Professor, University of Chinese Academy of Sciences, Institute of remote sensing and digital earth, Chinese Academy of sciences. In 2000 by the Chinese Academy of Sciences to the introduction of outstanding talent, is currently the director of the State Key Laboratory of Remote Sensing Science, director of the Institute of remote sensing of environmental health, public health field of space information technology application research center executive director.
Personal profile
Cao Chunxiang, Professor, University of Chinese Academy of Sciences, Institute of remote sensing and digital earth, Chinese Academy of Sciences, doctoral tutor. In 2000 by the Chinese Academy with outstanding talent introduction, currently serves as director, remote sensing of Environmental Health State Key Laboratory of Remote Sensing Science, space science and Chinese executive director of Institute of earth remote sensing and digital public health information technology research center, 863 major projects in earth observation and navigation technology of expert group, and served as a protection association director of science and technology, second China wetland Wetland National Committee of experts, Chinese Institute of health information health geographic information systems professional committee and other national Specialized Committee members; international well-known professor of Boston University and University of Tokyo in Japan with her, Kyoto University founded the "environmental health remote sensing diagnosis" cross disciplinary direction, and created the "environmental health" remote sensing diagnosis Dr. boutique courses at the University Academy of Sciences China.
Cao Chunxiang, after returning home, after more than ten years of painstaking research in 2011 for the global environmental health formally proposed remote sensing diagnosis cross disciplinary research direction; established in 2013 Department of remote sensing on environmental health in the State Key Laboratory of Remote Sensing Science; through the traction around the work group of international cooperation in environmental health remote sensing diagnosis interdisciplinary joint research sponsored by the annual session "environmental health remote sensing diagnosis International Symposium", build a platform for international cooperation and exchanges. Scientific output: a total of 106 s, of which SCI search more than 60 s (the average impact factor of 1.975) in 2013, and well-known professor of united in "Nature", "Nature Climate Change", the journal published a (Temperature and Vegetation Seasonality Diminishment over Northern Lands) remote sensing is the "natural" 10.1038/nm. On the zero breakthrough; again in 2016 published in the "Nature", "Nature Climate Change" 10.1038/nm (Greening of the Earth on and its Drivers), and signed the "Environmental Science Press Health", "environmental health diagnosis of remote sensing remote sensing diagnosis index system", "environmental health", "key technology of remote sensing diagnosis global environmental health", "remote sensing diagnosis Chinese remote sensing diagnosis", "environmental health and environmental health remote diagnosis system" a series of Monographs This version of the contract, first of which have been published in 2013, published in 2015 on the "diagnosis" forest biomass remote sensing monographs; for major national strategic needs put forward the recommendations in the report of 5 were above the provincial level leadership instructions. Over the past 863 years, a total commitment to the country's major projects, the number of projects, such as the national defense science and Industry Bureau and other research projects of 23, access to software copyright of the invention, the application for invention patents, access to utility model patents of 1, a total of 6 projects in the past 5 years, with a total of more than $7.
Education
1996 - 2000.03 of Japan's Hiroshima University School of Biosphere Science, (environmental planning remote sensing) Ph.D.
1994.04 - 1996.03, Japan's Agriculture Department of Kyoto Prefectural University, received a master's degree in forestry
Bachelor's degree, 1982.09 - 1986.07 Inner Mongolia Agricultural University Department of forestry
work experience
Since 2003, the executive director of public health application of spatial information technology research center
So far, 2013-03 Chinese Institute of remote sensing and Digital Earth Research Institute of State Key Laboratory of Remote Sensing Science remote sensing research director of environmental health
2012-04~2013-03 Chinese, Institute of remote sensing and Digital Earth Institute researcher innovation
Study on Application of 2008-01~2012-04, Chinese academy innovation researcher
Research on the application of 2000-01~2008-12, Chinese project researcher at the Institute of remote sensing
1986-08~1993-03, Inner Mongolia Forestry Bureau of Hohhot City Saihan District Engineer
In the party and mass organizations, part-time
2013-03 month, has served as Chinese Academy of Sciences, Institute of remote sensing and digital earth State Key Laboratory of Remote Sensing Science Second Party branch branch
So far, 2012-07 College of resources and environment, University of Electronic Science and Technology Professor
Study on Application of 2007-01 - 2011-01, Chinese Institute of remote sensing institute a branch branch
Study on Application of 2007-06 - 2012-09, Chinese Institute of remote sensing is divided by the chairman of the trade union
On behalf of 2007-05 - 2011-09, China Academy of Sciences, Institute of remote sensing application session of the Fifth Congress
On behalf of 2003-06, 2007-06 Chinese Fourth Academy of Sciences Institute of remote sensing application session of Congress
1986-12 1993-03, Inner Mongolia Forestry Bureau of Hohhot City Saihan district Party Branch Committee Propaganda
Postgraduate training
Researcher Cao Chunxiang since his return in local graduate training more than 20, of which 2 postdoctoral fellows, 9 Ph.D., received a master's degree in 2, graduating students go to the system, China Academy of Sciences and the National Space Agency, the state forestry system; recruit from Thailand, Nepal, Pakistan 6 international students, exchange exchanges and cooperation with the Boston University, the Max Planck Institute, Kyoto University, Hokkaido University, University of Fukui, Japan, and other international well-known universities and academic institutions have students; graduate and graduate student scholarship awards including the dean Chinese Academy 1, Chinese academy scholarship director of 2 people, 2 people the title of outstanding graduates of Graduate University of Chinese Academy of Sciences, University of Science Institute Chinese three good student TITLE 7 people, 1 people of the remote sensing model of three good student; in 2012 China Academy Learn the first "environmental health remote sensing diagnosis," dr..
