The research approach based on sub-watershed partition, which is taken as an indispensable tool of spatial analysis in GIS applications, plays an important role in many research fields of watershed, such as landform, soil, hydrology and environment. Watershed codification usually is a key step in the research process via the above approach. Compared with some other watershed codification methods, Pfafstetter coding system is widely adopted due to its uniqueness of code, consideration of topological relationship and high efficiency. At present, with the development of spatial data acquisition technology, the quick acquisition of spatial data from large areas and with fine scales becomes a solid reality, which brings a great difficulty to GIS on how to process and analyze these massive datasets quickly and efficiently. Parallel computing brings an opportunity to face this challenge with the development of computer technology. In this paper, a parallel watershed codification algorithm was proposed to overcome the computation difficulties in processing the massive grid dataset. Firstly, the Pfafstetter coding rule was modified to compensate the disadvantages in the original algorithm including the incomplete coding and inconsistent code point. Secondly, data partition and parallel strategy were discussed based on the serial Pfafstetter coding algorithm and the requirements of data parallelism. At last, the parallel algorithm for watershed codification was realized and implemented. To evaluate the validity and the efficiency of the proposed parallel algorithm, experiments were designed on a cluster system with SRTM dataset covering the middle and upper watershed of Yangtze River. The experiment results showed that the parallel algorithm could generate correct results which were consistent with those in the real world; meanwhile, it possessed a significant improvement of computational efficiency. Besides the advantages in improving the computation ability and efficiency for the watershed codification algorithm, the parallel strategy in this paper could be further expanded as a reference to other researches on watershed analysis.

The problem of Large-scaled Point Feature Cartographic Label Placement (LS-PFCLP) is one of map labeling difficulties, which is mainly limited by time efficiency and labels’ quality. Changing this plight will accelerate the application development of Intelligent Cartography. The article firstly contraposes the form simplification of traditional potential label position scheme and puts forward an oval multi-orientations and multi-levels cartographic potential label position scheme to make a better conformation of the potential label position scheme to the actual demand, and make it parameterized and multiplex. Secondly, the article combines the space distribution features of point features to adopt an Ant Colony Algorithm based on cluster grouping (C-ACA), whose core framework is decreasing the large scale of points to plural mini-scaled point collections through DBSCAN clustering, then integrating Ant Colony Algorithm to C-ACA. In the process of C-ACA’s implementation, we discuss and optimize the core parameters, such as Eps and MinPts of DBSCAN, ant colony size parameters (\begin{array}{c}{P}_a\end{array}、\begin{array}{c}{\eta }_{\mathit{cj}}\end{array}、\begin{array}{c}{\tau }_{\mathit{cj}}\end{array}、\begin{array}{c}{P}_{\mathit{cj}}^b\end{array}), and evaluation function of \begin{array}{c}{E}_{\left(\mathit{bc}\right)}\end{array}, to achieve Large-scaled Point Feature Cartographic Label Placement. Experiments show that C-ACA has a great contribution to the efficiency improvement of LS-PFCLP. When compared, with two cases of random points tests and one realistic boundary points case, with techniques such as Ant Colony Algorithm (ACA), the C-ACA has been proven to be an efficient choice, with better performance in both efficiency and quality. In case 1, The C-ACA improves the efficiency by 73.2 percent than normal-ACA, when the label density falls in between 5% and 30%. Moreover, the altered resultant label’ quality is 8.0 percent better than before. In case 2, the result of C-ACA has justified the stability presentation. In case 3, we have used this algorithm to process the boundary points of the collective land ownership data of Fushun county in China, which has improved the efficiency by 86.7% and the quality by 14.6% with outstanding performance. We concluded that the improved algorithm is applicable to LS-PFCLP with points that having massive quantity and greater variations of clustering density.

