Geo-Informatics in Resource Management and Sustainable Ecosystem

Economies of scale and economies of scope are two big business advantages for financial holding companies. This paper is based on the operating data of 8 domestic financial holding companies from the years 2007-2012. Analyzing the effect economies of scale have on the returns and costs of financial holding companies, and analyzing the effect of economies of scope in terms of fixed effect and random effect. Research shows that both economies of scale and economies of scope exist within domestic holding companies; the effect of economies of scale is much more profound in moderate-sized financial holding companies; whereas in large financial holding companies the effect of economies of scope is comparatively weaker. Thus, this paper believes that the government should actively promote the development of financial holding companies, and that financial holding companies should maintain appropriate scale management.

Recently, there stands an upsurge to construct smart city all over China. A higher demand is put forward to real-time and dynamic data. At present, city data is multi-source, inconsistent and hard to match in most region of China, which can’t meet the need of smart city construction. This paper focuses on the connotation and techniques of data resource management platform, which is oriented to data acquisition and integration. Based on systematic analysis of city data resource, we discussed the common features from four dimensions of time, space, user and theme, and proposed a multi-dimensional data model. Besides, we designed and implemented the data resource management platform. Key techniques, such as comprehensive data acquisition, data storage and dynamical update, fusion method for multi-source heterogeneous data, full-scale data encoding and spatial-temporal data warehouse, were described. The data resource management platform can provide a data support for comprehensively application and multi-dimensional decision analysis in smart city.

Based on multidimensional niche theory, the paper tried to explore the function of cities and interaction relations among urban agglomerations, so that to provide a new perspective realizing the sustainable development of urban agglomerations. Using the principal component analysis, urban ecological niche breadth model and urban ecological niche differentiation index model on 16 indicators for 10 cities in Northern Slope of Tianshan Mountains (NSTM), ecological niche breadth and differentiation characteristics of the urban agglomeration were measured and calculated. The results are as follows.1) Comprehensive urban niche breadth of primate city is bigger than most cities in NSTM. The polarization is obvious.2) Comprehensive differentiation index of urban niche breadth shows an increasing tendency. The regional development elements gather in regional central city, moreover, the accumulative effect is even enhancing. 3) In general, the niche differentiation index of economy and public service, equitable development and population increasing rises apparently, however, the infrastructure status declines.

Spatial heterogeneity exists widely in geographical space. We here suggest that spatial association mining should consider spatial variations when designing knowledge-discovering models and applying the models in geographical studies. A Quadtree-based framework was proposed to mine localized spatial associations. Unlike many other approaches, the novelty of this Quadtree-based frame is its suitability in finding strong spatial association rules that are valid in smaller areal patches or “hot spot” area rather than the whole region, and therefore provides domain experts an insight to explore further the associations among different geographical phenomena. The principle underlying the Quadtree-based algorithm is that it employs a Quadtree data structure to explore the multi-level nodes (each representing a patch at that level), recursively. This recursive process is used to check whether the explored nodes satisfy predefined criteria (including support and confidence threshold for association rules, and event density and minimum area for each node), denoting a strong association. Practical application in an ecology study proved that, compared to traditional global association mining, the proposed model and algorithm for mining localized association rules are more meaningful under spatially heterogeneous environment.

Complex network theory provides a powerful framework to statistically investigate the topology of complex system include both artificial systems and natural systems. We propose a method to construct a climate observation network with climate observation records from automatic weather stations (AWS) in different locations. A link between AWS represents the cross-correlation between them. Apply this method to the climate observation records from the city of Chengdu and find that AWS with edge connected are located very close to. And the area with dense AWS has a significantly higher correlation between AWS compared to the area with exiguous AWS. This work would be helpful for identifying the preferred strategy for location optimization problems / discovering similar observation stations associated with AWS or using this information to complete missing/error values.

Compared wth the traditional GIS, the Gloud GIS has many advantages in infrastructure management, such as improving the utilization rate of hardware and the high performance of services, which can solve the existing problems in construction of digital city. Thus the Gloud GIS is studied and implemented. The experimental results showed that the proposed scheme outperforms the traditional GIS methods not only in efficiency but also in accuracy.

To enhance the urban lake information management, this paper applied the remote sensing technique to timely acquire the lake area reduction and water quality deterioration information of urban lakes. The appropriate classification rules and retrieval model were selected to obtain the important information concerned by the lake management department, such as the lake boundary, land use classification, lake temperature and chlorophyll content based on the multi-source remote sensing images. We found that the remote sensing technique can detect the abnormal change of the urban lake and track the development trend consistently. It highly improves the lake survey efficiency and will also promote the sustainable development of the lake ecosystem.

This paper proposes a method by which scattered LIDAR point clouds are converted into a two-dimensional image and then building footprints are extracted through the image processing. Firstly point cloud grid is handled to generate georeferenced feature image, and then image threshold segmentation, morphological close operation, connectivity analysis and contour tracking method is used to obtain the final building footprints. Finally, based on the mapping relationship between georeferenced feature image and scattered point clouds, building outline points are obtained. Experimental result shows that this method could extract building footprints very well in plain area, but due to the adoption of single image segmentation method in the georeferenced feature image, it is not suitable for the building footprints extraction in mountainous area.

ArcGIS is a series of geographic information system (GIS) software that has been widely applied in many industries in people’s daily life. However, there are few applications in the ocean domain. This article discussed the basic concepts and methods of using ArcGIS to visualize ocean environment data and an experiment based on Hong Kong water quality monitoring stations data was conducted. The results show that ArcGIS can be very helpful and powerful when dealing with ocean environment data and it can make a significant contribution to the protection of the ocean ecological environment.

There is a strong and persistent demand amongst scientists, citizen scientists and the general public for hydrologic data such as NEXRAD imagery and stream gauge time-series. Despite this interest, basic analysis tools are available only through specialized scientific software that is accessible to a small cadre of users. Furthermore, hydrologic data, while highly available, has not been integrated in a single system and no system exists to facilitate collaboration for scientists, citizen scientists, and the general public. This paper presents the design of the Watershed Science Network which is a collaborative social network aimed at multiple user groups who are focused on hydrology and watershed science. More specifically, we present a lightweight system that can analyze large datasets quickly and efficiently, while allowing users to interact with one another and perform collaborative analysis. This online gathering spot will allow citizens to post photos of local conditions, data providers to post announcements to users, and field scientists to view station data in the field. Users of the system can subscribe to watersheds of interest and automatically receive updates of recent analysis, visualization, and discussion activity regarding the watershed.