Dr. Zhong Shaobo: "GIS and remote sensing applied to the epidemiology of infectious diseases - hepatitis B and highly pathogenic avian influenza as an example" 2006
Dr. Guo Jianping: "remote sensing quantitative modeling of aerosol and suce reflectance in the underlying suce of the land" 2007
Dr. Bai Linyan: "quantitative inversion of atmospheric aerosol remote sensing satellite with high suce facies" 2009
Dr. Bao Yunfei: Research on Forest Parameter Extraction Based on multi source remote sensing data 2009
Dr. He Qisheng: "cooperative inversion of forest biomass based on multi-source remote sensing data" 2010
Dr. Xu Min: spatial temporal distribution and prediction of cholera in China based on spatial information technology 2011
Dr. Gao Mengxu: "the study on the Himalaya Tibet Plateau marmot plague foci in the spatial distribution of 2011
Dr. Ni Xiliang: Remote Sensing Inversion of forest biomass in China based on scale growth theory 2013
Dr. Zhao Jian: remote sensing estimation of shrub biomass in Mu Us sandy land 2013
Dr. Huang Mingren PEERA YOMWAN (Thailand students): "caused by multi temporal satellite images and BP neural network model based on the flood of water-borne diseases research" 2014
Dr. Xiang Haibing: Research on LiDAR and PolInSAR cooperative inversion tree height 2014
The ark: "Dr. ramorum disease in Chinese potential outbreak risk forecast and early warning on" 2014
Dr. Zheng Sheng: "the characteristics of air pollution in Beijing and its influence on human health by remote sensing" 2015
Dr. Tian Rong: wetland health remote sensing 2015
Dr. Apitach INSOM (Thailand): "monitoring of infectious diseases caused by flood based on geospatial information technology" 2015
Dr. Yang Bin: "Research on Remote Sensing Extraction of three dimensional greenness based on image and lidar" 2015
Zhao Xiaojie: remote sensing diagnosis based on multi source remote sensing data of bamboo willow global distribution 2015
Dr. Patcharin Insom (Thailand international student): application of state estimation techniques in land class identification: a case study of flood inundation area identification and wetland change monitoring, 2016
Study on the inversion of shrub biomass in Mu Us sandy land based on multi source remote sensing data 2017
Liu Di: Wetland biomass remote sensing diagnosis 2017Bipin Kumar Acharya (Nepalese students): human activity response remote sensing 2017
Shahid Naeem (Pakistan students): human activity response to remote sensing 2017
Bao Shanning: crop health remote sensing 2018
Song new Sornkitja Boonprong (Thailand students): vegetation health remote sensing 2018
Yang Tianyu: Wetland infectious diseases remote sensing 2019
Master Chen Wei: comparative analysis of remote sensing inversion of vegetation coverage in Mu Us sandy land 2012
Liu Cheng's master: "prediction and risk assessment of tree flu" in China based on GIS 2013
Wang Mengya, master, "analysis of optical properties and radiative effects of dust aerosol in Beijing" 2015
Liu Xia: Study on the inversion model of forest biomass based on resource three images ", 2015
Yin Hang: snow cover and environmental health response remote sensing 2018
Jiang Houzhi: tree flu early warning model 2018
Wu Chunying: wetland health remote sensing 2018
Mani: regional vegetation remote sensing after the earthquake 2019
Liu Mingbo: forest remote sensing cooperative inversion 2019
Aman Chang: remote sensing of atmospheric health 2019
Undertake scientific research projects
Cao Chunxiang, in recent years, 973, undertake 863 major national special project, National Natural Science Fund. A total of 23 projects, through the project carrying scientific research way to vigorously promote the development of environmental health remote sensing diagnosis subject.
1, the country's major projects, "the typical application of global quantitative remote sensing product production system" () (2013AA12A302)
Project organization of more than and 30 units, the typical application field of global quantitative remote sensing index system, establish a research in the key algorithm model, process based on the global common products based on quantitative remote sensing data source, research and development for the global forestry, agriculture, mineral resources, water resources, ecological environment and other typical applications of quantitative remote sensing thematic products the production system, and distributed deployment in the national forestry, agriculture, mineral resources, water resources, ecological environment and other related business departments, formed more than 20 kinds of typical quantitative applications of remote sensing thematic products production capacity, production capacity and more than 20 kinds of elements of the ecological environment monitoring and diagnostic products, and relying on quantitative remote sensing thematic products in service with the government the public and user oriented operating system. After the completion of the system in the forest biomass and carbon storage of global remote sensing estimation, 100m grid, overseas production the key region of 300-500m biological grid forest biomass and carbon reserves distribution of 2; the bulk of the world's crop production estimation, achieve monthly, quarterly and annual crop growth, yield and drought monitoring results released, covering more than 90% of global crop production; important mineral resources and energy remote sensing detection and evaluation of global metallogenic belt, the construction of global mineral resources and energy remote sensing detection and evaluation system, complete the South American giant ore into multi-scale remote sensing detection and evaluation of important mineral resources and energy; international rivers hydrological simulation platform forecast and remote sensing monitoring information management hand, sudden disaster monitoring and monitoring report submitted in 10 hours after the acquisition of data; ecological environment remote sensing monitoring Measurement, the production of more than 20 kinds of global change sensitive areas of ecological environment factors demonstration products.
2, the major projects of national science and technology project "integrated information analysis and dissemination of infectious disease risk prediction technology research" project seven "demonstration of the application of information visualization research on infectious disease" (2008ZX10004012)
The project is based on the Shenzhen city information resources, cross disciplinary theory and method by using digital technology, information technology and network technology, from the visual angle to describe the spatial distribution and spread of infectious diseases, the establishment of the Shenzhen City Infectious Disease visualization and prediction and early warning system; fitting and predicted incidence trend of main infectious diseases in Shenzhen City influenza, malaria, diarrhea 8 minutes, kidney hemorrhagic fever; and completed the routine monitoring and early warning of the major infectious diseases, to realize sharing of cross sectoral attribute data, spatial and temporal analysis and field, human resource allocation, the system key technology breakthrough lies in the city of basic geographic information data, data, data of infectious diseases, medical site climate the environmental quality data, data integration in the same platform, can show from a different point of view in the form of property The characteristics and laws of infectious diseases were analyzed, and the main infectious diseases were predicted by analyzing the change characteristics of climate and environmental factors. Interactions in modern society is becoming more and more complex, the space partition model of a discrete form of predicting the spread of infectious diseases, the model considers the complex spatial contact patterns between individuals in modern society, and the real situation of widespread population heterogeneity and heterogeneity. The project to build the Shenzhen infectious disease visualization and forecasting and early warning system, city level simulation and analysis system of infectious diseases, infectious disease 3D visualization system for improving the ability of monitoring and early warning of infectious diseases in Shenzhen City, Shenzhen city to promote the development of public health are very important social benefits.
