Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology

Nanjing, China

Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology

Nanjing, China
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Mao J.,Nanjing University | Wang S.,Hohai University | Ni J.,Nanjing University | Xi C.,Nanjing University | And 2 more authors.
ISPRS International Journal of Geo-Information | Year: 2017

Flood disasters from dam breaks cause serious loss of human life and immense damage to infrastructure and economic stability. The application of Geographic Information System technology integrated with hydrological modeling for mapping flood-inundated areas and depth can play a momentous role in further minimizing the risk and possible damage. In the present study, base terrain data, hydrological data, and dam engineering data were integrated using the MIKE-21 dam-break model to analyze flood routing under the most serious scenarios. A deterministic approach was used to calculate the hydraulic elements of dam breakage during a flood. Additionally, the hydraulic elements generated by the MIKE-21 dam-break model (a modelling system for estuaries, coastal waters, and seas)-including flood depth, submersion time, and flow direction-were integrated with a digital elevation model of the site downstream of the dam in order to map the possible affected areas. Using an empirical model in addition to using the superimposition of dam flood calculation results and the social and economic survey data, dam damage assessment was implemented. In accordance with a relevant standard, the flood risk mapping guidelines and a set of client/server structures were developed for a management system for dam-break hazard mapping of the Foziling reservoir. The simulation data and the study results can provide a scientific basis for emergency management of the reservoir and provide a socio-economic framework for downstream areas. © 2017 by the authors. Licensee MDPI, Basel, Switzerland.

Huang H.,Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology | Huang H.,Nanjing University | Ni J.,Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology | Ni J.,Nanjing University | And 9 more authors.
Applied Sciences | Year: 2016

Landslides are the most frequent type of natural disaster, and they bring about large-scale damage and are a threat to human lives and infrastructure; therefore, the ability to conduct real-time monitoring and early warning is important. In this study, a Web3DGIS (Web3D geographic information systems) system for monitoring and forecasting landslides was developed using the Danjiangkou Reservoir area as a case study. The development of this technique involved system construction, functional design, organizing and managing multi-source spatial data, and implementing a forecasting plan and landslide-forecasting model. By integrating sensor technologies, spatial information technologies, 3D visualization technologies, and a landslide-forecasting model, the results of this study provide a tool for real-time monitoring at potential landslide sites. When relevant data from these sites reach threshold values, the model automatically initiates forecasting procedures, and sends information to disaster prevention sectors for emergency management. © 2016 by the authors.

Pu Y.,Nanjing University | Pu Y.,Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology | Song X.,Nanjing University | Song X.,Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology | Ge Y.,Hohai University
International Conference on Geoinformatics | Year: 2016

Identifying the functionalities of urban regions helps policy makers to improve resource management and urban planning. In this paper, we propose an improved framework to discover urban functional regions with GPS trajectories and POIs. We construct a spatial proximity model (SPM) by incorporating spatial clustering and co-location patterns into the traditional independent model, and then employ resilient back propagation (RBP) algorithm to solve it. 22 variables are included in the SPM model, which are 6 of GPS at six different periods in 24 hours, 5 of POIs, and 11 spatial lag variables of each region. We evaluate this framework with over 100,000 GPS trajectories and 46,000 POIs in Hefei city, China. The overall training and test accuracies are up to 90%. The concentric structure of the study area can be visually discovered from the map identified by SPM. Moran's I and BW joint count statistics are further applied to verify the significance of spatial clustering and co-location patterns. © 2016 IEEE.

Ni J.,Nanjing University | Ni J.,West Anhui University | Qian T.,Nanjing University | Xi C.,Nanjing University | And 3 more authors.
International Journal of Environmental Research and Public Health | Year: 2016

The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities. © 2016 by the authors; licensee MDPI, Basel, Switzerland.

Li F.,Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology | Peijun D.,Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology
Joint Urban Remote Sensing Event 2013, JURSE 2013 | Year: 2013

Over the past 30 years, urban development in China has been remarkable. Land development and consumption have been out of control and have kept expanding out of order, especially to marginal areas of some metropolises. Therefore, dynamic change monitoring of urban sprawl is necessary. Taking Jiangning District, Nanjing City as a research area, this paper demonstrates the dynamic change of urban sprawl by Landsat MSS/TM data. Furthermore, three-dimensional indicators are considered based on the actual situation of urban sprawl in Jiangning in order to better reflect the nature of sprawl. The result indicates that the trend of urban sprawl is significant. From 1979 to 1988, the phenomenon of disorder and scattered construction was obvious in Jiangning; from 1988 to 1997, sprawl is more significant in the process of suburbanization. Leapfrog development is significant; from 1997 to 2003, the land became fragmented, resulting in a broken landscape. © 2013 IEEE.

Shen D.,Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology | Shen D.,Nanjing University | Shen D.,Changjiang River Scientific Research Institute | Kuang Q.,Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology | And 5 more authors.
International Conference on Geoinformatics | Year: 2016

Flood damage assessment is an important part of assessing flood control in hydraulic engineering, flood risk mapping, and flood insurance claims. How to assess flood damage scientifically and accurately has been the emphasis and difficulty of flood disaster research. This article describes the present research status of flood damage loss assessments from three aspects: the disaster classification, the indicator system of assessing the loss of flood damage, and the method of assessing the loss of flood damage, and explores the current problems in the scale of assessment, the indicator system of assessment, the determination of the loss rate of hazard-affected bodies, as well as other aspects in current approach of assessing flood damage loss. In the end, the prospect for further research is made. © 2015 IEEE.

