DTP Scholarships at UNNC and IGSNRR

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.

This project will produce the most up-to-date assessment of flood risk and drought hazard across globally 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 Prof Tang Qiuhong (tangqh@igsnrr.ac.cn), Dr Simon Gosling (simon.gosling@nottingham.ac.uk) and Dr Meili Feng (meili.feng@nottingham.edu.cn), but formal applications should follow the instructions in ‘How to apply’ section. 

Data mining is one of the essential steps of the knowledge discovery process from given raw data sets, a very important interdisciplinary field of computer science. It targets to discover interesting hidden patterns in large data sets. Clustering is the task of discovering similar groups on the given raw data sets. Anomaly detection such as detection of outliers, change, or deviations may also be considered as a part of clustering techniques. This step generally used for identification of unusual or abnormal data records or errors, which can be interesting sometimes. In order to measure the similarities among the data-items, distance metric plays a very important role. Thus in our proposed research we plan to propose efficient and effective algorithmic approaches for clustering using metrics of Euclidean distance, taxicab distance, and Chebychev distance in the clustering process, and their pros and cons.

In reality, geographical data or social network data also possess some graph structures, which may represents similarities between data, interactions between data, or their relationships. Thus  the clustering process needs to take such factors into consideration, and the clustering approaches need to be adjusted to adapt to such constraints. And among our above proposed clustering approaches, we expect some evolutionary intelligent approaches need to be applied to obtain much better clustering results. Moreover, we expect to conduct extensive experimentation on our proposed approaches.
Informal inquiries may be addressed to Dr Sheung Hung Poon (Sheung-Hung.Poon@nottingham.edu.cn) and Prof Chenghu Zhou (zhouch@lreis.ac.cn), but formal applications should follow the instructions in ‘How to apply’ section. 

How to evaluate the risks of urban water disasters and further to mitigate them is one key topic for the urban stormwater management, which is also the foremost challenge for the sustainable urban developments. The Chinese government proposed the concept of “Sponge City” in 2013 to handle the aggravating urban water disasters (i.e. urban surface water floods/waterlogging) over China. Over the last six years, many measures and technologies have been developing for guiding the designs and implementation of the program in the 30 pilot cities. However, there still have many challenges that prevent the positive feedback of the “Sponge City” program, questioning its functions and effects. This project will focus on two major dimensions on (i) solve the key hydrology-related issues (e.g. estimation of proper rainfall threshold in various magnitude of precipitations) for guiding the design of the “Sponge City” program and (ii) evaluate the effects of the “Sponge City” program by considering the trade-off between the investment and its potential benefits. 
Informal inquiries may be addressed to Dr Faith Chan (Faith.Chan@nottingham.edu.cn) and Prof Yanfang SANG (sangyf@igsnrr.ac.cn), but formal applications should follow the instructions in ‘How to apply’ section. 

Floods, from snow melting, storms, or both, can cause severe disasters to human being. Under the threat of climate change, the probabilities of floods as one of the extreme events are getting higher. It becomes an immense task to do an accurate prediction to floods to save life and reduce the impacts. Flood predictions require data to build the flood prediction model for determining model parameters, validating model results and correcting predicted results real-timely. Flood predictions thus pose a bigger challenge when data are scarce.This project will focus on three major dimensions on: (i) How to acquire data needed for flood predictions via satellite, radar, Unmanned Airborne Systems, in-situ observations and modelling, (ii) How to increase the accuracy of flood predictions for data scarce basins, and (iii) How to investigate the importance of flood warning under climate change circumstances.
Informal inquiries may be addressed to Dr Faith Chan (Faith.Chan@nottingham.edu.cn) and Prof Suxia LIU (liusx@igsnrr.ac.cn), but formal applications should follow the instructions in ‘How to apply’ section. 