3, the National Natural Science Foundation of China "SAR and LIDAR parameters of the cooperative inversion model and method" (40871173)
The project is to further strengthen the algorithm to study the radiation mechanism and the forest structure parameters of active microwave and active optics, two active remote sensing forest structure parameters of cooperative inversion, improve the inversion precision of single sensor forest structure parameters, interference in SAR scattering model, LIDAR parameter based small spot extraction, large spot number LIDAR waveform simulation, terrain parameter setting the different of the vertical structure of vegetation parameter inversion model of computer simulation, quantitative analysis of sensitivity of interferometric SAR and LIDAR on forest structure and topographic parameters; according to the full waveform model prior knowledge and LIDAR data extraction of forest structure parameters and geometric optical radiative transfer model to build large spot laser radar, using waveform inversion map of forest structure parameters other forest structural parameters and interpolation to large areas to get the whole image decomposition technique Comprehensive coverage of SAR interference; and small spot LIDAR discrete points acquired high elevation accuracy, the integration of the two techniques, change the SAR scattering model of interference, and combined with the discrete LIDAR data provided to SAR extraction of forest structure parameters of the final accuracy, forest structure parameters in large area on the expansion of the real three-dimensional forest distribution; the scene of interferometric SAR backscattering signal, the laser echo waveform of the forward simulation analysis of two kinds of sensors, analog signal and its components or its description parameters on forest structure and topographic parameters of sensible, based on geometrical optics model of two levels of DEM and canopy on the interferometric coherence and polarization target decomposition technique and using LIDAR technology the optimal, considering multi scale effect, realize the interference SAR and LIDAR Comprehensive Forest parameter inversion, relative to a single data inversion to improve the accuracy of 5-10%.
4, the National Natural Science Foundation of China "based on spatial information technology of Chinese tree influenza risk and forest health correlation analysis" (41171330)
The main project of tree flu pathogen in Chinese suitable areas distribution research, simulation analysis and prediction based on tree flu outbreak and spread risk, based on the analysis of risk and forest health related tree flu outbreak, and the forest health diagnosis and evaluation, so as to maximize the protection of forest resources china. The project focuses on the climate elements of geographical spatial and temporal distribution of the known influenza pathogen analysis tree in different regions Chinese adaptability, and distribution area of remote sensing and GIS spatial information technology research based on the host tree species in China, observation factor acquisition of each species, including canopy and canopy structure parameters, LAI, biomass, etc. with these parameters as indicators, combined with prior knowledge and forest survey data, to determine whether tree species may be infected tree flu, through field verification, prediction and analysis of tree flu outbreak risk. At the same time on the diffusion pattern and direction of the British "tree flu" in the case of the disease, risk analysis and prediction of the incoming China and further diffusion from the aspects of geography and management standards, the possibility of colonization and colonization after the possibility of diffusion. Based in the risk of outbreaks of influenza research China tree, in view of the influence of the outbreak of the physiological and ecological characteristics of forest trees tree flu, for forest health assessment, establish appropriate indicators, correlation analysis between tree and forest health risk of flu. Based on remote sensing and GIS spatial information technology to obtain the parameters, the State Forestry forest survey data and tree flu monitoring results of the pathogen of suitable areas for forest health diagnosis, which can provide reference for the forest resource monitoring and evaluation.
5, the State Forestry Administration Project "wetland ecosystem evaluation system"
The project on the basis of literature research, through a comprehensive investigation, expert consultation and field verification work, based on "monitoring, reporting and operation" as the guiding principle, the wetland ecosystem health, function, value three aspects to set up a scientific and reasonable and feasible evaluation index system. And in February 29, 2012 successfully passed the national forestry bureau of science and Technology Committee of experts. The index system for all types of wetlands in this classification system, the index of wetland ecosystem health, function and value evaluation index system and its calculation method, for the evaluation of the wetland nature reserve or the minimum administrative region as a single wetland unit health status, functional strength and economic value, can be for the same type of wetland ecosystem health, function and value. The evaluation index system of wetland ecosystem wetland according to the project implementation plan in the final draft, the evaluation index system of wetland ecosystem health of the 5 major categories of 13 indicators, the evaluation index system of wetland ecological system of 4 categories of 7 indicators, the evaluation index system of wetland ecosystem value of the 4 categories of 8 indicators field validation. To promote the transformation of evaluation system of wetland ecological system from research to production, to further improve the scientific and representative national assessment of wetland values, different types of international focus on 7 key projects of wetland wetland GEF5 planning projects and other various areas in China to expand the application of wetland ecological system evaluation pilot, completed the work of ecological system evaluation and demonstration of two batches of a total of 21 wetland pilot development, its demonstration effect will lead to national wetland protection, wetland management, scientific research and reasonable utilization to provide timely and accurate reference.
6, Qinghai Province, a major scientific and technological research project "Qinghai East Kunlun metallogenic belt characteristics and the suce of the complex geological conditions of multi-scale remote sensing target detection technology"
The joint project of 4 units, according to the geometrical properties of refine the metallogenic model of different spatial scale metallogenic geological targets and remote sensing information of physical attributes corresponding fitting principle, considering the complexity of the suce, the formation of different platform of aerospace remote sensing data supporting the selection and goal oriented data processing technology for comprehensive scheme. The area has the full collection of geological, mineral, geophysical and geochemical exploration, remote sensing geology, comprehensive information, scientific research and other geological data, find out the previous work, the main mineral anomaly verification problems and breakthrough in the work, as a basic research work, through all kinds of information, information collection, build a research platform. At the same time, the genetic types, temporal and spatial distribution characteristics, regional metallogenic geological background, metallogenic environment and ore controlling factors of known ore deposits are studied. The focus and Research on typical deposits by analogy, in theory, summarize the metallogenic regularity, plays the role of point. In the end, the metallogenic regularity is summarized, and the key techniques of the prediction target area and the ore prospecting breakthrough of the major mineral and metallogenic type of large and medium-sized deposits (mineral resources) are proposed. At the same time comprehensive analysis system to construct a fast large metallogenic target location in remote sensing image model - sensor model - processing model in one model, the formation of the East Kunlun metallogenic belt is the representative of the Qinghai geological prospecting information sharing service platform technology. The research of this project by using the uncertainty of spatial data mining model improves the precision by determining the target of remote sensing, Crosta in the diagnosis of clear known deposits in East Kunlun area (DOT) variable features in the image in Crosta, and the remote sensing technology from Kunlun to West Shandong were delineated 58 class I, class I, class II class target area.