Ni J.,Nanjing University | Ni J.,West Anhui University | Wang J.,Nanjing University | Rui Y.,Nanjing University | And 3 more authors.
International Journal of Environmental Research and Public Health | Year: 2015

Civil administration departments require reliable measures of accessibility so that residential care facility shortage areas can be accurately identified. Building on previous research, this paper proposes an enhanced variable two-step floating catchment area (EV2SFCA) method that determines facility catchment sizes by dynamically summing the population around the facility until the facility-to-population ratio (FPR) is less than the FPR threshold (FPRT). To minimize the errors from the supply and demand catchments being mismatched, this paper proposes that the facility and population catchment areas must both contain the other location in calculating accessibility. A case study evaluating spatial accessibility to residential care facilities in Nanjing demonstrates that the proposed method is effective in accurately determining catchment sizes and identifying details in the variation of spatial accessibility. The proposed method can be easily applied to assess other public healthcare facilities, and can provide guidance to government departments on issues of spatial planning and identification of shortage and excess areas. © 2015, by the authors; licensee MDPI, Basel, Switzerland.

Song X.,Nanjing University | Pu Y.,Nanjing University | Pu Y.,Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology | Liu D.,Nanjing University | Feng Y.,Nanjing University
Cehui Xuebao/Acta Geodaetica et Cartographica Sinica | Year: 2015

Urban functional area is an important concept in urban planning. It is difficult to obtain regional functional properties by remote sensing techniques since land uses are not always directly observable even by the closest inspection. With the development of Internet and popularity of mobile positioning devices, a large volume of pedestrians' movement trajectories are available to the common. This paper applies machine learning method to discover urban functional areas implicit in the GPS data. The analytic framework is built on an idea that people's movement patterns and trip rules have a strong correlation with regions' functions. Gaussian Mixture Model (GMM) is applied to extract different functional clusters through iterative machine learning process. About 60 areas are therefore sampled to determine the specific functional areas for residential, commercial, governmental, educational and leisure area. The 6 functional areas are identified with the help of samples' temporal distributions. The preliminary results indicate that urban functional areas can be discriminated by integrating GPS movement trajectories with machine learning method, especially with large amount of data. This spatial data mining process is simple, applicable and easy to be carried out in the actual production. © 2015, SinoMaps Press. All right reserved.

Pu Y.,Nanjing University | Pu Y.,Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology | Han H.,Shandong University | Ge Y.,Hohai University | And 2 more authors.
Dili Xuebao/Acta Geographica Sinica | Year: 2016

Population migration flows between different regions are related to not only the origin- and destination- specific characteristics, but also to the migration flows to and from neighborhoods. Intuitively, changes in the characteristics of a single region will impact both inflows and outflows to and from other regions. In order to explore the spatial interaction mechanism driving the increasing population migration in China, this paper builds the spatial OD model of interprovincial migration flows based on the sixth national population census data and related social- economic data. The findings are as follows: (1) Migration flows show significant autocorrelation effects among origin and destination regions, which means that the migration behavior of migrants in some region is influenced by that of migrants in other places. The positive effects indicate the outflows from an origin or the inflows to a destination tend to cluster in a similar way. Simultaneously, the negative effects suggest the flows from the neighborhood of an origin to the neighborhood of a destination tend to disperse in a dissimilar way. (2) Multilateral effects of the regional economic and social factors through the spatial network system lead to the clustering migration flows across interrelated regions. Distance decay effect plays the most influential force in shaping the patterns of migration flows among all the factors and the negative spillover effect further aggravates the friction of distance. As for destinations, the influence of wage level and migration stocks is beyond that of GDP and the positive spillover effects of these factors enhance the attraction of neighborhood regions. The spillover effects of unemployment rate and college enrollment of higher education are significantly negative while the effect of population in a destination is not significant. As for origins, population and migration stocks lead to positive spillover effects on the neighborhoods while the effects of other factors are negative. (3) Changes in the regional characteristics will potentially lead to a series of events to the whole migration system, and the flows to and from the center of oscillation and its neighborhoods vibrate greatly compared with other regions. The simulation results of 5% GDP increase in Jiangsu province indicate that the outflows to other regions decrease while the inflows from all others increase to some different extent. Comparatively, the influence on the flows to and from the regions neighboring Jiangsu is significant while that of remote regions is much less, which cannot be explained by the traditional gravity model. © 2016, Science Press. All right reserved.

PubMed | Northwest Agriculture and Forestry University, U.S. Geological Survey and Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology
Type: | Journal: Scientific reports | Year: 2016

Over the past 100 years, human activity has greatly changed the rate of atmospheric N (nitrogen) deposition in terrestrial ecosystems, resulting in N saturation in some regions of the world. The contribution of N saturation to the global carbon budget remains uncertain due to the complicated nature of C-N (carbon-nitrogen) interactions and diverse geography. Although N deposition is included in most terrestrial ecosystem models, the effect of N saturation is frequently overlooked. In this study, the IBIS (Integrated BIosphere Simulator) was used to simulate the global-scale effects of N saturation during the period 1961-2009. The results of this model indicate that N saturation reduced global NPP (Net Primary Productivity) and NEP (Net Ecosystem Productivity) by 0.26 and 0.03 Pg C yr

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