This paper explored the rational construction land layout in Qi river ecological district of Hebi city so as to provide references for the construction land layout in other similar domestic area. We took the geographical information system software (ArcGIS) and statistical software (SPSS) as technical support. As research methods, combining Qualitative analysis and quantitative calculation, data analysis with graphical analysis were adopted in the study. The paper evaluated the suitability and the ecological sensitivity of the construction land in Qi River ecological area, then analyzed the evaluation results supported by ArcGIS, finally got the suitable part of construction land in the ecological region. According to research, rational layout of construction land in ecological region is not only relates to suitability evaluation but also sensitivity evaluation; There are strong correlations among ecological sensitivity and water system, land cover type, elevation, special value.

To obtain the damaged building information rapidly and accurately can provide support for the disaster-relief work after the earthquake, and it is also an important part of the evaluation of the earthquake disaster losses. The high-resolution remote sensing image and the satellite radar data are important technical means for the disaster monitoring, but the accuracy of the automatic extraction of information is subject to certain restrictions. However in recent years, the newly-presented LiDAR technology can provide the elevation information for ground targets, which can be applied to rapidly and accurately extract the earthquake disaster information under the circumstances that the remote-sensing image is absent before the earthquake. Adopting the LiDAR data and remote sensing data in the Yushu disaster area, the damaged building information after the earthquake is automatically extracted through the Arcmap collection category samples and by using the object-oriented SVM classification, the overall accuracy can reach 80.96% in the research.

Virtual Globe technology has become a cutting-edge technology of geographic information industry in recent years. In view of the touch operations of mobile terminals and the interactive requirement in Virtual Globe, we design a set of finger-screen interactive control mechanism, which consists of a series of multi-touch gestures such as tap, slide, pinch, swipe, double click and so on, to handle the multi-scale interactive browse of 3D Virtual Globe in mobile terminals. Pixel threshold and time threshold are introduced into error control, which solves the problem of unstable disturbances and finite precision while operating the touch-screen interface. To demonstrate the feasibility and effectiveness of this mechanism, experiments were carried out on the platform of Android. The results showed that the shaking screen phenomenon and the error responses were eliminated. It achieves highly effective seamless browse of 3D Virtual Globe in mobile terminals.

The need for updating GIS spatial data automatically and effectively, especially ensuring data security which motivated us to propose a scheme based on digital watermark technology that detects and locates modification data with high accuracy while guarantees exact recovery of the original content and the updated data. In this paper, the data updating algorithm is explored based on digital watermark technology. The copyright and version information are embedded in the process of data distribution. Then, the algorithm of removing watermark information is designed after updating data. Experimental results show that the proposed scheme has good performance in invisibility, and can guarantee that the data is used legally and security. Thus, the authority and effectiveness of data updating can be maintained, and the requirements of storage the qualified data in database is satisfied.

Satellite remote sensing of dust aerosol depth is quite significant for practical application. In this paper, airborne dust AOD is retrieved from the hyperspectral observed data of the Atmospheric Infra-Red Sounder (AIRS) by using Singular Value Decomposition (SVD) method which is first proposed by L Kuser in 2011. According to the analysis, 8.8-12 infrared observation can be used for dust aerosol retrieval. This method took advantage of the spectral shape of dust extinction and surface and atmospheric influence over the total 8.8–12

μ

m window band. Though the proper linear combination of the singular vectors, dust signal was finally distinguish from the influence of surface emissivity and gas absorption. Then dust AOD of Beijing areas was retrieved to validate this method. As a result, the inversion by using SVD is good with ground-based observations of Aerosol Observation Network (AERONET) data, where their correlation coefficient is 0.9891. In contrast to the traditional physical methods, this method takes advantage of the statistics without losing the physical meaning.

In the era of big data, complex network theory has been applied to the field of internet information mining and information research. This study chose the keywords from query term log data of the Korea NDSL (National Digital Science library), and analyzed the complexity properties of keyword network. The result showed that the keyword network had the character of free-scale complex network, and that the distribution of link degree accords power law distribution. Meanwhile, we proved that the key word network has growth and self-organization attributions. In digital library, there are some other big datasets which are similar with the real information search query data, so we can utilize the theory to other keyword network research directly.

The traditional super-resolution image reconstruction methods for optimization and implementation are designed for common processor (CPU). According to the parallel computing capability of GPU-CUDA, a fast super-resolution image reconstruction method is presented based on GPU-CUDA. Additionally, we proposed the MAP framework that can allocate sub-pixel displacement information of low-resolution images to the unified super-resolution image grid. On the basis of the parallel architecture and hardware characteristic of GPU, the acceleration method use CUDA programmable parallel framework to optimize the data storage structure, improve the efficiency of data access and reduce the complexity of the algorithm. The experiment expressed that we could get an over ten times speed effect by this method than traditional super-resolution image reconstruction methods.

Image segmentation is an important step in bridging the semantic gap between low level image interpretation and high level information extraction. Many image segmentation algorithms are available, i.e. active contour method, watersheds method, edge based method, threshold method, etc. Most of these algorithms are parametric and require the image with strong gradient. Mean shift algorithm is a non-parametric density estimation algorithm, which is popularly used in image segmentation recently. However, one bottleneck of the mean shift procedure is that the results of segmentation rely highly on selection of bandwidth. We present an improved mean shift algorithm with adaptive bandwidth for remote sensing images. The bandwidth of each pixel is adaptively adjusted according to the corresponding probability distribution. Compared with traditional fixed bandwidth, our proposed algorithm is both with high efficient and accurate in segmentation of high resolution remote sensing image.

Watermarking is widely being explored as an effective means of providing copyright protection for digital multimedia data, and there has been increasing interest in applying watermark to digital raster map for the same purpose. Tile map, however, subjected to a very different feature from other multimedia data. Thus, the watermark scheme designed for image can not be directly applicable to tile map. The purpose of this paper is to propose a novel feature based watermarking algorithm for tile map. First of all, characteristics of tile map have been analyzed and corresponding requirements of watermarking algorithm has been discussed. Then, the watermark embedding and detection algorithm concerning features for tile map have been proposed. Finally, experiments have been conducted to verify the proposed algorithm. The experimental results have shown that the algorithm has excellent invisibility, and it is able to resist various attack behavior such as adding noise, compression, stitching and format conversion.

The observation scheduling problem with multi-task and multi-resource for multi-satellites is studied in this paper. Firstly, the time constraints and resource constraints remain in the scheduling process are analyzed, and the mathematical model for the scheduling problem is established. Secondly, the ways of checking the time and resource constraints are respectively given, especially for the resource with both producing and consuming functions. Finally an improved ACO is proposed, combining with the task priorities and resource constraint information, proper transition controlling strategy and pheromone updating mechanism. The simulation proves the validity of the model and the algorithm.