The 7 and 973 sub project "integrated model and method of SAR and lidar vegetation parameters inversion"
The project through the forward simulation of scattering signal, the laser echo waveform of real 3D scene forest distribution of interferometric SAR, analysis of two kinds of sensor analog signal and its components or its description of the features of parameter sensitivity on forest structure and topographic parameters, based on forest structure parameters play comprehensive inversion model and method according to the respective advantages of the two species. The first project is studied by using the forest biomass estimation method of SAR data, combined with the regional forest biomass generated by LiDAR weight distribution, SAR extraction and analysis of biomass on different scales in response to LiDAR, finally established the forest biomass estimation method based on stand scale. LiDAR and SPOT5 were used to retrieve forest biomass, and the model was established by multiple stepwise regression model by using the normalized point cloud statistics and the indicator factors selected by SPOT5 to extract forest biomass. Collaborative retrieving forest biomass by using SAR and SPOT5, the neural network model of SPOT5 extraction of forest biomass when selecting indicators of HH, SAR and HV polarization data as the input data of the neural network, the establishment of cooperative retrieval model based on neural network. Finally, SAR, SPOT5 and LiDAR combined with multi-source remote sensing data to collaborative retrieving forest biomass, from the angle of model establishment of leaf area index, structure parameters and optical LiDAR data extraction coverage to collaborative microwave backscattering model, cooperative inversion model of multi-source remote sensing data to establish based on physical mechanism.
8, the key project of the Chinese Academy of Sciences, two-color infrared remote sensing system for environmental health research and development"
Infrared remote sensing application project for resource exploration, environmental monitoring, the key technology breakthroughs related to infrared focal plane physics, materials and devices, and further improve the basic technical platform is necessary, on the basis of existing research, the two color infrared remote sensing environmental health diagnosis system research. Study on the long wavelength two-color focal plane detector component 128 * 128 / to carry out the specific needs, both through the detection of infrared target specific absorption requirements of accurate positioning and stable device detection wavelength repeatability, array as effective optimization and system improvement of the temperature resolution element, make the application of the device more fit high. At the same time, the related research and device verification of resource remote sensing application. Specifically to remote sensing and digital earth China Academy of Sciences Institute of infrared remote sensing application for traction, carry out double color infrared remote sensing environmental health diagnosis system research, analysis to validate the applicability of two color infrared optical detection system of suce temperature, forest fires, city heat island environmental health factor, to complete the system of spectrum and spectral response function working temperature and the consistency of pixel response parameters evaluation and uncertainty analysis, which is the key component of infrared infrared remote sensing in the localization and to contribute to the upgrade. The project achieved stable and high uniformity of repeated mid / long wave double color laminated quantum well infrared detector array chip preparation technology, the performance of similar devices to maintain the domestic front, infrared double color array in the application of multi domain leading; shorten the gap with the international level, through practical verification and evaluation, provide the basis for to truly meet the needs and the subsequent promotion plan.
9. "CAS-TWAS" project for the scientific research of space disaster reduction in China: A Study on flood disaster mitigation in flood prone areas based on spatial information technology cooperation between China and Southeast Asian countries"
As one of the most destructive natural disasters, flood disasters have caused a lot of casualties and economic losses all over the world. In the context of global climate change and economic development, the impact of flood disaster on a global scale is expected to be more serious, especially in the region of asia. When the flood disaster occurs, people in flooded areas will suffer the risk of infection of infectious diseases, especially for some waterborne infectious diseases (water-borne diseases). In recent years, remote sensing technology played an important role in flood disaster monitoring and disaster assessment, but the dynamic changes of the application of remote sensing technology in waterborne infectious diseases and environmental related disease is rare. In addition, the flood disaster occurred during remote sensing data acquisition by cloud and return to the cycle, it is difficult to rely on a single remote sensing data sources to meet the needs of rapid monitoring of flood, to be through data sharing mechanism and Constructing Flood stricken areas of spatial database to resolve. According to the characteristics and developing trend of flood disaster in Asian countries, the aims of the space China with Southeast Asia information technology cooperation, establish and perfect the Thailand Yom basin and Yangtze River Basin Chinese typical disaster spatial database, and on this basis to build an integrated model by the rapid monitoring of flood model and water-borne diseases caused by floods the risk assessment model of integration. The good cooperation between the research group and Southeast Asian countries have, through the spatial data sharing, flood mitigation technology exchange, personnel training mode of communication to conduct a more in-depth cooperation, for Chinese Academy of remote sensing and digital earth research development of new interdisciplinary Tim brick Bhargava, training senior technical talents in the field of space for flood disaster mitigation for the developing countries in Asia, and further widen the space disaster exchanges and cooperation with other Asian countries on the road.
10, forestry public welfare industry research special tree flu outbreak risk remote sensing diagnosis and early warning research
The "tree flu" names "sudden oak death", the disease is caused by the devastating forest and ornamental plant diseases, can cause fatal damage to the trees in a short period of time. The disease caused by tree flu can spread infection of leaves, twigs, plants and plant seedlings, after the infection has no effective prevention methods. Based on Remote Sensing (RS), geographic information system (GIS) remote sensing diagnosis and early warning can save a lot of manpower and material resources to the tree flu outbreak based spatial information technology, quickly and accurately understand the tree flu adaptability and propagation mechanism, to prevent the spread of germs spread tree flu, influenza outbreak risk control tree. Multi-source remote sensing and geographic environment, climate, etc. based on the establishment of a global "flu" factor data set of "tree flu" in temporal and spatial distribution of global; spatial information technology as the main method to analyze the influence of the main environmental background factor tree flu distribution and spread; according to the pest risk assessment theory, establish the "tree flu" intrusion risk index system and early-warning model, and provide technical support for the protection of forest resources, State Forestry Safety in china.
11, the Three Gorges follow-up research project "Three Gorges reservoir ecological barrier area ecological benefit monitoring technology and evaluation method"
In the investigation and analysis of existing resources and monitoring of ecological barrier zone in the Three Gorges Reservoir Area on the basis of the issues, carry out the rapid extraction of forest ecosystem ecological barrier zone technology, ecological monitoring technology, forest ecosystem ecological barrier zone comprehensive evaluation system of ecological benefit technology, forest ecosystem ecological barrier zone and reservoir impact assessment of social and economic development the work of forest vegetation ecological barrier zone of temporal and spatial variation, a set of available ecological benefit monitoring and evaluation index system and method of comprehensive building. Including: focus on capture of forest vegetation spatio-temporal change of forest area, forest volume parameter estimation technology difficulty, explore the formation of rapid extraction method of forest vegetation spatial and temporal variations, and large Laoling pilot demonstration area, fast update forest volume monitoring index. Study on the index system and method of ecological benefit monitoring in Three Gorges Reservoir area, the optimization of ecological monitoring network system and the application of demonstration area. Participate in the evaluation index system and method of ecological benefit of the Three Gorges Reservoir area and the application of demonstration area, and the research on the effect of forest and land use change on the social and economic development.
