联合培养博士生项目由宁波诺丁汉大学每年提供若干博士生招生指标，本年度招生指标5-8个。由中科院地理资源所与宁波诺丁汉大学导师共同指导，参与该项目的博士生将享受来自地理资源所与宁波诺丁汉大学的双重优质师资和完善的科研设备设施，获得丰厚奖学金，顺利完成项目的博士生将获得由英国诺丁汉大学颁发的学位证书。

　　具体招生方向和导师见下面的详细说明，招生截止日期为2019年6月14日。各位有意向的同学请与相关导师联系沟通。 

　　详细招生信息也可以在下面网站查阅：https://www.nottingham.edu.cn/en/graduateschool/phd-scholarships/19053dtpbj-2019.aspx

　　1. Investigation of the impacts on water disaster risk related (drought and floods) under the implications of Belt and Road Initiative: The Case of NW China and C Asia 

　　IGSNRR supervisor: Professor Juanle WANG 

　　UNNC supervisors: Dr Faith CHAN (School of Geographical Sciences) & Dr David O’BRIEN (School of International Studies)  

　　China’s Belt and Road Initiative (BRI) is potentially the largest infrastructure development scheme in our lifetime, with an estimated cost of over four trillion US dollars. The BRI has no geographic boundaries, and currently the economic corridors in the BRI connects 65 countries through both land and marine routes, which enhances various types of large-scale road and sea logistics, developments and trades, cross-boundary high-speed railway and trans-national road networks construction projects, boosting multi-national trade and energy resource investments between China and the BRI countries.  

　　The BRI has critical transboundary implications for water resources that need to be considered, but the impacts of water extremes (drought and floods) have been occurred along the BRI countries and caused substantial socio-economic losses and political issues, for example in the NW China and Central Asia  

　　In this proposed project, there are three major dimensions:  

　　(1) Using the geographical information system (GIS) and remote sensing techniques to construct the potential impacts to water resources (and biodiversity hotspots, etc.) on the locations along the BRI economic corridors, thus we can understand a better strategy to manage the transboundary ecological conservation and water resources management; (2) Using the qualitative methods (e.g. textural analyses) to investigate on the current and previous water resources management (especially focusing on water extremes) in the case of China-Central Asia-West Asia Corridor; 

　　(3) Using big data analysis and evaluation method to find the high-risk regions and influenced factors, provide disaster risk reduction data, information and knowledge products, and propose related solutions for the policy makers in regional or international levels. 

　　Informal inquiries may be addressed to Dr Faith Chan (faith.chan@nottingham.edu.cn) and Prof Juanle Wang (wangjl@igsnrr.ac.cn), but formal applications should follow instructions in the ‘How to apply’ section below.
2. Climate change impacts on hydrological extremes in China.  

　　IGSNRR supervisor: Professor Qiuhong TANG 

　　UNNC supervisor: Dr Meili FENG (School of Geographical Sciences) 

　　UNUK supervisor: Dr Simon GOSLING (School of Geography) 

　　This project will produce the most up-to-date assessment of flood risk and drought hazard across China under climate change scenarios for the 21st century. The project will analyse the latest hydrological model simulations from several models participating in the third phase of the Intersectoral Impact Model Intercomparison Project (ISIMIP3), run with climate change projections from the 6th Coupled Model Intercomparison Project (CMIP6). Changes in floods and droughts will be quantified under different greenhouse gas emissions scenarios, and the confidence in projections will be assessed by accounting for the emissions and model uncertainties.  

　　Informal inquiries may be addressed to Dr Meili Feng (meili.feng@nottingham.edu.cn) and Prof Tang Qiuhong (tangqh@igsnrr.ac.cn), but formal applications should follow instructions in the ‘How to apply’ section below. 

　　3. Patent distribution and industrial development in China: evolution, spatial coupling and transfer network 

　　IGSNRR supervisor: Professor Jiaoe WANG 

　　UNNC supervisor: Professor Cong CAO (Nottingham University Business School) 

　　Patents are one of the most important intellectual properties, and invention patents are especially key to the industrial upgrading and economic development in China today as innovation has driven the Chinese economy. Existing studies mainly focus on the relationship between patenting and economic development at various geographic scales, and there has been limited investigation into the coupling relationship between patenting and industrial development and upgrading.  

　　This proposed project will focus on two major dimensions:  

　　1) Invention patents and their consistency with industrial development in local and surrounding areas; and  

　　2) Evolution of interurban invention patent transfer network in China: spatial dependence and industrial coupling.  