With the rapid increase of the number of mobile GPS devices including smartphones, it is becoming more and more important to develop efficient and effective algorithms to analyze massive trajectory data streams generated through those devices. Although there are many algorithms that can find patterns from massive trajectory data stream by batch processes, what we need now is a new algorithm that can deal with massive data streams with limited resources by online processes. This study aims at developing such an algorithm and attempts to discover the places at which people often stop when they are walking or driving, or the places which are becoming crowded by analyzing massive trajectory data streams.

GPS-enabled mobile devices are extremely popular today. Billions of such devices are currently in use. The application and research potentials of these devices are limitless, but how accurate are these devices? The research team used Average Euclidean Error (

AEE

), Root Mean Square Error (

RMSE

), and Central Error (

CE

) to define and calculate the accuracy and precision of twelve popular GPS-enabled mobiles devices in two different geographical regions in Middle Tennessee. Field data were collected, and the results were ranked and compared. A website and related algorithm were developed to facilitate potential future research. In this preliminary study, it was discovered that various mobile devices performed differently in terms of

AEE

,

RMSE

, and

CE

. Their performance also varied in different geographical regions in terms of both (

AEE

,

RMSE

, and

CE

) values and ranking.

In this paper, we propose an improved strategy of terrain dispatching and pre-reading during the process of spatial multi-resolution terrain rendering. The improved strategy is adopted to render the 3Dterrain. The fundamental step of the procedure is the terrain data processing including three parts of terrain data source, terrain data block and terrain texture generation. The ultimate goal is to render the terrain successfully via the proposed strategy of terrain dispatching and pre-reading. The displayed rendering effect demonstrates that the improved strategy is feasible and achievable.

Aiming at enhancing the rendering performance of complex natural phenomena such as smoke diffusion, a rendering approach based on Compute Unified Device Architecture (CUDA) and particle system is designed and implemented in this paper. The strategy that host memory resource is mapped to the CUDA memory address, and the technique which uses two-dimensional textured planar graph to simulate the three-dimensional effect combined with CUDA parallel computing (the parallel billboard technique) are integrated applied. The simulation results demonstrate that this proposed approach can effectively accelerate the rendering process, save memory usage, and achieve impressive visual effects.

With the rapid increasing of spatial data resolution, the high volume datasets make the geocomputation become more time-consuming especially operating some complex algorithms, i.e. viewshed analysis and drainage network extraction. Parallel computing is regarded as an efficient solution by utilizing more computing resource, which has also been proved its availability in digital terrain analysis according to many published literatures. Among them, the stable and credible services play an irreplaceable role in the high performance computing, especially when a failure occurs in the large-scale processing. However, litter research focuses on this issue. In this paper, a new approach for the parallel digital terrain analysis considering the performance of fault tolerance, named the Fast Parallel Recomputing (FPR) was proposed. FPR owns fast self-recovery ability. Once some failures are detected, all the surviving processes repartition the data block and recompute the sub-blocks in parallel to improve the efficiency of failure recovery. The experiments show that the proposed the FPR method achieves better performance than the traditional checkpointing method.

To improve the quality of the fused image, we propose a remote sensing image fusion method based on sparse representation. In the method, first, the source images are divided into patches and each patch is represented with sparse coefficients using an overcomplete dictionary. Second, the larger value of sparse coefficients of panchromatic (Pan) image is set to 0. Third, Then the coefficients of panchromatic (Pan) and multispectral (MS) image are combined with the linear weighted averaging fusion rule. Finally, the fused image is reconstructed from the combined sparse coefficients and the dictionary. The proposed method is compared with intensity-hue-saturation (IHS), Brovey transform (Brovey), discrete wavelet transform (DWT), principal component analysis (PCA) and fast discrete curvelet transform (FDCT) methods on several pairs of multifocus images. The experimental results demonstrate that the proposed approach performs better in both subjective and objective qualities.

The correlation coefficient of two interference image pairs is the basis of the polarimetric radar interference image classification; the different feature category can be obtained through the analysis of the correlation coefficient. The coherence matrix of polarimetric interference after dealing with multi-look obeys the complex Wishart distribution, with a judgment criterion which similar to the Bayesian maximum likelihood classifier, the polarimetric interference radar image can be classified; this method is called polarimetric interference Wishart ML unsupervised classification. This paper summarizes the classification step of this method, and based on full-polarimetric PALSAR data in Tahe area, analyzed the method of Wishart ML unsupervised classification, the classification results show that this classification method has strong adaptability, and has obvious boundary between classes, the classification results belongs to the type of information with the same scattering mechanism, these information provide references for the development and utilization of forest resources.

Terrestrial Laser Scanning has been established as a leading tools to collect dense point cloud over object surface. The collected point cloud does not provide semantic information about the scanned object. Therefore, different methods have been developed to deal with this problem, it may be the most effective one to segment point cloud into basic primitives. This paper intrudes a modified method based on RANSAC to identify planar, cylindrical and spherical surfaces in point cloud. The method firstly construct space division by 3D grid, draw a random sample to determine a sub-cell and carry local-RANSAC method to detect multi-primitive models in it, and get the candidate model(s) by local score, then the best model in the candidate modelscan be obtained by statistic inference, and its consensus set determined by distance and normal vector constrains in the global range. Finally the experimental results show that our method can segment man-made objects with regular geometry shape efficiently, and deal with the over and under segmentation properly.

The historical satellite imagery obtained by US since 1960s is of great significance for monitoring ecological environment changes and its sustainable development. Since 1995, US has declassified the following three batches of satellite imagery (Declassified Intelligence Satellite Photographs, DISP): DISP-1 in 1995, including the first reconnaissance satellite imagery CORONA, ARGON and LANYARD; DISP-2 in 2002, mainly GAMBIT satellite imagery and HEXAGON cartographic satellite imagery; DISP-3 from 2011, metadata (satellite imagery excluded) of GAMBIT, GAMBIT 3 and HEXAGON project information. This paper first presents in detail the declassified data, related plans, parameters and their coverages in China. To make full use of the imagery, we conducted geometric positioning analysis. With the satellite orbit parameters and other necessary parameters unavailable, we discussed geometric correction methods with KH-4B imagery covering Shanghai in 1970s as an example and came to the conclusion that the three order polynomial correction method is the most optimal. The mosaic map has also been generated, providing a basis for further application of the imagery.