12, the scientific and technological foundation of the special work of China's wetland resources and its main ecological environment comprehensive investigation"
In "technical specification for" Chinese marsh "satellite remote sensing investigation and classification system of wetland and investigation standard" as a guide, the use of medium and high resolution remote sensing image as the main data source, reference of the natural geographical background and social economic background, to identify the status of the southwest plateau marsh wetland in China (2010-2012) and the past 30 3 Main Years (2000, 1990, 1980) the concentrated distribution area of wetland types, quantity, location, area, distribution. Based on the survey data, the constructed wetland ecosystem in China southwest plateau marsh health evaluation model of China's typical marsh wetland southwest plateau (Ruoergai and Sanjiang source wetland) of wetland ecosystem health assessment and threat analysis of wetland ecosystem health main driving factor.
13, independent cultivation project
Since 2007, Professor Cao Chunxiang led research room every two years, raised funds in Inner Mongolia were in Maowusu Sandy Land synchronous field experiment has been carried out 4 experiments (2007, 2009, 2011, 2013), accumulated a large number of experimental data.
14, the team members to lead or participate in other projects
Wetland protection and management center of the State Forestry Administration of the Yangtze River basin"
Chinese Academy of international cooperation project "based on remote sensing and remote sensing satellite data in flood prone areas of flood disaster monitoring and forecasting and early warning"
Chinese Academy of Sciences Institute of remote sensing and digital earth "135" strategic deployment breakthrough of the "project of the three" quantitative simulation of remote sensing system"
The State Key Laboratory of Remote Sensing Science (ZD12-5), a sub project of "environmental change and public health", "global remote sensing analysis of cholera"
A study on the scientific research foundation of the State Key Laboratory of Remote Sensing Science: a dynamic model of hand foot mouth disease based on human settlements"
Study on the temporal and spatial transmission and epidemic of infectious diseases based on modern information technology"
The State Key Laboratory of Remote Sensing Science: an emergency risk assessment based on spatial information technology after the 512 earthquake"
A study on ecological environment suitability and spatial regulation of Qinghai County in Qinghai, Ledu"
Study on the spatial and temporal distribution and prediction model of cholera in the southeast coastal area of china"
Study on the environmental impact factors of H7N9 avian influenza and the model of time and space propagation in the youth talent project of Chinese Academy of sciences"
Journal articles
[106]Liu Di，Cao Chunxiang，Wei Chen, Xiliang Ni, Rong Tian, Xiaojun Xing,”Monitoring and predicting the degradation of a semi-arid wetland due to climate change and water abstraction in the Ordos Larus Relictus National Nature Reserve, China”，Geomatics, Natural Hazards and Risk 2016（accepted）
[105]Bipin Kumar Acharya, ChunXiang Cao, Tobia Lakes,Wei Chen and Shahid Naeem.”Spatiotemporal analysis of dengue fever in Nepal from 2010 to 2014”.BMC Health Services Research，2016（accepted）.
[104]Insom P, Cao C, Boonsrimuang P, et al. “A Support Vector Machine-Based Particle Filter Method for Improved Flooding Classification[J]”. IEEE Geoscience & Remote Sensing Letters, 2015, 12(9):1943-1947
[103] Sungho Choi, Christopher P. Kempes, Taejin Park, Sangram Ganguly, Weile Wang, Liang Xu, Saikat Basu, Jennifer L. Dungan, Marc Simard, Sassan S. Saatchi, Shilong Piao, Xiliang Ni, Yuli Shi, Chunxiang Cao, Ramakrishna R. Nemani, Yuri Knyazikhin1, Ranga B. Myneni.”Application of the metabolic scaling theory and water-energy balance equation to model large-scale patterns of maximum forest canopy height”.Global Change Biology.2016(accepted)
[102] Chunxiang Cao, Wei Chen, Sheng Zheng, Jian Zhao, Chaoyi Chang, Jinfeng Wang & Wuchun Cao. “Analysis of Spatiotemporal Characteristics of Pandemic SARS Spread in Mainland China”. BioMed Research International, 2016 (accepted).
[101] Min Xu, Chunxiang Cao, Qun Li, Peng Jia, Jian Zhao.“Ecological niche modelling of risk factors for H7N9 human infection in China”.International Journal of Environmental Research and Public Health. 2016(Accepted).
[100 M. XU, C. X. CAO, D. C. WANG, B. KAN, Y. F. XU, X. L. NI and Z. C. ZHU. “Environmental factor analysis of cholera in China using remote sensing and geographical information systems”.Epidemiology & Infection 2016,144(05):940-951.
[99] Min Xu, Chunxiang Cao, Duochun Wang and Biao Kan.” Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies Int. J. Environ. Res”.Public Health 2015, 12, 354-370
[98]Zaichun Zhu, Shilong Piao, Ranga B. Myneni, Chunxiang Cao et al. “Greening of the Earth and its drivers[J]”. Nature Climate Change, PUBLISHED ONLINE: 25 APRIL 20162016.
[97]Chunxiang Cao, Di Liu, Ramesh P. Singh, Sheng Zheng, Rong Tian & Haijing Tian. “Integrated detection and analysis of earthquake disaster information using airborne data”.Geomatics Natural Hazards & Risk, 2015.
[96]Haijing Tian, Chunxiang Cao, Wei Chen, Shanning Bao, Bin Yang, Ranga B. Myneni. “Response of vegetation activity dynamic to climatic change and ecological restoration programs in Inner Mongolia from 2000 to 2012”. Ecological Engineering, 2015, 82:276–289.
[95]Xiliang Ni, Yuke Zhou, Chunxiang Cao, Xuejun Wang, Yuli Shi, Taejin Park, Sungho Choi and Ranga B. Myneni. “Mapping Forest Canopy Height over Continental China Using Multi-Source Remote Sensing Data”, Remote Sensing, 2015, 7:8436-8452.
[94]Zheng, S., A. Pozzer, C. X. Cao, and J. Lelieveld.”Long-term (2001–2012) concentrations of fine particulate matter (PM 2.5) and the impact on human health in Beijing, China.”Atmospheric Chemistry and Physics 15, no. 10 (2015): 5715-5725.
[93]CaoChunxiang, Sheng Zheng, and Ramesh P. Singh.”Characteristics of aerosol optical properties and meteorological parameters during three major dust events (2005–2010) over Beijing, China.”Atmospheric Research 150 (2014): 129-142.