As the aging population increase, most Chinese cities face new challenges of effective and efficient elderly care services. Constrained by social, economic and cultural backgrounds of China, it is dispensable to develop innovative concepts and service patterns to achieve China’s social development goal and ensure the welfare of the elderly population. This project will study the elderly care service issue from an interdisciplinary perspective. It is anticipated to investigate and evaluate the theories and practice of elderly care services, and propose innovative ideas on elderly care service, in order to provide sustainable solutions for the aging cities.
Participants of the project will conduct intensive user research, modelling and data analysis for older people in different Chinese cities. They will analyse people’s needs for formal and informal care service by means of user-interview and survey methods, study the geographical distribution of elderly care resources, and explore the opportunities for innovation for elderly care services. The project will make innovations in urban elderly care services through the organization, process design, and resource allocation of elderly care services. Applicants are anticipated to have a strong background in geography, planning, or industrial design, and have good skills in user research, field survey, and GIS analysis. Research experience in the field of elderly care service is desirable.
Informal inquiries may be addressed to Dr Ali CHESHMEHZANGI (Ali.Cheshmehzangi@nottingham.edu.cn) and Professor Xiaolu GAO (gaoxl@igsnrr.ac.cn), but formal applications should follow the instructions in ‘How to apply’ section. 

New-type urbanization and eco-city constructions have been widely promoted in China since 2014. To optimize urban planning, mitigate the mismatch between urban scale hierarchy and urban functions, improve resource utilization efficiency and eco-efficiency, enhance the level of urban ecology and urban management and services, perfect the institutional mechanisms are of great importance to promote healthy development of ecological cities. At present, many cities in China put forward the goal of building ecological cities and communities, however, the research on integrated ecological management mechanism is relatively underexplored. 
In this proposed project, there are three major dimensions: (1) clarify the characteristics of the lifestyles and consumption patterns in typical eco-cities, and further quantifies their impacts on ecological environment; (2) quantify the resource utilization efficiency in selected domestic and foreign cities with typical urban ecological management modes, and estimates the impacts of different modes on urban ecological environment; (3) estimate the urban eco-efficiency and environmental efficiency and identify their key limiting factors, and conduct systematic research from the perspectives of urban planning, industrial structure, resource policy, ecological and environmental protection measures and standards. All the research work will be summarized to refine urban ecological adaptive management modes, construct a set of method system for urban ecology adaptive management that meets the development needs of new-type urbanization, to provide scientific support for ecological community construction and integrated urban ecological management.
Informal inquiries may be addressed to  Dr Ali CHESHMEHZANGI (Ali.Cheshmehzangi@nottingham.edu.cn) and Prof Xiangzheng Deng (dengxz@lreis.ac.cn), but formal applications should follow the instructions in ‘How to apply’ section. 

The Belt and Road Initiative (BRI) started in 2013 that addressed by President Xi and enhanced multi-national partnerships in trading, education, technological development, logistics and transport, etc., will escalate the regional and global economy in the coming decades. Whilst, it is expected to face challenges on water and other environmental issues through the projected rapid developments, especially for water issues as most of the BRI countries that have been involved in Asia are under water scarcity and water risk (by drought and floods). The big question here is to investigate the sustainable ways to maintain adequate water resources and balancing with social-economic and developmental pressure in the BRI. This project will request candidate to particular focus on the regions - NW China, Mongolia and C Asia of some major economic corridors.
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 the instructions in ‘How to apply’ section. 

One of the key issue inhibiting the understanding of quaternary glaciations in the Tibetan Plateau is the lack of detailed knowledge of paleo glacier extent. Geomorphic mapping only provides glacier extent reconstruction for area with well-preserved glacial landforms, and paleo glacier extent derived from complicate numeric model forced by climate has large uncertainties, especially for regional reconstruction. The proposed project aims to develop an approach to combine geomorphic mapping and simplified numeric modelling for regional reconstruction of glacier extent and ice thickness distribution. The approach will be applied to the glaciation reconstruction in the eastern Hengduan Mountain, where has been significantly glaciated during the Quaternary. The results will largely improve our understanding of the glaciation pattern and paleo climate of the area and allow a correlation of local glaciation with other regions.
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. 