Watershed process simulation has become an important tool for geographical researches and decision making of watershed management. For watershed process simulation with long period, high spatial resolution and multi-process integrated modeling, the amount of required computation is so huge that the parallel computing is urgently needed to handle these simulations. Currently, the rapid development of hardware and software in parallel computing provides a good opportunity for solving the computation bottleneck of multi- process and high-resolution watershed process simulation over large regions. In order to take full advantage of the capabilities of new parallel-computing hardware, it is necessary to use geographical laws, which illustrate the characteristics of watershed processes, to guide the design and implementation of parallel computing algorithms. This paper presents that geographical laws can be used to guide the design and implementation of parallel computing algorithms for watershed process simulation from different aspects (i.e. spatial, sub-process, and temporal aspects). The laws that can be used include the spatial hierarchy structure, the interactions among spatial units, the dependences among geographical process, and the spatial-temporal dynamic of geographical processes, etc. At the end of this paper, two parallel computing cases of watershed process simulations guided by geographical laws are illustrated to show how these geographical laws can be used in real-world applications. This paper intends to provide a theoretical and methodology guidance for parallel computing of watershed process simulation and other similar types of geo-computation.

With the development of high performance computing, parallel processing has been widely used in analyzing LiDAR point clouds. Aiming at the loading unbalancing problem that exists in current parallel algorithms for generating DEM from LiDAR point clouds, this research implements a parallel algorithm which uses dynamic load balancing strategy to generate DEM from massive LiDAR points. The parallel algorithm is based on the master- slave scheduling strategy. The master processor adaptively partitions LiDAR data and generates several strips afterwards. The data strip may be horizontal or vertical based on the characteristic of LiDAR data. The slave processors generate raster DEM from discrete LiDAR points using spatial interpolation. Furthermore, we propose a dynamic scheduling strategy based on the quantity of tasks. The quantity of each task is measured by the number of points in data strip. Firstly, all processors count the point number for all data strips and the master processor creates a task queue. The task queue is arranged according to the point number of those data strips in a descending order from the largest to the smallest. Secondly, the master processor communicates with the slave processors to distribute these tasks dynamically, thus to help the slave processors achieve the load balancing. In this way, all of the data strips are processed from the largest to the smallest based on the computational complexity. Finally, we test the proposed parallel algorithm in a cluster. The cluster is composed of 24 cores. The volume of the LiDAR point clouds for testing is 30 GB, which contains about 1.2 billion points. The resolution of the target DEM is 1 meter, and the biggest speedup ratio of the parallel algorithm is 15.16. At the same time, we compare the dynamic scheduling strategy proposed in this paper with the static scheduling strategy. The result shows that the dynamic scheduling strategy proposed in this research achieves a better load balancing among all processors. Therefore, we can come to a conclusion that the parallel algorithm proposed in this research can significantly improve the efficiency of generating DEM from massive LiDAR point clouds.

There are a large number of earthen sites that have important historical and cultural values in Turpan region, Xinjiang. It is very meaningful to study the spatial-temporal change of earthen sites and their environment. Aiming at the exploration of earthen sites conservation, using methods of archaeology and field investigation, remote sensing (RS), geographic information system (GIS), and global positioning system (GPS) techniques, we analyzed the spatial-temporal change of earthen sites and their internal-external environment. The results showed that the persistence of the earthen sites has a close relationship with the regional environment, that the regional environment has an influence on the persistence of earthen sites. The earthen sites and their internal environment had changed greatly from the 1960s to 2010. We found that the main driving forces of earthen sites and their internal environment change were diseases and human destructions. The main forms of diseases in earthen sites are fracture and collapse, wind erosion, water erosion, alkali disease, surface peeling, and biological erosion. Among the above factors, fracture, collapse and wind erosion are the dominant forms. From 1990 to 2010, great changes in the external environment of earthen sites had taken place in the study area. The cultivated land and residential land had increased significantly, while the grassland and unused land had decreased obviously. The changes in the external environment were especially obvious around Jiaohe and Gaochang ruins, while the intensity of human activities around these earthen sites had increased. The changes in surface environment types of earthen sites in different regions were different. The changes in environment types of earthen sites that located in the interior of oasis were more intense than those located at the edge of oasis; earthen sites that located in the interior of oasis are more vulnerable to the impacts of human activities. The development of cultivated land and residential land were the main driving forces of the external environment change of earthen sites, thus it is necessary to limit human activities for the purpose of earthen sites conservation.