[92]Insom, Patcharin, Chunxiang Cao, Pisit Boonsrimuang, Di Liu, Apitach Saokarn, Peera Yomwan, and Yunfei Xu. “A Support Vector Machine-Based Particle Filter Method for Improved Flooding Classification.” (2015).
[91]Chengdong Xu, Jinfeng Wang, Li Wang and Chunxiang Cao, “Spatial pattern of severe acute respiratory syndrome in-out flow in 2003 in Mainland China”,BMC Infectious Diseases, 2014.
[90]Bin Yang, Chunxiang Cao, Ying Xing, and Xiaowen Li. “Automatic Classification of Remote Sensing Images Using Multiple Classifier Systems”. Mathematical Problems in Engineering, 2014 .
[89]Min Xu, Chunxiang Cao, et al.” Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies”.Int. J. Environ. Res. Public Health, 2014. (accepted).
[88]Mengya Wang, Chunxiang Cao, Guoshuai Li,Ramesh P. Singh.”Analysis of a severe prolonged regional haze episode in the Yangtze River Delta”,China.Atmospheric Environment, 2014(accepted).
[87]Chunxiang Cao, Haijing Tian et al., “Deriving Regional Crown Closure Using Spectral Mixture Analysis Based on Up-scaling Endmember Extraction Approach and Validation”.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing[SCI2.827]
[86] Wei Chen, Kazuyuki Moriya, Tetsuro Sakai, Lina Koyama, Chunxiang Cao. “Post-fire forest regeneration under different restoration treatments in the Greater Hinggan Mountain area of China”.Ecological Engineering, 2014, 70: 304-311. DOI: 10.1016/j.ecoleng.2014.06.016.(SCI3.041).
[85] Cao Chunxiang, Zheng Sheng,Ramesh P. Singh, et,al “Characteristics of aerosol optical properties and meteorological parameters during three major dust events (2005 – 2010) over Beijing”, China,Atmospheric Research,2014.[SCI 2.421]
[84] 杨斌，曹春香，田蓉，刘诚，田海静，刘迪，项海兵. 2014. 汶川县震后 5年生态环境质量恢复评价. 遥感学报，18 (4 ) : 946-957[CSCD]
[83] W. CHEN, K. MORIYA, T. SAKAI, L. KOYAMA and C.X. CAO. “Mapping a burnedforest area from Landsat TM data by multiple methods”.Geomatics, Natural Hazards and Risk, 2014, DOI: 10.1080/19475705.2014.925982. (SCI 0.622)
[82] Wei Chen, Kazuyuki Moriya, Tetsuro Sakai, Lina Koyama, Chunxiang Cao. “Monitoring of post-fire forest recovery under different restoration modes based on time series Landsat data”. European Journal of Remote Sensing, 2014, 47: 153-168. DOI: 10.5721/EuJRS20144710.[SCI 0.971]
[81] Tian, H.,Cao, C., Xu, M., Zhu, Z., Liu, D., Wang, X., & Cui, S. (2014). “Estimation of chlorophyll-a concentration in coastal waters with HJ-1A HSI data using a three-band bio-optical model and validation”. International Journal of Remote Sensing, (ahead-of-print), 1-20.[SCI 1.359]
[80] Xiliang Ni, Taejin Park , Sungho Choi, Yuli Shi, Chunxiang Cao, Xuejun Wang, Michael A. Lefsky, Marc Simard and Ranga B. Myneni . Allometric Scaling and Resource Limitations Model of Tree Heights: Part 3. Model Optimization and Testing over Continental China. Remote Sens. 6, 3533-3553,2014.[SCI 2.623]
[79]LIU Cheng, CAO ChunXiang. Prediction of potentially suitable distributions of sudden oak death in China based on GIS technology. Chinese Science Bulletin, 2014, 59(18): 1732-1747.[CSCD]
[78] Zhou Fang, Chunxiang Cao. Estimation of Forest Canopy Height over Mountainous Areas Using Satellite LiDAR[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10.1109/JSTARS.2014.2300145.[SCI 2.827]
[77]Tian, Rong, Chunxiang Cao, Ling Peng, Guangren Ma, Daming Bao, Jianhong Guo, and Peera Yomwan. “The use of HJ-1A/B satellite data to detect changes in the size of wetlands in response in to a sudden turn from drought to flood in the middle and lower reaches of the Yangtze River system in China.” Geomatics, Natural Hazards and Risk ahead-of-print (2014): 1-21.[SCI]
[76]Jia, Huicong, Donghua Pan, Yi Yuan, and Chunxiang Cao.”Using a BP Neural Network for Rapid Assessment of Populations with Difficulties Accessing Drinking Water Because of Drought.”Human and Ecological Risk Assessment: An International Journal just-accepted (2014).[SCI]
[75]S. ZHENG, C. X. CAO, J. Q. CHENG, Y. S. WU, X. XIE, M. XU,Epidemiological features of hand-foot-mouth disease in Shenzhen, China from 2008 to 2010,Epidemiology and Infection, (2014)142,1751-1762. [SCI]
[74] Wei Chen, Tetsuro Sakai, Kazuyuki Moriya, Lina Koyama &Chunxiang Cao.Estimation of vegetation coverage in semi-arid sandy land based on multivariate statistical modeling using remote sensing data.Environmental Modeling and Assessment.Environmental Modeling and Assessment, 2013, 18(5): 547-558. DOI:10.1007/s10666-013-9359-1.[SCI]
[73] Zheng, Sheng, Chun-Xiang Cao, and Ramesh P. Singh. “Comparison of ground based indices (API and AQI) with satellite based aerosol products.” Science of The Total Environment 488 (2014): 398-412.[SCI]
[72] Zheng, Sheng, Chunxiang Cao, Yongfeng Dang, Haibing Xiang, Jian Zhao, Yuxing Zhang, Xuejun Wang, and Hongwen Guo. “Retrieval of forest growing stock volume by two different methods using Landsat TM images.”International Journal of Remote Sensing 35, no. 1 (2014): 29-43.[SCI]
[71] Yomwan, Peera, Chunxiang Cao, Preesan Rakwatin, Warawut Suphamitmongkol, Rong Tian, and Apitach Saokarn. “A study of waterborne diseases during flooding using Radarsat-2 imagery and a back propagation neural network algorithm.”Geomatics, Natural Hazards and Risk ahead-of-print (2013): 1-19.[SCI]
[70] Hai-bing Xiang; Jin-song Liu; Chun-xiang Cao; Min Xu. Algorithms for Moderate Resolution Imaging Spectroradiometer cloud-free image compositing. J. Appl.Remote Sens. 7 (1), 073486 (November 05, 2013); doi: 10.1117/1.JRS.7.073486 [SCI]
[69] L. Xu, R. B. Myneni, F. S. Chapin, T. V. Callaghan, J. E. Pinzon, C. J. Tucker, C. Cao, et al. Temperature and vegetation seasonality diminishment over northern lands.Nature Climate Change 3, no. 6 (2013): 581-586. [SCI]