The spatiotemporal assessment of Surface Water Quality of River Ndakotsu (latitude 9°.34N and longitude 6°.30E), Lapai-Nigeria was conducted from November 2010 to October 2012, using standard methods. The ranges obtained for the Physico-chemical parameters were air temperatures (23

o

c- 35°C) water temperature (20°C -31°C), depth (8cm-63cm), Velocity (0.83cm/s-6.67cm/s), conductivity (10.28

μ

Scm/s-770.00

μ

Scm/s, pH (5.20-8.75), DO (0.28mg/l-6.70mg/l), BOD (1.10mg/l-31.35mg/l), water hardness (10.00mg/l-315.00mg/l), and total alkalinity (8.00mg/l-317.00mg/l). Water quality changes indicated significant differences (p<0.05) in water and air temperatures, depth, turbidity, velocity, conductivity, pH, water hardness, total alkalinity; Nitrate-Nitrogen and phosphate-phosphorus, but insignificant (p>0.05) in BOD

5

and COD between the five sampled stations within the months. Higher values of these parameters were observed at the impacted station 3.

Six Landsat TM imageries from 2001 to 2008 were used as the data source to identify the spatial and temporal variations of the suspended sediment concentration in surface waters of the Jiulongjiang Estuary and Xiamen Bay. The results showed: (1) The spatio-temporal distribution of suspended sediment concentration in Xiamen Bay are not only governed by river flow and tidal current, but also are affected by factors of wind and waves, which will change greatly in different seasons and regions; (2) There were two relative high concentration zones in different time in the whole Xiamen Bay, the first is in Haimen Island near and the second is in the shallow water area of the east sea of Xiamen; (3) In the Xiamen waters, SSC has strong seasonal variation; surface suspended sediment concentration distribution is different in different waters in a tidal cycle.

Northwest China, covering the provinces of Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang, and a portion of Inner Mongolia, has an extremely complex climate due to the varied terrain where environment is sensitive to climate change. We employed the Mann-Kendal test to investigate trends of precipitation distributions using annual, seasonal and monthly data records from 1960 to 2008. On the whole, the trends of precipitation are more complex than those for temperature. The trends of annual, seasonal and monthly precipitation have shown remarkable difference between the east and west. In the west, such as in northern Xinjiang and western Qinghai, the trend has shown a significant increase, consistent with the temperature change. Whereas in the east such as in eastern Gansu, southern Shaanxi, the trend has shown a remarkable decline, opposite to the change observed in temperatures.

Coastal ecosystem vulnerability assessment was carried out for further better management of marine environment in southeast China. As a research sample area, the coastal of Dongshan Bay was divided into 138 evaluation units according to the geological and topographic features for anecosystem vulnerability assessment. The index system was established according to the “pressure-state-response” evaluation model. The calculated results were analyzed and evaluated through comprehensive assessment methods. The evaluation results illustrated that the fragile ecosystem in concentrated at two regions: one was the estuary of Zhangjiang river mangrove national nature reserve region, another one was the reclaim beach for aquaculture near the Shaxi town in north Dongshan Bay. In consideration of the evaluation results, more protection measures should be applied into these two areas.

It is found that by the survey on the industrial waste water emissions and unreasonable use of fertilizers and an analysis of the correlation between chloride pollutants and other chemical characteristics of shallow groundwater in Jiaozuo that the shallow groundwater has been seriously polluted with chlorides in this region. And this is attributed to the irrational emissions of industrial wastewater as well as incorrect utilization of fertilizers, which have caused an increase of chloride in the shallow ground water. In addition, we also found the sources polluting the shallow groundwater, the pollution mechanism and the transferring disciplinarian demonstrations.

The concept of "national hectare" is introduced into the calculation of ecological footprint model in this article. That is, the national average yield is used instead of the global average yield. Based on this concept, the national average yields of plantation products, forest products, aquatic products and livestock products, the equivalence factors and the yield factors of Xiamen City from 2000 to 2009 are calculated. The main conclusions can be summarized as the following:(1) In the calculation of national average yield of livestock products, the types of productive land for beef, mutton and milk should be expanded from grassland to grassland and farmland according to the actual situation in China. The proportion of the productive land for livestock products attributed to grassland is lower, which affects the calculation result of equivalence factor of grassland. (2) The equivalence factor in the ecological footprint model based on the concept of national hectare is calculated by calorific value method. The results indicate that the equivalence factor of farmland is the maximum, and the grassland is the minimum. (3) It can be seen from the result that the yield factor of grassland in Xiamen City decreases continuously with the years. The biological productivity of grassland in Xiamen City declines continuously compared with the average biological productivity of the national grassland. However, there are large fluctuations for the yield factors across the years, but no obvious rules are identified. This study is conducive to the further calculation of ecological footprint and the comparison of ecological footprint across the provinces and cities. Thus, the utilization and sustainable development trends of natural capitals in China can be reflected.

With the advantages of good condition of port water, large environmental capacity, abundant transport capacity, low freight and modifiable tense situation of land use, the coastal region becomes the biggest petrochemical project region in the world. It is necessary to establish suitable environment risk assessment methods for coastal petrochemical projects so that we can keep away the environment from harm as well as minimize pollution to the environment in operation and after accident. In this research, a scientific nature and accuracy the coastal petrochemical projects’ environmental risk system of Quanzhou petrochemical project is constructed, as well as the assessment method through the instance analysis.This system contains 3 citerion layer indexes, 2 expanding layer indexes and 22 factor layer indexes, forming a multi-level and multi-factor model of structure. After building the index system, the combination of empowerment method of analytic hierarchy process and entropy weight method have been carried out, the indexs are modified and improved using expert consultation method. A linear weighted group legal is appled to valuate the factor weight of the index system and calculate the environmental risk level of the coastal petrochemical projects, as a result, the risk of the project could be determined. It could provide a reference for the coastal petrochemical projects’ environment protections: scientific location decision,environment management, risk prevention and control. It may reduce the impact of the accidents and prevent environmental risks by strengthening and perfecting the environmental risk management system combining with the sensitive degree of environmental factors.

Trajectory similarity search has been an attractive and challenging topic which spawns various applications. In this work, we study the problem that finds trajectories close to some query locations with timestamps designated by a user. We firstly define the similarity between the query locations and trajectory on road networks. Then, we propose a method to retrieve similar trajectories based on Network Voronoi Diagram. By taking advantage of Network Voronoi Diagram, the proposed method can accelerate the query processing through some pre-computation. Finally, we verify the efficiency of the proposed method by extensive experiments.

It is important and practical to search for an effective way to reduce the energy consumption and pollution emission. This paper structures a spatial econometric model of the panel for the identification of spatial effect on provincial carbon intensity and energy intensity, in turn to discuss the mutual positive influences between the areas. According to the empirical study, there exists significant positive mutual influence and convergence between provincial carbon intensity and energy intensity. The provincial level of the indicators also converges to country’s average level in a picture of “boats rising with the tide”. Additionally, provincial indicators only respond selectively to the domestic economic growth and sometimes even show a passive manner.