Endmember extraction is a key step for unmixing hyperspectral mixed pixels and an important prerequisite in the further analysis of hyperspectral imagery. The traditional N-FINDR algorithm is a classical and effective algorithm among various endmember extraction methods. However, the N-FINDR algorithm need to compute all the possible pixel combinations, thus it is time consuming. In order to improve the time efficiency of the N-FINDR algorithm, this paper proposed an improved N-FINDR algorithm on hyperspectral endmember extraction based on spectral Shannon entropy theory and the convex geometry, meanwhile we utilize the characteristic that in spectral feature space, all pixels of the hyperspectral imagery could compose a single shape body, in which the pure pixels are located at the apex and the mixed pixels in the interior or at the surface. The spectral Shannon entropies of all pixels are calculated according to the pixel gray probability, and are used to determine the purity of pixels. The pixel is removed if its spectral Shannon entropy is greater than the threshold value of the spectral Shannon entropy, otherwise it is preserved. Next, the N-FINDR was used to search the largest volume from the single shape body composed by the preserved pixels, and the pixels at the apex of the body with the largest volume would be the endmembers. Finally, we use the Hyperion data of a copper mine in Dexing city from Jiangxi province to testify the improved N-FINDR algorithm. By analyzing the experimental results, the improved algorithm ensured a high accuracy as well as improved the data processing efficiency very greatly in the course of extracting hyperspectral endmembers.

With the rapid development of remote sensing (RS) image acquisition and processing technology, the spatial resolution and temporal resolution of RS image have been greatly improved. For large-scale RS image, traditional sequential pyramid building algorithms have been found difficult to meet the quick browsing requirements. Technologies and facilities of high performance computing have become more and more feasible to researchers. Taking the advantages of multi-core, multi-node cluster computing environments and parallel processing mechanism is turning to be an inevitable trend. Some of recent works explore the efficiency and flexibility of parallel pyramid building methods. However, these methods all have deficiencies. For example, GPU-based parallel method is hardware-aware, the improvement of its performance is limited on a single node, and the system architecture will be too complicated when applied in a cluster environment. Whereas the distributed clusterbased method requires the data to be distributed to be stored in different nodes, and the complete pyramid file needs to be merged, which is excessive time consuming. Therefore, using the high-performance disk-shared cluster is an alternative mechanism for achieving the parallel building pyramid of large-scale RS images. In this paper, we proposed a parallel algorithm based on Message Passing Interface (MPI). Based on this, the whole pyramid building task is decomposed into several subtasks. The result of each subtask can be written to the same pyramid file simultaneously by incorporating MPI/IO. The algorithm can greatly improve the performance of pyramid building through parallel resampling and parallel I/O. Specially, with regard to the multi-band pyramid file stored in BIP format, a parallel I/O strategy using file view was proposed to improve the performance of parallel writing. Experimental results show that our algorithm has better acceleration effect compared to the sequential method, and there is a positive correlation between the acceleration effect and the image size. For large remote sensing images (in our case it is 46G), the performance of our parallel algorithm can be approximately 10 times faster than GDAL.