　　We expect that the doctoral candidate will integrate the theories and methodologies of economic geography and innovation studies, and empirically examine the two dimensions mentioned above, and compare the values of patents in industrial upgrading of China and other countries. 

　　Informal inquiries may be addressed to Prof Cong Cao (Cong.Cao@nottingham.edu.cn) and Prof Jiaoe Wang (wangje@igsnrr.ac.cn), but formal applications should follow instructions in the ‘How to apply’ section below. 

　　4. Effect of Infrastructure Development on Market Integration in the Context of BRI 

　　IGSNRR supervisor: Professor Jiaoe WANG 

　　UNNC supervisor: Dr Marina GLUSHENKOVA (Nottingham University Business School) 

　　In 2013, Chinese President Xi Jinping announced the establishment of a new regional cooperation programme, officially named the “Belt and Road Initiative” (BRI). One of the main goals of the BRI is to deepen market integration through enhancing infrastructure and institutional linkages. Geographically, the BRI programme covers six land routes (China-Europe, China-Mongolia-Russia, China-Mediterranean Sea, China-Pakistan, Bangladesh-China-India-Burma, and China-South Asia) and two maritime roads (China-South Pacific and China-Europe). Infrastructure is the most significant component of the BRI, which directly affects connectivity of regions and is expected to be conducive to international trade and investment. Better connections and the lower trade costs may in turn trigger the process of economic convergence across countries. 

　　This project aims to analyse the importance of infrastructure development along the BRI for the economic integration of countries participating in the initiative by exploring the linkage between connectivity of countries and their economic performance. Our goal is to study the development of transport infrastructure systems at various scales, including the inter-state, national and sub-national levels, evaluate the effects of urban accessibility and connectivity along BRI, and examine to what extent the increasing physical and soft connectivity influences the society and economy. 

　　Informal inquiries may be addressed to Dr Marina Glushenkova (marina.glushenkova@nottingham.edu.cn) and Prof Jiaoe Wang (wangje@igsnrr.ac.cn), but formal applications should follow instructions in the ‘How to apply’ section below. 

　　5. Impacts of High-Speed Railway Network on Economic Development of Chinese regions 

　　IGSNRR supervisor: Professor Jiaoe WANG 

　　UNNC supervisor: Dr Marina GLUSHENKOVA (Nottingham University Business School) 

　　China’s high-speed rail (HSR) network is known to be the largest in the world. Started in 2003, the construction of the HSR network has greatly improved the accessibility and connectivity of cities in China. However, its effects on peripheral cities or poverty areas are still unknown. This project aims to explore the impact of HSR construction on regional growth, labour migration and income inequality in peripheral areas of China. Moreover, it will study the role of the HSR network in the domestic market integration process, and the formation of regional economic clusters. We intend to provide some answers to the following questions: What are the effects of the HSR construction on development of peripheral regions in China? Do China’s domestic markets become more integrated over time? How is this process affected by the construction of the HSR network? Do Chinese regions form income and/or price convergence clubs? If yes, what is the role of HSR network in explaining these?  

　　Informal inquiries may be addressed to Dr Marina Glushenkova (marina.glushenkova@nottingham.edu.cn) and Prof Jiaoe Wang (wangje@igsnrr.ac.cn), but formal applications should follow instructions in the ‘How to apply’ section below. 

　　6. 4D data visualisation-based water resource management for sustainable development 

　　IGSNRR supervisor:  Professor Yi LUO 

　　UNNC supervisor: Dr Ying WENG (School of Computer Sciences) 

　　Management of water resources is becoming increasingly more challenging due to the demands of a growing population and the complexity of the water management infrastructure. Accordingly, there is an ever increasing need for water providers and public authorities to be able to critically evaluate, assess and monitor the status of water resources to enable more effective decision making. One method of addressing this need is to use data visualisation techniques which consider the spatio-temporal availability of the resource. 

　　This project will focus on the application of advanced spatio-temporal data mining and visualization techniques with predictive analytics based on statistical and logical inference to create 4D representations in response to temporal changes in water process enabling continuous water resource monitoring and optimisation. 

　　Informal inquiries may be addressed to Dr Ying Weng (ying.weng@nottingham.edu.cn) and Prof Yi Luo (luoyi@igsnrr.ac.cn), but formal applications should follow instructions in the ‘How to apply’ section below. 