For mastering the effect of urban expansion on farmland ecosystem health, we adopted information entropy model, hand-picking and stereo microscope methods. Shenbei new district was divided into urban region, urban fringe and rural region. We took samples of large and medium size soil animals and analyzed their gradient variation of individual number, biomass and diversity, richness & evenness indices. The results show: (1) 620 soil animals belong to 2 phyla, 4 insectas and 5 orders. Dominant groups are Nematode, Collembolan and Coleopteran. (2) Individual number of soil animals from urban region to rural region show U-shape trend in both farmland and habitat scale. But species number doesn’t change obviously. (3) There is a relationship of second order curve between the distance from city centre and individual number of soil animals. Using biomass of soil animals is a new try to reflect the effect of urban expansion on farmland ecosystem.

This paper reviews the accomplished research on water quality modelling with the use of Geographical Information Systems (GIS) and remotely sensed data. Basic definitions, theory and classifications of hydrological models usually used in the field of hydrological water quality modelling are highlighted. Examples of research in field of hydrology that benefited from modern technologies of GIS and remote sensing are discussed. Integration of hydrological models with topographic information known as digital elevation model (DEM) is investigated. Conclusions and possible research areas are also suggested.

Recently, research on ecosystem health assessment has become dominance in environmental and ecological science. In this paper, terrestrial ecosystem in the Yellow River Basin was chosen as the assessment subject and characteristics of the ecological pattern, functions and pressure were analyzed. 29 sub-watersheds were selected as assessment units and the terrestrial ecosystem health from 2000 to 2010 was assessed by using RS and GIS technologies with natural social economical features and influence factors. The results showed: (1) the overall health condition of the terrestrial ecosystem was moderate; (2) in the view of spatial distribution, ecosystem health condition in the upper reaches was better than that in the middle and lower reaches, and the condition in the lower reaches turned the worst; (3) in the view of time distribution, the terrestrial ecosystem health was degenerated from 2000 to 2010 and health conditions of only a few sub-watersheds were improved.

The application of the Internet of Things (IOT) and next-generation information technology makes the digital environmental protection become smart environmental construction, and therefore makes our government’s environmental management mode being changed. By studying some smart city application cases and literatures, this paper not only proposed the government management’s operation mode and organization structure for the smart environmental protection, but also discussed an effective method to improve the working efficiency.

The purpose of this paper is to explore the distribution of patent as collateral in the different region in China from 2008 to 2012, and analyze the spatial correlation of patent as collateral with GDP and enterprise patent application. Using the spatial autocorrelation analysis method, we analyze the Global and Local spatial autocorrelation of patent as collateral. Taking the GDP per capita and the number of enterprise patent application as indexes of measure, discusses the spatial autocorrelation of the patent as collateral. Some conclusions are drawn as follow: there is a great increase in the number of patent as collateral from 2008 to 2012, and the upward trend is more significant in east areas compared with middle and west areas in China; The Global and Local Moran’s I of patent as collateral reveals that there is evolution from a discretization pattern to an agglomeration pattern, and the agglomeration area of patent as collateral increasingly concentrated in eastern China; the influences of regional economic development and enterprise patent application are not spatial autocorrelation with patent as collateral before 2012.

One of the fundamental technologies for smart city construction is location-aware technology. This paper discusses a number of key issues related to the implementation of indoor navigation systems. The paper proposes an innovative airport indoor navigation solution that combines Wi-Fi-based multi-mode positioning technology, flexible indoor map and simple route-planning algorithm, with an aim to improve positioning accuracy, stability and enhance user experience. It provide sgreat reference value to the indoor navigation system design and implementation of similar kind.

We propose Principal Component Analysis-Support Vector Machine (PCA-SVM) to forecast the changes of regional carbon dioxide concentrations. Firstly, we get the most valuable principal components of the influencing factors (IF) of carbon dioxide concentrations by PCA. Then we use the output of PCA as the input of non-linear SVM to learn a regression forecasting model with radial basis function. Due to the introducing of PCA, we successfully eliminate the redundant and correlate information in IFs and reduce the computation cost of SVM. The results of the comparative experiment demonstrate that our PCA-SVM model is more effective and more efficient than the standard SVM. Moreover, we have tested different kernel functions in our PCA-SVM model, and the experimental results show that PCA-SVM model with radial basis function performs best respecting to the learning ability and generalization capability.

Agent based modeling, a processed based approach, is advantageous in simulating the interaction between human’s decision processes and environmental systems. In this study, we apply an agent-based model to simulate potential agricultural land use change scenarios in Uganda. The simulation model incorporates decision making processes at small holder and commercial farmers’ level on the basis of biophysical and socioeconomic factors and use these as basis to analyze how farmers’ decisions may affect agricultural land use changes. Geographic information system (GIS) tools are employed to build spatial relations between farmer agents and land cover system. Satellite imageries are used to represent the initial land cover condition and serve as observed land cover dataset to calibrate the simulated results. The results of the simulation model are promising and the model was successful at representing historical and future scenarios of agricultural land use patterns at national-level.

Based on geological background of the workspace, this study determined possible mineralization and alteration types and alteration combinations after analysis; extracted targeted remote sensing anomalies related to the mineralization in the study area; obtained the alteration types corresponding to the mineralization by sorting out the achieved mineralization clues and categories of altered minerals according to the basic geological information; selected appropriate data and reliable algorithm to extract remote sensing alteration information by analyzing the discernible diagnostic spectral characteristics through the mineral and alteration identification physical basics. It also made extensive significant analysis through the combination of remote sensing information about anomalies and deposit type, stratum, tectonic feature etc., as well as previous geophysical and geochemical data and delineated anomalies. Taking into consideration the basic geological background and the distribution conditions of contact metsomatic deposits, hydrothermal deposits and porphyry deposits, the delineation of anomalies is of certain significance for the regional two-dimensional metallogenic prediction and the determination of prospecting targets.

Business Process Management describes a holistic management approach for the systematic design, modeling, execution, validation, monitoring and improvement of organizational business processes. Traditionally, most attention within this community has been given to control-flow aspects, i.e., the ordering and sequencing of business activities, oftentimes in isolation with regards to the context in which these activities occur. In this paper, we propose an approach that allows executable process models to be integrated with Geographic Information Systems. This approach enables process models to take geospatial and other geographic aspects into account in an explicit manner both during the modeling phase and the execution phase. We contribute a structured modeling methodology, based on the well-known Business Process Model and Notation standard, which is formalized by means of a mapping to executable Colored Petri nets. We illustrate the feasibility of our approach by means of a sustainability-focused case example of a process with important ecological concerns.