[68] Shi, Yuli, Sungho Choi, Xiliang Ni, Sangram Ganguly, Gong Zhang, Hieu V. Duong, Michael A. Lefsky, Chunxinag Cao et al. “Allometric scaling and resource limitations model of tree heights: Part 1. Model optimization and testing over continental USA.”Remote Sensing 5, no. 1 (2013): 284-306.[SCI]
[67] Xu, Min, ChunXiang Cao, DuoChun Wang, Biao Kan, HuiCong Jia, YunFei Xu, and XiaoWen Li. “District prediction of cholera risk in China based on environmental factors.” Chinese Science Bulletin 58, no. 23 (2013): 2798-2804. (SCI)
[66]Sungho Choi and Xiliang Ni, YuliShi, SangramGanguly Chunxiang Cao et al. Allometric Scaling and Resource Limitations Model of Tree Heights: Part 2. Site based testing of the Model. Remote Sensing, 2013,5(1): 202-223.(SCI)
[65]Chunxiang Cao, Yunfei Bao, et al. Extraction of forest structural parameters based on the intensity information of high-density airborne LiDAR Journal of AppliedRemote Sensing, 2012, 6(1), 063533.(SCI)
[64]Wei Chen, Chunxiang Cao. Topographic correction-based retrieval of leaf area index in mountain areas [J].Journal of Mountain Science, 2012, 9:166-174. (SCI)
[63]Q.S. HE, C.X. CAO, et al. Forest Stand Biomass Estimation Using ALOS PALSAR data based on LiDAR-derived prior knowledge in the Qilian Mountain, western China, International Journal of Remote Sensing. 2012, 33(3): 710-729. (SCI)
[62]Xiliang Ni, Chunxiang Cao, et al., A fully automatic registration approach based on contour and SIFT for HJ-1A/B images[J]. Science China Earth Sciences.2012, 42(8):1245-1252.( SCI)
[61] Zhao, Jian, Min Xu, Shi-lei Lu, and Chun-xiang Cao. “Human settlement evaluation in mountain areas based on remote sensing, GIS and ecological niche modeling.”Journal of Mountain Science 10, no. 3 (2013): 378-387.(SCI)
[60]Huicong Jia, Jingai Wang, Chunxiang Cao, Donghua Pan & Peijun Shi (2012):Maize drought disaster risk assessment of China based on EPIC model, International Journal of Digital Earth, 5:6, 488-515.(SCI)
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[58]Jian Zhao, Chunxiang Cao，et al.,Spatial and temporal dynamic analysis of Land use / cover change in arid areas: A typical example in Zhungeer, Journal of arid land resources and environment, 2013, 27(004): 99-105. (in Chinese)(CSCD)
[57]Chunxiang Cao, Wei Chen, Guanghe Li, Huicong Jia, Wei Ji, Min Xu, Mengxu Gao, Xiliang Ni, Jian Zhao, Sheng Zheng, Rong Tian, Cheng Liu and Sha Li, The retrieval of shrub fractional cover based on a geometric-optical model in combination with linear spectral mixture analysis[J]. Canadian Journal of Remote Sensing, 2011, 37(4):1-11.(SCI)
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[55]Huicong Jia, Jingai Wang，Donghua Pan，Chunxiang Cao.Maize Drought Disaster Risk Assessment Based on EPIC Model:A Case Study of Maize Region in Northern China [J].ACTA GEOGRAPHICA SINICA, 2011, 66(5): 643-652. (in Chinese)(CSCD)
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[53]Shaobo Zhong, Zhanhui Sun, Quanyi Huang, Chunxiang Cao. A framework for geographical surveillance of disease in China [J].International Journal of Disaster Resilience in the Built Environment, 2011, 2(3): 256-267.
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[49] Wei Ji, Xincai Wu, Chunxiang Cao. Research on dynamic catalog tree for land resources datacenter[J]. Bulletin of surveying,2012,02:74-76+102. (InChinese) [CSCD]
[48] Wei Ji, Xincai Wu, Chunxiang Cao et al.,A dynamic modeling technology of spatial analysis model[J]. Science of Surveying and Mapping,2012,04:49-51. (InChinese) [CSCD]
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[45]Rong Tian, Chuxiang Caoet al., Changes and Driving Factors of Plateau Wetlands in Maduo County[J]. WETLAND SCIENCE，2011，9（1）：61-68. (InChinese) (CSCD)
[44]Sheng Zheng, Xiang Zhao，Hao Zhang，Qisheng He，Chunxiang Cao，Liangfu Chen. Atmospheric correction on CCD data of HJ-1 satellite and analysis of its effect [J]. Journal of Remote Sensing, 2011, 15(4): 709-721. (In Chinese)(CSCD)
[43]Shouxun Yan，Xiaobo Wu，Chaoxian Zhou，Chaohui Liu，Yongcheng Zhuang，Chunxiang Cao et al.,Advances in remote sensing and spectroscopy and the use of remote sensing in geological and mineral exploration of practice[J].Advances in earth science, 2011, 26(1): P624-627.(In Chinese)(CSCD)
[42]LI G P, Cao C X. Development of environmental monitoring satellite systems in China[J]. China Earth Sci, 2010, 53:1-7,doi: 10.1007/s11430-010-4141-7.(SCI)
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[39]Min Xu，Chunxiang Cao et al., Spacetime Cluster Detection of Pandemic H1N1 Influenza A U sing GIS [J].Journal of Geoinformation Science, 2010, 12(5):707-712. (In Chinese)(CSCD)
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[26]Jianping Guo, Huadong Xiao, Yong Xue, Huizheng Che, Xiaoye Zhang, Chunxiang Cao, Jie Guang, Hao Zhang. A New Method to Retrieve Aerosol Optical Thickness from Satellite Images on a Parallel System[J]. Particuology, 2009, 7(5), 392-398. (SCI)
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发表会议论文
[53]Haifang Guo, Min Xu, Binbin, He, CAO Chunxiang. Analysis of land use change in the urbanization. EOBAR 2016, Beijing, China. (EI)
[52]CAO Chunxiang, FANG Zhou, CHEN Wei, JIANG Houzhi. Risk prediction and analysis for SOD in world and China based on spatial information technology. EOBAR 2016, Beijing, China. (EI)
[51]Xuejun Wang, Yuxing Zhang, Enping Yan, Guosheng Huang, Chunxiang Cao, Xiliang Ni, DEFORESTATION AREA ESTIMATION IN CHINA BASED ON LANDSAT DATA, IGARSS 2014.(EI)
[50]Zaichun Zhu, Chunxiang Cao, Ranga Myneni, Xiliang Ni, Min Xu, Yunfei Xu. Global Data Sets of LAI3g and FPAR3g Derived from GIMMS NDVI3g for the Period 1981 to 2011. The Third International Workshop on Diagnosis of Environmental Health by Remote Sensing, 2013.
