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Li T.,Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions | Li T.,Henan University | Zhang S.,Chinese Academy of Sciences
International Conference on Geoinformatics | Year: 2013

Gully erosion of tillage land in northeast China cause mass land degradation and threaten the safety of grain production of China. The relationship between the spatial distribution of gullies and topographic factors, such as slope angle, aspect, slope form, SPI and TWI, as well as land use and lithology are discussed in the Keshan County of Heilongjiang province. The topographic factors are derived from Digital Elevation Model, and landuse as well as gully distribution data were interpreted from satellite images and field survey. Basis on mapped controlling factors, single factor analysis was taken to recognize high risk region of gully erosion. The result of overlay analysis showed that nearly 80% of gullies occurred in farmland and concave slope elements; high slope angle and SPI value are identified as the high gully initiation regions due to the enhancement of runoff convergence. The two patterns of gully erosion were identified via the overlay analysis of different substratum. Based on the analysis, two processes of gully erosion were identified. © 2013 IEEE. Source


Wang S.,Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions | Wang S.,Henan University | Wang S.,Zhengzhou Tourism College
International Conference on Geoinformatics | Year: 2013

The proper protection and utilization of ancient passes in a scientific way are based on the objective evaluation of their comprehensive values. With the data obtained through field researches and interviews with experts, the ancient passes tourist resources of Shanxi Province are analyzed and evaluated by adopting the analytic hierarchy process (AHP) and establishing a fuzzy mathematics comprehensive evaluation model. Thus, the decision-making references for further integrated development and utilization of the ancient passes are providedin this document. © 2013 IEEE. Source


Zhai S.,Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions | Zhai S.,Henan University | Song G.,Zhejiang University
International Conference on Geoinformatics | Year: 2013

This paper examines the causal relationship among economic growth, energy structure, R&D investment and carbon emission in China by using autoregressive distributed lag bounds testing approach of cointegration during the period of 1990-2011. In order to examine this linkage, theauthors use the two-step procedures. Firstly, theauthors conducted the unit root tests to measure whether the single integrated of time series is not more than 1. Secondly, theauthors explore the long-run relationships between the variables by using ARDL bounds testing approach complemented by Johansen-Juselius maximum likelihood procedure in a multivariate framework. The findings are as follows:when carbon emissions and economic growth, respectively, are the dependent variable, the other independent variables show the long-term stability cointegration relationship of the dependent variable. Whether in the short-run or long-run relationship, the impact of economic growth and R&D investment on carbon emission is not statistically significant. In the long term and short term relationships, carbon emissions have a positive impact on the economic growth. However, energy structure has a negative impact on the economic growth. The decrease in energy structure will cause carbon emissions reduction and boost economic growth in both the long-run and short-run period. Therefore, China's government should give more attention to the optimization of energy structure and make a reasonable and feasible energy saving policy. © 2013 IEEE. Source


Cui C.,Henan University | Han Z.,Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions
ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services | Year: 2015

Identifying spatial patterns of geographic entities such as retail stores is important in city for understanding how they behave. The pattern formed by the distribution of points can be measured by some quantitative methods. In Big Data era, the data sets for spatial patterns analysis are various including traditional street network data and points of interest (POIs) data in LBS (Location based services) application. This paper analyzed the spatial pattern of retail stores and its correlations with street centrality using POIs data in Zhengzhou, China. Firstly, the paper provided an exploratory analysis of spatial patterns using the centrographic methods including Standard Deviational Ellipse and Average Nearest Neighbor. Secondly, the paper uncovered the spatial distribution of retail stores using the kernel density estimation (KDE). Finally, the paper calculated the street centrality of Zhengzhou using three centrality assessment indexes and converted all nodes centrality index values to raster pixel using KDE for correlation analysis. Results show that the retail stores are clustering pattern and mainly elongated along the west-east direction. The street centralities are correlated with the retail store location in Zhengzhou, and there is a different level of correlation between them. The paper reveals that the spatial pattern analysis and street centralities index are valuable in location analysis or urban planning. © 2015 IEEE. Source


Wang S.,Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions | Wang S.,Henan University | Wang S.,Zhengzhou Tourism College
International Conference on Geoinformatics | Year: 2013

Improving the efficacy of space utilization has been listed as the primary task of land space development in the report to the Eighteenth National Congress of the Communist Party of China. But with the booming development of the tourism industry, tourism land has shown the trend of rapid expansion. Therefore, the efficacious utility of the land for scenic area is The inevitable tendency of tourism development. Gulou District was chosen as the study object in this paper, and the land use of the scenic area within the district was evaluated by using fuzzy mathematical model and the data obtained by field survey and expert interviews. The results show that the lower efficacy of the current land use of the scenic area within Gulou District leaves a huge space to improve the situation. © 2013 IEEE. Source

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