Rivers are self-adjusting systems and yet their self-adjusting mechanism has remained unclear. Over the last century, rivers have adjusted their morphology dramatically in many parts of the world due to the effects of intensive human activities and climate change. An understanding of the way by which rivers have responded to human activities and climate change is helpful not only for uncovering river self-adjusting mechanism but also for making plans on conserving or restoring river eco-systems. 
Focusing on rivers in a typical geographical region, this project will perform a detailed investigation of the characteristics of rive morphological change using long-term field measurements and/or satellite observations and then identify the key factors controlling the characteristics. Finally, a physical model will be developed to explain the self-adjusting mechanism of the rivers focused. 
Informal inquiries may be addressed to Dr Tengwen Long (Tengwen.Long@nottingham.edu.cn) and Prof He Qing Huang (huanghq@igsnrr.ac.cn), but formal applications should follow the instructions in ‘How to apply’ section. 

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 the instructions in ‘How to apply’ section. 

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 the instructions in ‘How to apply’ section. 

People have had close relationships with animals throughout history. Wildlife interactions (observing, feeding, touching, photographing or otherwise experiencing wild animals) occur in a wide variety of settings worldwide especially in China. Wildlife tourism involves an experience with non-domesticated animals, either in their natural habitat or in captivity. Meanwhile, wildlife tourism is regarded as a minimum impact activity and wildlife viewing is described as a non-consumptive use of wildlife. The research on wildlife tourism supply focuses on the development of wildlife tourism products and related industries. Its purpose is to provide satisfactory wildlife tourism experience and the coordinated development of regional tourism. Sustainable development of tourism destination is the core content and ultimate goal of wildlife tourism research. Tourism, however, can have both positive and negative effects upon wildlife.
Thus far, there is a lack of comprehensive quantitative studies aiming to understand how this multitude of factors and particularly natural resource, environment and market influence wildlife tourism and how these factors are related to wildlife tourism development. This project will focus on its influence on wildlife tourism development and its mechanism from three aspects of natural resources, environment and market. The purpose of this study is to make natural resources, environment and market better promote the development of wildlife tourism, better protect wildlife, and make wildlife tourism development sustainable.  
Informal inquiries may be addressed to Dr. Odette PARAMOR (Odette.PARAMOR@nottingham.edu.cn) and Prof ZHONG Linsheng (zhongls@igsnrr.ac.cn), but formal applications should follow the instructions in ‘How to apply’ section.

With the rapid urbanization and industrialization, urban-rural transformation development causes various socio-economic and environmental issues in the fringe of metropolis, the so-called suburbs. Therefore, how to realize the sustainable development of suburbs is not only a significant challenge of being the safeguard of integration between urban and rural areas, but also a huge problem to be solved in the current geography research. The student in this project is expected to propose a planning strategy to optimise the sustainability of development in a Chinese suburb area using spatio-temporal analyses on socio-economic factors as well as environmental conditions from the perspective of multi-disciplinary interaction.     
Informal inquiries may be addressed to Dr Ali Cheshmehzangi (Ali.Cheshmehzangi@nottingham.edu.cn) and Prof Hualou LONG (longhl@igsnrr.ac.cn), but formal applications should follow the instructions in ‘How to apply’ section. 

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 the instructions in ‘How to apply’ section. 

The big Earth data depends on different acquisition methods, such as earth observation, ground monitoring, deep exploration, simulation calculation, real-time activities of people, voluntary collection and so on. It comes from different application purposes, scenarios, standards and processing methods. In this context, the biggest challenge of the integration, sharing and mining of big Earth data is the heterogeneity of data semantics. The state-of-art semantics, ontology, linked data, knowledge graph and others provide a basis for solving the problem of semantic heterogeneity of geospatial data.

Potential topics include (but are not limited to) the following: (optional, but recommended)

• Geospatial semantic mining on ubiquitious network
• Geospatial semantic reasoning and information retrieval
• Geospaital ontology alignment, fusion and integration
• Crowdsourcing or volunteer geospation ontology construction
• Geospatial data ontology and applications 
• Geospatial linked data 
• Geospaital knowledge graph
• Geospatial data, models and computation sharing

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