Trajectory outlier detection is significantly important in the field of data mining for moving object. TRAOD (TRAjectory Outlier Dectection Algorithm), a classic algorithm for detecting trajectory outliers, focuses on a new two-level trajectory partitioning strategy to enhance the efficiency of algorithm. The main advantage of TRAOD algorithm is the ability to detect outlying sub-trajectories. However, it has a low efficiency on abnormality detection for massive trajectory data. In order to improve the efficiency for mining trajectory outliers from massive datasets, a parallel algorithm for detecting trajectory outliers based on MapReduce framework, which is called PTRAOD (Parallel algorithm for TRAjectory Outlier Detection), is presented. It redesigns the TRAOD algorithm based on the MapReduce framework, and encapsulates the steps of TRAOD into its Map and Reduce functions. PTRAOD algorithm takes full advantages of the features from Hadoop platform. It firstly distributes the trajectory data into distributed computing nodes. While distributing the data, it also takes the load-balance into consideration. And after all, each node runs the same algorithms to detect abnormal trajectories. Based on PTRAOD algorithm, a grid-based parallel algorithm for detecting trajectory outliers, called GPTRAOD (Gridbased Parallel algorithm for TRAjectory Outlier Detection), is then proposed. GPTRAOD algorithm makes use of the grid index to realize regional query and reduce unnecessary calculations. At first, GPTRAOD algorithm divides the map into a series of equal- sized grids, whose size is determined with respect to each specific data. Then, the grid index is established to implement the regional query. Finally, the algorithm finds out the abnormal trajectory segments and judges whether the trajectories that contains the abnormal trajectory segments are abnormal. In general, GPTRAOD algorithm takes advantages of the gird index to realize regional query on the basis of PTRAOD algorithm, which furthermore can search abnormal trajectory on the cloud computing platform. To assess the performances of the proposed algorithms, extensive experiments were conducted. The experimental results demonstrate that the proposed two parallel detection algorithms can both successfully achieve the trajectory outlier detection. The efficiency of PTRAOD algorithm is higher than TRAOD algorithm, while GPTRAOD algorithm has the higher scalability and better speedup ratio than PTRAOD algorithm. In addition, with the rapidly expanding of datasets, GPTRAOD algorithm shows obvious advantages and increasing potentials.

Parallel raster- based programming libraries have been proposed to make the details of parallel programming and the parallel hardware architecture to be transparent to users in some degrees. Thus these libraries can facilitate the development of parallel programs of raster-based geocomputation. Among the existing parallel programming libraries, parallel raster-based geocomputation operators (PaRGO), which is recently proposed by Qin et al, shows great advantages. This is not only because PaRGO encapsulates the general steps in parallel raster- based geocomputation, but also because PaRGO is compatible with multiple commonly used parallel computing platforms. Currently, PaRGO is designed for supporting local operation, focal operation and global operation directly. However, the availability of PaRGO for supporting regional operation in raster-based geocomputation has not been evaluated. In this paper, we evaluate PaRGO to testify its performance in this circumstance by using a multiple-flow-direction algorithm as a representation of the regional operation. Different versions of PaRGObased parallel programs for this algorithm are tested on a symmetrical multiprocessing (SMP) cluster and evaluated from two aspects: the performability and the parallel efficiency. The experimental results show that the current PaRGO cannot directly support the parallelization of regional operations. But it can be supportive when the regional operation is transformed into an iteration process of focal operation. On a SMP cluster, MPI-version parallel program performs better than MPI/OpenMP-version parallel program.

Parallel computing provides a promising solution to accelerate complicated spatial data processing, which is becoming increasingly computational intense. Partitioning large datasets into workload-balanced subgroups remains a challenge, particularly for unevenly distributed spatial data. In this study, a density-based data grouping algorithm was developed to tackle the partition problem for large line data. The algorithm includes three procedures: (1) extracting representative segment samples based on data density distribution; (2) generating a distance matrix between segment samples and the rest of the data by using three line distance measurements into calculations; (3) grouping line segments with data load balanced. Experiments show that the algorithm is able to partition large line data efficiently and evenly into equally sized sub-groups. The speed-up ratios of parallel interpolation save up to 65% of the execution time in comparison with consequential interpolation. A high efficiency of parallel computing was achieved when the datasets were divided into an optimal number of child data groups.