　　7. Current and historic air quality mapping in China  

　　IGSNRR supervisor:  Prof Baozhang CHEN 

　　UNNC supervisor: Dr Nicholas HAMM (School of Geographical Sciences) 

　　Air quality is a hot topic of widespread concern in China.  Maps of air pollutant concentration are important for monitoring the situation, for identifying the relationship with emissions and for supporting studies in epidemiology and public health.   Models for air quality are typically process-based (e.g., atmospheric chemistry models that track emissions transport, atmospheric chemical reactions, chemical decomposition and deposition) or statistical (e.g., land-use regression, based on empirical relationships between human and environmental covariates and monitored values) or some combination of the two.  Epidemiological studies of chronic disease require historic maps for the last 10 to 20 years and some papers have already been published on this topic.   However, both process-based and statistical models are limited by data quality issues including currency, accuracy and missing values.   This PhD will focus on the development and evaluation of air quality maps for China based on models, satellites and in situ measurements.  Key issues to address are: development and quality assurance of an air quality database, including pre-2012 data, uncertainty evaluation of current and historic air quality maps, identification of the appropriate space-time resolution for analysis. 

　　Informal inquiries may be addressed to Dr Nicholas HAMM (nicholas.hamm@nottingham.edu.cn) and Prof Baozhang CHEN (baozhang.chen@igsnrr.ac.cn), but formal applications should follow instructions in the ‘How to apply’ section below. 

　　8.  Space-time analysis of remote sensing and in situ environmental data 

　　IGSNRR supervisor:  Prof Yong GE 

　　UNNC supervisor: Dr Nicholas HAMM (School of Geographical Sciences) 

　　For many applications it is important to have quantitative current and historic maps of the environment (e.g., land cover, urban land use, environmental and air pollution).   The historic extent range from the present day to the past 10-40 years.   Such datasets are needed for environmental monitoring and modelling in the context of land-use change, urban expansion and developments surrounding the Belt and Road initiative.  Environmental epidemiology is another application.   Data sources include remote sensing, in situ environmental monitoring networks, socio-economic data, social media and volunteered geographic information.  Core topics to be addressed in this PhD are: (a) identification of appropriate current and/or historic data, (b) integration and modelling of these big geoscience datasets using novel statistical and machine learning methods, (c) data sharing, (d) spatial-temporal scale and (e) spatial data quality and validation.   The exact direction and application will be decided in consultation with the successful candidate. 

　　Informal inquiries may be addressed to Dr Nicholas HAMM (nicholas.hamm@nottingham.edu.cn) and Prof Yong GE (gey@lreis.ac.cn), but formal applications should follow instructions in the ‘How to apply’ section below. 

　　9. Space-time modelling of poverty in China and surrounding countries 

　　IGSNRR supervisor:  Prof Yong GE 

　　UNNC supervisor: Dr Nicholas HAMM (School of Geographical Sciences) 

　　Poverty alleviation has been a major feature of Chinese policy over the past 40 years.  Nevertheless, by the end of 2012, China still had almost 100 million people concentrated in contiguous poverty-stricken regions.   Poverty shows a complex relationship with the wider geographic context – including the physical environment, natural resources and economic systems.  This geographic context further includes aspects of urbanization, infrastructure (e.g., roads and railways), education and food security.  Poverty shows a complex pattern in shape.  Hence spatial statistical analysis can support identification of the patterns of poverty as well as the relationship with the wider geographic context, both of which can vary in space and time.  This has the potential both to support the development of poverty alleviation policies as well as monitoring the effectiveness of those policies.   

　　This PhD will focus on:  

　　(1) Dynamic change information extraction by incorporating VGI and street view  

　　(2) Modelling the relationship between poverty and geographic context: spatial regression and machine learning 

　　(3) Fine scale mapping of poverty incidence and uncertainty analysis  

　　Informal inquiries may be addressed to Dr Nicholas HAMM (nicholas.hamm@nottingham.edu.cn) and Prof Yong GE (gey@lreis.ac.cn), but formal applications should follow instructions in the ‘How to apply’ section below. 

　　10. Analysis on the interaction between multiple spaces using geographic big data 

　　IGSNRR supervisor:  Prof Tao PEI 

　　UNNC supervisor: Dr Jun LU (Department of Architecture and the Built Environment) 

　　Traditional geographical analysis is implemented in geographical space. With the development and advancement of modern technologies of the internet, communication and transportation, all things are connected in new, different, and increasingly, complex ways and these connections may form different and new spaces, e.g. (1) The internet may create internet space and each website may have its own location and relationship with others; (2) Everyone may have their location in social space based on their communication with other individuals.  

　　The key issues of this research include: (1) how to define the basic geographical concepts of space, (2) how to analyse their spatial distribution, (3) evaluate if the basic laws of space are correct and (4) investigate the relationships between different types of space. For example, what is location and distance in social space and does the first law of geography still work?  