Precision topography map in the field scale is very important for land rearrangement planning. In this study, the elevation in the field scale from such measurements we encountered a strong trend in a land rearrangement project, of Yichun, China, which we had to take into account in addition to correlated random variation. We separated the two sets of effects and estimated their parameters by OLS. A spherical function seemed best to describe the random effect, and its parameter values were inserted into the equations for prediction by ordinary kriging. We compared the results by cross-validation and calculated the mean error (ME), mean squared error (MSE) and mean squared deviation ratio (MSDR). The fitted model gave small ME, as expected—kriging is unbiased. The MSE is also very small. The MSDR was 1.032, which ideally should equal 1. The goodness of the model encourages regression kriging is a good enough method for modeling topography in land rearrangement project.

A self-adjusting node deployment algorithm is proposed to improve the coverage rate after nodes randomly deploying in wireless sensor network. The proposed algorithm sets the standard distance between sensor nodes that is calculated according to the required minimum nodes meet the full coverage task area. The randomly deployed Nodes are self-adjusted to its new position, which makes nodes move away from each other when mutual distance is less than the standard. On the contrary the nodes gathered themselves together when mutual distance is more than the standard. Simulation experiments show that the new algorithm does more quickly complete coverage then the virtual force deployment algorithm, and it is an efficient method to complete the deployment of sensor networks.

Extracting accurate water boundary plays a critical role in oceanography research. In this study, we tested several water extraction methods using CCD and IRS images from satellites HJ-1A and HJ-1B in Liaodong Bay that has miscellaneous topography structure. These tested methods are based on variant water indices, including NDVI, NDWI, and MNDWI. Moreover, we proposed a new water index NDVI-MNDWI as the fittest model for water object extraction in hybrid area. Relative to these traditional indices mentioned above, the new NDVI-MNDWI model can enhance the differentiation between land and water, and can decrease the interference of artificial objects as well. The experimental results show that the NDVI-MNDWI model can get accurate borders of water objects in hybrid regions.

It is very important for people, who are facing the dust storm disaster, to forecast dust storm accurately. Traditional prediction algorithms tend to be suitable for discovering the rules of majority classes instead of that of minority classes or rare classes. In this paper, according to the monthly data of dust storm observation and the data of occurrence regularity of dust-storm provided by observation points in China, we have discovered that the dust storm occurrence data are merely the rare classes, while the data of non-occurrence of dust storm are the majority classes. Considering that current adopted methods are only suitable for excavating the time period of non-occurrence of dust storm rather than the regularity of dust storm occurrence, we find that the current algorithms are defective in studying rare classes, thus their accuracy is relatively low and is difficult to be improved. Taking this into account, according to the principles of rare classes algorithms, we combine SMOTE algorithm with adaboost algorithm as well as the random forest algorithm and propose a combination machine learning method applicable for the study of rare classes regularities. In this combination algorithm, we first balance the samples of different classes according to the idea of SMOTE algorithm, and then we make predictions utilizing random forest algorithm according to the adaboost system. This new combination algorithm possesses a total predictive accuracy which reaches 96.51%, a false alarm rate of zero, and a missing report rate of merely 0.28%. In general, this combination algorithm is one with practicability, effectiveness and simple feasibility, thus it can be applied and popularized to realistic dust storm forecasting.

FAR (floor area ratio) is an important indicator for urban management. But now in China, FAR is basically determined by the planners with experience, which makes the authority and scientific of the urban planning been widely questioned and criticized. This article attempts to apply quantitative methods to determine the value of FAR. This research utilized the spatial analysis by Geographical Information System (GIS), combined it with geostatistics method to study the spatial distribution of FAR. We used ArcGIS software to carry out the experiment study. The case of Wuhan study shows that the result of Kriging interpolation is superior to other interpolation algorithms and it can produce the minimum forecast error. According to the cross validation table, it is considered that Kriging interpolation is the optimal method for estimation and projection of FAR.

As the most destructive natural disaster, earthquake may cause catastrophic demolition which leads to devastating outcomes. Earthquake’s hypocenter is a point associated with spatial footprint, occurrence time, and magnitude. Open source point process modeling is adopted to detect the possible interactions among earthquakes with spatial features, temporal characteristics and effect of the other covariates. Integration of geologic variables in the point process models is suggested for the investigation of the magnitude 6.1 earthquake and the aftershocks occurred on Jun 30, 1975 in Yellowstone National Park. A Multitype Strauss Process Model is utilized, and it successfully captures the spatial pattern of epicenters under the effect of interaction radii among different types of earthquakes. In addition, the distance to faults and earthquake focal depths are implemented as the geologic variables in explaining the seismic pattern.

Cardinal direction calculus (CDC) which contains 218 basic cardinal direction relations (BCDRs) is an expressive method for qualitative direction information of regions. The inverse relations of BCDRs, however, are still an important issue of spatial direction reasoning. In this paper, a quadruple model is proposed to represent BCDRs based on minimum bounding rectangle (MBR). Then a novel approach to computing the inverse relations of BCDRs is presented in terms of constraints in the quadruple model. Compared with mainly reasoning approaches which do not consider the inverse relations, the algorithm proposed are effective to reasoning performance for BCDRs.

Renewable energy has become an increasingly important and viable approach for mitigating the negative impacts of generating electrical energy with fossil fuels, such as oil and gas. In our study of renewable energy we conducted geospatial analysis of an array of demographic characteristics and renewable energy facilities (manufacturers, installations) for wind and solar energy. The analysis focused on Southern California, but also included two benchmark urban regions in other states, Maryland and Texas with well-developed solar and wind sectors, respectively. Qualitative data on renewable energy was also collected through personal interviews to supplement our geospatial analysis. Implications for sustainability are drawn by identifying key aspects of renewable energy development in Southern California.

This study presents possible way of soil erosion identification on a tropical watershed of Nyaba river basin in Enugu State combining remote sensing and GIS techniques. The aim of this study is to identify and map out soil erosion types in Nyaba river basin and its spatial distribution in 2011. This study identifies soil erosion types in Nyaba River Basin subcatchment units in Enugu Urban of Enugu State, Nigeria, which is a mountainous region with steep slope and an upland ecosystem. To achieve the aim of this study, data were collected from LandSat satellite image of 2011, rainfall data from NIMET for 2011, hydrological data and soil samples were collected in the entire subcatchment unit. The data collected were processed using different methods; Erdas Imagine 9.1 was used in the Land use land cover image classification while the soil type was determine using Soil Textural Triangle by David Whiting, 2011 U.D.S.A , the hydrological data generated was analysed using rational method formula and were categorized into three classes: high, medium and low. Spatial multi-criteria evaluation operation in Arc GIS 10 was used to generate the soil erosion map of the study area. The result showed that there were various erosion types in the study area. Erosion types identified by the research work are rill, sheet, and gully erosion. In conclusion, integrated Remote Sensing, Geographical Information System and Spatial Multi-criteria Evaluation Model tool used to identify soil erosion types in mountainous regions will assist decision makers on environmental management policy.