The commonly used Plane Sweep algorithm in spatial relationship query is a serial algorithm. Some scholars had studied some parallel query algorithms that based on multi-core CPU. However, due to the limitations induced by the number of CPU's core and thread, when dealing with massive data query, these methods are incapable to meet the requirements for query efficiency. To solve this problem, this paper proposes a new parallel algorithm of spatial relationship query between polygon layers based on heterogeneous multi-core architecture. The algorithm used STR-tree index to filter the disjointed polygons first. After the filtration, we built a quadtree index to manage the line segments of the polygons, so that we could quickly get the line segment combination to prepare for computing the intersection situations. Then, the CPU+GPU architecture was adopted to parallel compute the line segments'intersection situation. In details, we firstly put each line segment combination into each thread of GPU to calculate the relevant intersection situation, and the intersection type was counted using CPU. Next, the topological relations between the polygon rings were judged according to the type of line segment intersection, thus the values of DE-9IM parameters between these polygons were calculated based on the topological relations, and accordingly, the spatial relationship between the polygons were determined. At last, the efficiency and accuracy of the algorithm was verified by an experiment. In the experiment, we gradually increased the polygon number of the source layer and the target layer. When both of the two layers had 50000 polygons, here took the Contains relation as an example, we found that the computation time of the parallel algorithm is 15.143s faster than ArcGIS, and the speedup ratio can reach up to 2. In general, the parallel algorithm has more obvious advantages in dealing with higher volumes of data.

With the development of Earth Observation (EO) technology and the increasing geospatial sensor resources, it is necessary to efficiently manage geospatial sensor resources in Geospatial Sensor Web environments which facilitate users to plan and use these resources comprehensively, accurately and in demand. Based on the analysis of (1) features of EO emergency event and (2) demands of sensor emergency observation planning, this study aims to achieve the near real-time, accurate and comprehensive discovery of existing heterogeneous EO sensor resources. We propose an integrated management method of EO sensor resources oriented to emergency observation planning. The research contents include how to organize and build the index of EO sensors’ information, how to calculate the observation area covered for space-based sensors, and how to design the inquiry of metadata for collaborative emergency observation. Based on the above mentioned workflows that included in the proposed integrated management method, this study designed and produced an integrated management tool which is entitled GeoSensorQuery for emergency observation planning, via the utilization of Java programming language and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) information standard model-Sensor Model Language (SensorML). Finally, an application focusing on planning the flooding observation sensors occurred in the middle reaches of Yangtze River basin of China has been exemplified, in which the designed GeoSensorQuery prototype can meet the requirements of near real-time, accurate and comprehensive discovery of massive and heterogeneous EO sensor resources. As a conclusion, the selected example has verified the feasibility of our method.

We study and propose the evaluation approach for parallel geo-computation algorithms from the following aspects: correctness evaluation, performance evaluation, evaluation routines and evaluation tools. This approach proposes the hypotheses for correctness evaluation which are viewed as the foundation of measuring the correctness of geo-computation algorithms. To measure the correctness, we compute the relative errors by comparing the results using a certain algorithm under the single-process with the corresponding results evaluated under the multi-process environment. In this paper, we present a method in which the weights of the evaluation cases are determined by the computation scale. We also discuss a method which computes the computation scale of evaluation cases. The method involves the data scale, data distribution coefficient and time consumption per unit computation. Meanwhile, the geo-computation algorithms are evaluated by cases with weights. Under some circumstances, we can obtain the various evaluation indicators of a certain algorithm, such as the execution time, the speedups, and the parallel efficiency. In addition, this paper designs an evaluation routine based on the correctness evaluation and performance evaluation. It obtains the correctness evaluation and performance indicators of our target algorithms and generates the final reports. After experiments, we may confirm that our techniques can meet the requirements for evaluating parallel geo-computation algorithms. It could provide an effective support to algorithm optimization.

