts and mv are highly consistent with those of the Moderate Resolution Imaging Spectroradiometer T_(s)(R^(2)=0.57;RMSE=2.91 k)and ECV_SM m_(v)(R^(2)=0.51;RMSE=0.045 g cm^(−3)),***,this paper indicates an effective way to jointly modeling T_(s) and m_(v) using passive microwave remote sensing.

关键词： Surface soil moisture land surface temperature physical-based radiative transfer model AMSR-E brightness temperatures

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