Emergy analysis is founded on the basis of energy system analysis by the famous American ecologist Odum. H.T, is one of the hot issues of ecological research in economics. This paper describes briefly the basic theory of the energy value, and takes agricultural ecological economic system of the eastern region of Qinghai province as an example, using the net energy output, Per capita energy quantity, important emergy indicators to analyze the problems of agricultural ecosystems in the region, in order to provide a scientific basis for agriculture(de) the sustainable and healthy development of Haidong Region.

River shoreline is a precious but finite resource. With the continuous development of the social economy, all levels of local governments along the river raise the higher requirements for the utilization of shoreline. The exploitation, utilization and protection of the river shoreline resources play a significant role in maintaining the stability of the river ecosystem and promoting the sustainable development of society and economy. The spatial information technology based on VR (virtual reality) is gradually becoming an important technical support to the management of the river shoreline resource. This paper mainly introduces the characteristics and advantages of spatial information technology based on VR as well as its applications in the river shoreline resource management. In combination of the application examples of the main stream of Liujiang river (urban river), the paper discusses the role of spatial information technology based on VR in the management of river shoreline resource.

Italian agri-environmental landscapes are often neglected - when not overlooked or exploited - by urban planning initiatives and their consequences. Often, precious agricultural land is replaced with poor quality real estate. However, with the onset of Expo Milano 2015: “

Feeding the Planet, Energy for Life

,” the goal should be to protect landscapes such as these that are rich in exceptional human, alimentary and ecological resources. The following study is thus devoted to the preservation and revival of viniculture in the municipality of Prepotto (a municipality in Northeastern Italy, bordering Slovenia). These two goals can be achieved through the establishment of an urban analytical protocol for the analysis of the rural system. This protocol will enable the identification of new areas for vinicultural development that strengthen the already elevated quality of the native wine of Schioppettino. The approach presented in this paper integrates motives for the preservation of agricultural land with the economic needs of these border territories. This study offers both public officials and the producers of the unique Schioppettino wines the technical reasons to increase production, elevate vinicultural quality and guarantee environmental sustainability. The territory in question is one of tremendous beauty, exceptional landscape variety and peculiar biodiversity. Therefore, the governance of agricultural space must permeate throughout the urban plan - from the conservation of land to its environmental assets and agricultural multifunctionality. In this case, a multidisciplinary approach and a solid information base to support decision- making are indispensable. The application of Geographical Information Systems and the recourse of multivariate geostatistics have allowed the extraction of available information from regional archives. This information has been used to estimate the necessary indicators and interpret the particular complexity of these agrarian landscapes. A new role can thus be attributed to the field of urban planning: the protection of a non-renewable resource, namely land, with simultaneous attention to themes of landscape, tourism and agricultural productive quality - the only true alternative to the current industrialization crisis of these lands on the North/East border of the country.

On the basis of multi-source satellite data on compact ratio, fractal dimension and barycentric coordinates across different periods, we analyze the spatiotemporal characteristics and morphology changes of Tangshan using geographical information system and remote sensing techniques. The speed of urban expansion slowed down from 1976 to 1996 and changed periodically from 1996 to 2013. The variation trend of the compaction index is contrary to that of the fractal dimension. The changes in the compaction index showed a downward trend, and the fluctuations were reduced after 1996. Meanwhile, the variation trend of the fractal dimension is exactly the opposite of that of the compaction index, which showed an upward trend and experienced an increase in fluctuations after 1996. The barycenter of the built-up area of Tangshan moved toward the northeast from 1976 to 2009 and turned southwest from 2009 to 2013.

This paper presents an integrated study about the urban expansion process in Beijing from 1973 to 2013. Annual urban expansion area index, gravity center transfer model, fractal dimension index and the elastic coefficient or urban expansion-population growth are employed to explore the temporal and spatial characteristics of urban expansion. The results reveal that urban expansion of Beijing underwent seven different expansion stages, including one slow and steady expansion stage, three fast expansion stages, three shot deceleration stages, in the past 40 years. The centroid of urban lands moved to the southeast and urban boundaries became more and more complex and irregular. Urbane expansion speed was not harmonized with population growth distinctly in 1987-1998, 2000-2003 and 1998-2000. This study can provide scientific data for urban planning of Beijing and related studies of urban expansion in depth.

In this study, the BEPS (boreal ecosystem productivity simulator) model combining the Moderate Resolution Imaging Spectroradiometer (MODIS) multi-temporal satellite remote sensing data such as leaf area index (LAI) and land cover types data were used to simulate the rapeseed in Hubei province. Interpolating the 17 agricultural meteorological stations data of rapeseed in the study area, and based on the relevant data of rapeseed crop growth physiological and the process of rapeseed growth simulation technology, the estimating biomass of rapeseed was performed in a regional scale. This paper validated the result of simulated BEPS model and actual statistical data of rapeseed yield. The results showed that the model simulated values are agreed with the actual statistics yield of rapeseed, the correlation coefficient (

R

2

) is up to 0.877 with 0.01significant level. The simulated value with absolute mean square error (RMSE) of statistics is 416 kg/hm

2

. It determined that the BEPS process-based model integrated with MODIS satellite data can estimate the rapeseed yield in a regional scale.

China’s ‘National Program for Medium-to-Long-Term Scientific and Technological Development (2006-2020)’ has been promulgated seven years. However, there are few works referred to it’s impact on innovation capability of China’s strategic emerging industries. This study investigates how China’s policy affects patent licensing’s geographical evolution, by empirically scrutinizing licensed patents in strategic emerging industries from 2000 to 2012. The results show that, the publication of China’s independent innovation policy accelerates the evolution of patent licensing in China’s strategic emerging industries though reducing the lag period between patent applying and licensing as well as decreasing the geographic distance between patent licensor and licensee. Moreover, the positive effect of policy on industries’ capability of independent innovation appears distinct among different strategic emerging industries.

This study take the Huangfuchuan Watershed temperate grassland as the study area, RS and GIS techniques are used to explore the relationship between LUCC and NPP. With the combination of CASA model, the dynamic characteristics of NPP in 1987-2011 are studied. The main conclusions are as follows: (1) land use structure changes obviously in Huangfuchuan Watershed. The main trend of land use change was the gradual increase of construction land and woodland, the gradual decrease of water. Arable land, grass, shrub, bare rock and sand were fluctuant. It could be seen from land use dynamic degree. (2) Through the calculation of NPP model, the total value of NPP in 1987, 1995, 2000, 2007 and 2011 was 28.12GgC, 53.47GgC, 73.23GgC, 157.92GgC and 78.52GgC. (3) Through the analysis of land use change effects on NPP, it indicates the main reason for the increase of NPP is due to grassland transfer to shrub between 1987 and 1995. The decade of bare rock is the main reason for the increase of NPP in 1995-2000. Shrub transferring to grassland is the main reason for the increase of NPP in 2000-2007. Grassland transferring to shrub is the main reason for the reduction of NPP in 2007-2011. The results of the study is very meaningful for rational using of temperate grassland resources and improvement of the fragile ecological environment.