Dengue fever is an acute insect-borne disease transmitted by the Aedes mosquito, which is a class B infectious disease in China. Understanding the variations occurred in the spatial and temporal distribution of dengue fever epidemics will bring improvements to dengue fever prevention and control. In this study, monthly incidence data for dengue fever at municipality level across China were analyzed for the period from 2004 to 2013. The relationships between the incidence rates of dengue fever, the involved municipalities, and the imported cases were determined. The geographic pattern of dengue fever incidence rates was examined by GIS, spatial autocorrelation analysis and from the tracks of the centre of mass. Results showed that: (i) annually, the incidence rates for indigenous dengue fever cases exhibited the highest values between August and October, while the imported cases peaked between July and October. (ii) The logarithmic values of indigenous dengue fever cases was significantly correlated with the numbers of imported cases (r=0.669, p<0.05), while the number of municipalities with imported cases was linearly correlated to the number of all municipalities that have dengue fever cases (r=0.939, p<0.05). (iii) In addition to the increasing incidence rate, the dengue fever epidemic was affecting an increasing number of municipalities. The range of the epidemic was steadily increasing and gradually spreading toward inland area from the southeastern coast. (iv) Dengue fever cases did not distributed randomly with respect to time and geographical space. The highest density occurred in areas of Pearl River Delta, Hanjiang River Delta, Dehong prefecture, and Xishuangbanba prefecture. The centre of mass of dengue fever incidence rates was not stable and moved from the southeast coast (Fujian and Guangdong provinces) to the southwest (border of Yunnan province), which revealed the changes of the dengue fever distribution pattern. Our results indicate that the dengue fever epidemic in China is driven by imported cases from other countries. According to the temporal and spatial characteristics of the increasing incidence rates at municipality level and the expanding range of dengue fever in China, a stronger border inspection for people entering from abroad, especially from Southeast Asia and during the peak epidemic months between July and October, may be effective in preventing the spread of this rising epidemic.

Today, an abundant supply of remote senseing data with various spatial, radiative and spectral resolutions from multi-platforms has provided rich sources of information for scientific research. In order to overcome the limitation of a particular type of remote sensing data in application, and take the full advantage of other remote sensing data, image fusion technique has been frequently used to enhance the resolution of remote sensing data and perform scale transformation among images obtained from different remote sensing platforms. A proper image fusion algorithm can not only improve the refinement of details of a low-resolution multispectral image, but also preserve its spectral information. Moreover, it can utilize the complementary information, reduce the data redundancy, and enhance the interpretation ability of the images. The fusion result is influenced by many factors, such as image fusion algorithm, seasonal difference, registration error, spatial and radiation resolution difference, etc. The images used in this study have different radiation resolutions, including 8 bit, 11 bit and 16 bit. In order to reduce the influence of differences in the radiation resolution and in the resultant data dynamic range on image fusion, this paper proposed a method for the standardization of radiation resolution. Based on the unification of quantization intervals for digital number, the transformation from low to high radiation variability through multiplication of a same proportion coefficient can reduce the loss of image information, which is caused by data bits conversion in the fusion process. The results show that the proposed standardization method of radiation resolution can be applied to remote sensing data with different quantization intervals and is easy to be programmed. When using the proposed standardization method for fusing different images, the resultant fusion results are almost identical to each other, either using real number value or integer value. Whereas, when using other quantization methods, the resultant fusion image with real number value is generally better than that with integer value. The standardization of radiation resolution is a necessary step for image fusion when using reflectance-based images, because all image fusion algorithms will cause a serious spectral distortion to the fusion results.

Mental representations of spatial knowledge are organized hierarchically. This should be introduced to route guidance in order to reduce the cognitive workload of drivers, and to increase drivers′ satisfaction and wayfinding success probability. The most commonly used hierarchical spatial reasoning based route planning methods take the hierarchical characteristic of road network into consideration, but the road design grade used in these methods does not conform to human′s hierarchy recognition of road network. In this paper, we introduce the complex network analysis methods, and take use of topological structure measures to express roads′ hierarchical characteristic. And on this basis, we propose a novel route planning method. The planned routes are compared to the taxi driving routes in reality and the travelling time decrements are calculated by comparing these routes to the distance shortest route. The experimental results indicate that, the routes that are planned using our method are more rational and optimal than the distance shortest routes, dynamic time shortest routes, road grade based time shortest routes and dynamic betweenness centrality hierarchy based routes, and are equivalent to the empirical taxi driving model based routes. Moreover, our method does not need the support of floating car system, hence it is more practical for promotion and application.