[49]Xiliang Ni, Chunxiang Cao, Ranga Myneni, Zaichun Zhu, Min Xu, Yunfei Xu. Allometric Scaling and Resource Limitations (ASRL) Model Based Estimation of Forest Biomass over China. The Third International Workshop on Diagnosis of Environmental Health by Remote Sensing, 2013.
[48]M. Xu, C.X. Cao, et al, THE USE OF ENVIRONMENTAL VARIABLES TO PREDICT CHOLERA HAZARD, IGARSS 2013. (EI, Accepted)J. Zhao, C.X. Cao, et al, HUMAN SETTLEMENT SUITABILITY ASSESSMENT CONSIDERING CLIMATE AND DEM, IGARSS 2013. (EI, Oral)
[47]S.Zheng, C.X. Cao, et al. LAND SURFACE TEMPERATURE RETRIEVAL USING HJ-1B/IRS DATA AND ANALYSIS OF ITS EFFECT, IGARSS 2013. (EI, Oral))
[46]W. Chen, T. Sakai, C.X. Cao, et al. EXTRACTION OF BURNED FOREST AREA IN THE GREATER HINGGAN MOUNTAIN OF CHINA BASED ON LANDSAT TM DATA, IGARSS 2013. (EI, Oral))
[45]H.B. Xiang, C.X. Cao, et al. THE AUTOMATIC TREE DETECTION AND DELINEATION FROM AIRBORNE LIDAR, IGARSS 2013. (EI, Accepted)
[44]C.Liu, C.X. Cao, et al. A STUDY ON SITE QUALITY EVALUATION OF LARIX GMELINI IN ANSHAN CITY BASED ON SITE INDEX, IGARSS 2013. (EI, Accepted)
[43]D. Liu, C.X. Cao, et al. MONITORING THE DYNAMICS OF FOREST AREA BASED ON TM IMAGES, IGARSS 2013. (EI, Accepted)
[42]H.J. Tian, C.X. Cao, et al. TEMPORAL CHANGING ANALYSIS OF FOREST CROWN CLOSURE OF ANSHAN CITY BASED ON SPECTRAL MIXTURE ANALYSIS, IGARSS 2013. (EI, Accepted)
[41]A. SAOKARN, C.X. Cao, et al. URBAN AREA TEMPORAL CHANGING ANALYSIS AND MODELING IN CHIANG MAI, THAILAND’, IGARSS 2013. (EI, Accepted)
[40]Chunxiang Cao, Guanghe Li, Sheng Zheng, Jinquan Cheng, Guangchun Lei, Kun Tian, Yongsheng Wu, Xu Xie, Min Xu, Wei Ji. Research on the environmental impact factors of Hand-Foot-Mouth Disease in Shenzhen, China using RS and GIS technologies.IGARSS, 2012. (EI, Oral))
[39]Mengya Wang, Chunxiang Cao, Jianhong Guo, Shilei Lu, Sheng Zheng, Min Xu, Huicong Jia, Yunfei Xu, Bo Xu, Yiheng Zheng. Research on Urban Heat Island Effect during Beijing Urbanization Process by Remote Sensing and Its Impact on Environmental Health.IGARSS, 2012. (EI, Oral)
[38]Wei Chen, Tetsuro Sakai, Chunxiang Cao, Kazuyuki Moriya, Lina Koyama. Detection of forest disturbance in the Greater Hinggan Mountain of China based on Landsat time-series data. IGARSS, 2012. (EI, Oral))
[37]Xiliang Ni, Sungho Choi, Yuli Shi, Chunxiang Cao, Ranga B. Myneni. Forest biomass estimation of Northeastern USA using GLAS and TM data.IGARSS, 2012. (EI, Oral)
[35]Sheng Zheng, Chunxiang Cao, Guanghe Li, Shilei Lu, Min Xu, Huicong Jia. Incidence prediction of communicable diseases after the Wenchuan earthquake using remote sensing.IGARSS, 2012. (EI, Oral)
[34]Haibing Xiang, Chunxiang Cao, Huicong Jia, Min Xu, Ranga B. Myneni. The analysis and study on the accuracy of dem retrieval by the ground lidar point cloud data extraction methods in mountain forest areas. IGARSS, 2012. (EI, Accepted)
[33]Cheng Liu, Chunxiang Cao,Tetsuro Sakai, Jianlong Zhang, Aiguo Ma, Wei Chen, Min Xu. Predicting the adaptability of sudden oak death in China using spatial information techology.IGARSS, 2012. (EI, Oral)
[32]Rong Tian, Chunxiang Cao, Guangchun Lei, Kun Tian, Jingnong Weng, Huicong Jia, Min Xu, Haibing Xiang.Health assessment of the water-level-fluctuation zone(WLFZ) in the Three Gorges area based on spatial information technology. IGARSS, 2012. (EI, Oral)
[31]Peera Yomwan, Chunxiang Cao, Preesan Rakwatin, Pakorn Apaphant, The risk analysis for infectious disease outbreaks in flood disaster based on spatial information technologies. IGARSS, 2012. (EI, Oral)
[30]Zhou Fang, Chunxiang Cao, Wanshou Jiang, Shilei Lu, Wei Ji, Min Xu. Multi-spectral Image Inter-band Registration Technology Research.IGARSS, 2012. (EI, Accepted)
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[2]Shaobo Zhong, Yong Xue, Cunxiang Cao, Jianqin Wang, Jianping Guo, Yanguang Wang, Yincui Hu, Ying Luo, Guoyin Cai, and Jiakui Tang. Explore Disease Mapping of Hepatitis B Using Geostatistical Analysis Techniques[J]. Lecture Notes in Computer Science, 2005, Vol.3516，pp.464-471.（ISTP）
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