In recent years, Vietnam is very interested in the investigation classification, soil mapping, evaluating Suitable land, which has been an important contribution for enhancing the quality of plans for agriculture land use planning. It has been also the primary goal to synthesize and build the plant restructuring orientation associated with the restructuring of land use.

Through the preliminary evaluation regarding the socio-economic conditions, the soil as well as the farming practices at Thuy Bang Commune, Huong Thuy Town, Thua Thien Hue Province, Vietnam, it shows that this is the great potential land which is to develop the peanut production, and the inhabitants who live there are also increasingly expanding the planted peanut area in recent years. However, the determination and the suitable ability partition which is the scientific basis for the implementation of land planning to develop the planted peanut is yet to be processed. The study combined with the land evaluation according to FAO and GIS technology application, specifically is ArcGIS software, which are the implements to build the thematic maps and superpose these maps constitute the land unit map, then classify appropriately for peanut planting in the studied area at present and in the future. The research results have identified that Thuy Bang Commune has 28 land map units; the current classification for peanut planting shows that the studied area appears only at low and suitable medium accounted mainly. The research has been proposed to the developed area and distributed specifically to every other area and each land unit for the peanut planting of Thuy Bang Commune. The proposed research is very important and it is the scientific basis for the reference planning of the agricultural development in the future of Thuy Bang Commune, Huong Thuy Town, Thua Thien Hue Province, Vietnam.

There were many problems in Environmental Assessment (EA) application, which were inadaptable to the request of Joint Prevention and Control of EA (JPCEA),nowadays in China. Based on Environmental Assessment Automation System-C4ISRE, JPCEA integration simulation demonstration system were constructed which could product multidimensional information environment pollution situation scene which including natural geography environment, electromagnetic environment, space environment and so on, the related concepts and processes about JPCEA could ,which drove by simulation model and simulation system ,be shown in the way of all-direction, multi-angle. This method supplied one feasible technical reference for further JPCEA business research.

The management of the national sustainable development experimentation areas is faced with many problems, such as the complex and variable flow, affluent information and high-grade decision analysis. An online management system of the national sustainable development experimentation areas is developed based on the workflow technology and the business process management theory. With the traditional method, the system should be redeveloped if the management flow of the national sustainable development experimentation areas changed. In order to overcome this repetitive work, the dynamic definition model of the business process about the management of the national sustainable development experimentation areas is put forward. Based on the new system, the traditional artificial management mode of the national sustainable development experimentation areas can be transformed to system adaptive management pattern. The on-line use of the system shows that the efficiency and normative of the experimentation area management has been greatly improved.

With the launch of the first and second national land surveys, it has obtained the massive historical data of land survey. However, the key condition is how to manage the mass land survey data effectively. In accordance with these problems that the current base state amendments model exists high data redundancy and low history backtracking, based on the analysis on the strengths and weaknesses of existing base state amending model, combining the characteristics of changing trivially in land survey data, this paper puts forward a new base state with amendments model which is suitable for land survey data management. The model changes the general base state as a snapshot storage mode, only stores the initial base state of the file, reducing the amount of data storage; It dynamically establishes base state and improves the retrieval efficiency. The application results show that the improved model can save, manage and backtrack land survey data with low redundancy and high efficiency.

MAS(Multi-agent System) is a new modeling method developed in recent years. This article aims to use MAS technology to simulate the development process of urban land. Five factors, which may have impact on the choices of agents, are defined. Spatial analysis and multi-factor evaluation technique is employed to determine the weights and utility value for each factors. On the basis of an MAS platform named RePast, combining with other open source GIS component, the model proposed is implemented through second development using Java language. Finally, the status quo of Wuhan City in 2003 as initial value, future land-use changes are simulated. The result of primary experiment seems promising, and the outcome of model simulation is interpretable and reasonable. So we can conclude that MAS can be used to simulate urban land development, and the simulation results will provide decision basis for urban managers.

The central part of Wuhan City was chosen as soil sampling region to investigate the spatial distribution of heavy metals in roadside soils and the correlation between city road net and the spatial distribution of heavy metals. The total number of samples collected is 224 and the concentrations of As, Cr, Cu, Ni, Pb and Zn in soils were detected. The spatial distribution of heavy metals in roadside soils was characterized by applying Universal Kriging interpolation model. The correlation between road net and the spatial distribution of heavy metals was analyzed based on Voronoi diagram. The results show that there is high correlation between the road net and the distribution of heavy metals in the range of 400 m on both sides of the main road of the study area. There is no strong relationship between road net and heavy metals in the soil of the whole study area which indicates that the road net of Wuhan is not the main source of heavy metal contaminate in soils.

The purpose of this study is to investigate the current status of heavy metal pollution in surface soils from Hankou Region, the old industrial district in the city of Wuhan, China. The contents of eight heavy metals As, Cd, Cr, Cu, Hg, Ni, Pb and Zn were tested for each 132 soil samples. The results show that the average value of Cd and Zn in soils of Hankou Region were up to 0.548 and 220.7 ug/g, respectively, which were much higher than their natural background values. Their spatial patterns were analyzed by the geographical information system (GIS) technology. The spatial patterns of these elements revealed that Cd, Zn and Cu might originate from the familiar traffic and industrial, and the elements of As, Cr and Ni could originate from the natural sources. The values of pollution index (PI) indicated that metal pollution level was Cd > Zn > Cu > Hg > Pb > Ni > Cr > As. Potential ecological risk indexes (RI) further indicated that Wuhan was suffering from serious metal contamination.

Success in any commercial events of sport in today’s world is built and refined largely based on abundant and exceedingly diversified information. Player as the principal element of any sport has long been measured by many attributes and further examined by multiple disciplines and resulted with abundant findings and inspiration. The study tries to utilize information regarding birthplace at prefecture city level of a player in those records to identify some distributional characteristics of those places and examine the certain factors that leading to the findings. The results of spatial Distribution Analysis of Chinese Soccer Players’ birthplaces show a very unbalanced distribution, and are promoting that differentiated background of soccer developments, geographic seating with advantageous means of outward communication as well as conventional social-economic measures interact closely with a place in promoting its chance of breeding more soccer players of top level in nation.