Data I/O has become one of the main bottlenecks for parallel geospatial computing. In this study, we firstly explore the data structure of a widely used GIS raster data format-GeoTIFF, particularly focusing on its storage modes (strip storage and tile storage). The transfer functions which map the logical structure of data to the physical storage structure were constructed for both storage modes.This article also designs a framework for parallel I/O of raster data and implementsa parallel GeoTIFF I/O library (pGTIOL) using the file-view technique of MPI-IO. Experimental results showed that pGTIOL effectively enhances the I/O performance in comparison with the master-worker I/O mode which uses the Geospatial Data Abstraction Library (GDAL). pGTIOL encapsulates the underlying parallel I/O routines, and provides easy-to-use interfaces for the parallel reading and writing of GeoTIFF data. Compared with other parallel raster I/O software packages, pGTIOL supports a wide range of data types, both the strip and tile data storage modes, and various domain decomposition methods. Most importantly, pGTIOL supports asynchronous parallel I/O, which allows multiple processes to read and write sub-domains of data on demand.Hence,it could facilitate dynamic load-balancing in application.

To solve the problems about public transportation models in which the passenger behaviors and their interactions with public transportation are rarely concerned, a concept of virtual public transportation environment and the vector representation of its elements is proposed. Meanwhile, a transportation agent model and a passenger behavior agent model were built with the MAS method. Furthermore, an algorithm was proposed to simulate transportations, passengers, and the temporal and spatial variations in public transportation operation. Then, a prototype system of virtual public transport environment was implemented. In the end, a small-scale public transport environment, which was composed by7 roads, 8 bus routes, 31bus stops and 10 000 rides, was designed as the experiment environment. It produced 1428 bus runs and 30 436 passengers'swiping card data of getting on and off buses. The experimental data was analyzed while comparing with the average passenger waiting time under different departure intervals. The results show that the total travel time distribution is consistent with the input data, and the average waiting time is reduced if reducing the departure intervals of buses. It proves that the above models can effectively simulate public transportation environments. As a result, the traffic managers and researches could benefit from the prototype system and models, and it is helpful for them to make rational decisions.

With the development of service industry and promotion of culture industry, urban leisure and entertainment industry have gradually become an important symbol and driving force for urban economic and social development. KTV is a typical representative of the urban leisure and cultural entertainment services in China. Based on the geospatial entity data and business statistics data, this paper studies the market structure, spatial distribution and spatial expansion characteristics of KTV facilities in mainland China, using the spatial data visualization and the statistical analysis of GIS technology. Results show that KTV services have been rapidly developed and widely distributed across the whole country. The spatial distributions of KTV services were analyzed at national, provincial and city levels respectively, and they presented distinct characteristics including regional differentiation, urban hierarchy divergence, planar equalization, and central agglomeration. The relations between the spatial distribution and the influence factors, such as regional economy, population, and culture, were also investigated. All types of KTV facilities expand spatially from east to west and from the center to surrounding areas. In addition, among all types of KTV facilities, the KTV chains follow the geographical diffusion principles according to social economic phenomena research, which mainly include characteristics of hierarchy diffusion and contiguous diffusion.