　　The research will focused on those issues regarding urban residents and POIs in geographical, social and transportation spaces. POIs, transportation and mobile phone data will be used in the research.  

　　Informal inquiries may be addressed to Dr Jun Lu (Jun.Lu@nottingham.edu.cn) and Prof Tao Pei (Peit@lreis.ac.cn), but formal applications should follow instructions in the ‘How to apply’ section below. 

　　11. Automated GIS-based approaches for mapping glacial landscapes  

　　IGSNRR supervisor: Prof. Cheng-Zhi QIN 

　　UNNC supervisors: Dr Ping FU (School of Geographical Sciences) 

　　Geomorphic mapping has been widely used for reconstructing the extent and dynamics of paleo ice, including ice sheets and mountain glaciers. Current approaches to geomorphic mapping typically involves the manual digitisation of glacial landform features from digital elevation models and images which largely depends on human visual interpretation and is a time-consuming process.  

　　The PhD project aims to develop an automated GIS-based approach to delineating the main types of glacial landforms using topographic and remotely-sensed data. The method will be applied to the Himalaya region to aid the reconstruction and analysis of the paleo ice extent and patterns in this region. This region is a key site for paleoglaciology, but lacks detailed and systematic mapping results. The results will be compared with paleoglaciological studies in the other regions of the Tibetan Plateau, allowing for a detailed examination of the variations of glaciation patterns across the plateau.    

　　Informal inquiries may be addressed to Dr Ping FU (ping.fu@nottingham.edu.cn) and Prof Cheng-Zhi QIN (qincz@lreis.ac.cn), but formal applications should follow the instructions in ‘How to apply’ section below.  

　　12. Application of the Planetary Boundary concept to the Greater Bay Area, China.  

　　IGSNRR supervisor: Prof Fenzhen SU 

　　UNNC supervisors: Dr Odette PARAMOR (School of Geographical Sciences) 

　　The concept of planetary boundaries was developed to, ‘outline a safe operating space for humanity that carries a low likelihood of harming the life support systems on Earth to such an extent that they no longer are able to support economic growth and human development’ (Rockstr？m et al., 2013). The concentration of human populations into cities, or city clusters, is placing those spaces under enormous social, economic and ecological pressure, in addition to affecting their resilience to environmental change or disasters.  

　　This PhD will focus on the application of the concept of Planetary Boundaries to the Greater Bay Area, China, and will focus on assessing the status of one of the following areas: (1) freshwater use, (2) land use change and its impact on food security, or (3) how the resilience or carrying capacity of the Greater Bay Area has changed since 1978.  

　　Rockstr？m, J., Steffen, W., Noone, K., Persson, ？., Chapin, F.S., Lambin, E.F., Lenton, T.M., Scheffer, M., Folke, C., Schellnhuber, H.J., Nykvist, B., De Wit, C.A., Hughes, T., Van Der Leeuw, S., Rodhe, H., S？rlin, S., Snyder, P.K., Costanza, R., Svedin, U., Falkenmark, M., Karlberg, L., Corell, R.W., Fabry, V.J., Hansen, J., Walker, B., Liverman, D., Richardson, K., Crutzen, P. and Foley, J.A. (2009) A safe operating space for humanity. Nature 461 (7263) 472 – 475   

　　Informal inquiries may be addressed to Dr. Odette PARAMOR (Odette.PARAMOR@nottingham.edu.cn) and Prof Fenzhen SU (sufz@lreis.ac.cn), but formal applications should follow the instructions in ‘How to apply’ section below. 

13. Optimise the Sustainability of Suburb Development based on Eco-service and socio-economic performance

   IGSNRR supervisor: Prof. Hualou LONG

　　UNNC supervisor: Dr. Yu-Ting TANG

     China has been experiencing rapid urban expansion, as a result, creating increasing areas in the middle of urban and rural transition, or so called suburb.  As environmental impacts of urbanisation have been felt in China, sustainable development and management of these suburb areas have been put on the governmental agenda.  The student in this project is expected to propose a planning strategy to optimise the sustainability of development in a Chinese suburb area using spatial-temporal analyses on social-economic factors as well as environmental conditions, including land cover and land use.     

  Informal inquiries may be addressed to Dr Yu-Ting TANG (Yu-Ting.Tang@nottingham.edu.cn) and Prof Huanlou LONG (longhl@igsnrr.ac.cn), but formal applications should follow the instructions in ‘How to apply’ section below.