Accurately get the spatial distribution of soil salinization and the spatial location characteristics of its relationship with land use intensity can explain the reason of soil salinization from a perspective of land use intensity, so as to provide a reference to local planning and management. In this paper, taking Yinchuan Plain as the research area, we primarily studied the method of getting the saline soil's spatial distribution based on remote sensing images. Combined with the land use remote sensing mapping and with the support of statistical methods based on semivariance function and grey correlation theory, the visual expression of spatial location distribution characteristics are developed for land use intensity change, soil salinization change, and the respond relationships between each kind of saline soil and land use intensity in Yinchuan plain. The main conclusions are presented as follows: first, the development of Yinchuan plain had an agglomeration effect. Land use intensity change was closely related to the urban system structure, the distribution of road and channels and soil salinity. Second, the soil salinization change of Yinchuan Plain revealed a spatial distribution of entire alleviation but local aggregation feature. The response relationship between saline soil and land use intensity change was spatial heterogeneity. Third, the correlation coefficient between the saline soil level change and land use intensity change was 0.7781. The correlation degree between land use and saline soil were found higher in water and cultivated land, which showed that the land use could influence soil salinization distribution characteristics. Therefore, among all the land use types, water and cultivated land were important factors of influence to soil salinization. Generally, strengthen the awareness of environmental protection and cultivation will help reduce soil secondary salinization. Further improve the water conservancy facilities can help reduce groundwater salinity. Moreover, we can protect cultivated land to promote the sustainable development of agriculture.

The distribution of organic matters in tea garden soil shows an obvious spatial pattern. Methods to predict the distribution of organic matters in the study region using data from a limited series of sampling points is very important in studying the soil status of tea gardens, providing guidance to manage tea gardens, and improving tea quality and products. In this paper, we made a research on 4 famous tea planting areas in Jiangsu Province and Zhejiang Province, and we conducted a comparative analysis on the spatial heterogeneity of the organic matters in tea garden soil using descriptive statistics and geostatistics, which included the semi-variogram model and the spatial interpolation diagram analysis. Furthermore, we explored the spatial distribution characteristics of the organic matters in tea garden soil and its influencing factors. The results showed that: (1) the average level of the soil organic matters in all of the four study areas was favorable for tea growth. In addition, the average level of soil organic matters in Zhejiang Province was higher than that in Jiangsu Province. (2) The semi-variance function models proposed that a medium spatial correlation existed in the organic content of Xilong growing area, while a strong spatial correlation was discovered in the other three areas. The interpolation map showed that regions with high organic content in the two study areas of Zhejiang was had broader ranges than the other two study areas in Jiangsu. (3) We also conducted a qualitative analysis on factors influencing the spatial distribution of organic matters, based on relevant literatures, investigations and data. As a result, we found that the spatial distribution of organic matters in each area was determined by the structural factors, such as the soil physicochemical properties and the characteristics of landforms. Moreover, the random factors, such as human activities, business operation modes, tea garden management, and proper protection strategies, also had local impacts on the distribution of organic matters.

Flood is a frequently occurred disaster and it causes great harm in China. In order to effectively prevent, reduce and relief disaster, it is necessary to establish a flood event information model to represent and share flood information. By far, many scholars have studied a variety of event information models. However, the existed event information models mainly represent static information, and they are lack of the capability to handle dynamic process information. To solve this problem, a flood event model is proposed in this paper based on the flood emergence management stages and the dynamic process from the perspective of observation. To build up the model, this paper firstly describes the modelling considerations, including flood phases, observation, and ten types of primary elements for modeling. Then, we construct the flood event model as a ten tuple model based on MOF modelling framework with four layers, and encode the model with a method that maps the elements of the model to elements of the Event Pattern Markup Language (EML). Finally, we simulated an experiment for a flood case occurred in the Liangzi Lake in 2010 as an example to test the proposed model. In the experiment, the building process and the results of the proposed model at different emergence management stages are detailed. The experiment results show that the proposed model has following characteristics: (1) it establishes a model from the perspective of observation, since observation plays a decisive role in real-time disaster information acquisition. (2) The flood model was established by four emergence management stages, and the main tasks of each stage are different. (3) The flood model was modelled dynamically. The proposed ten tuple model itself is not dynamic, but the establishing process and its represented information are dynamic. The modelling process is modelled on real-time data streams, and it dynamically updates time-series data. The time series data in this model are generally the latest observations, which reveal the dynamic information of current flood. (4) The model is extensible and adaptable to ensure the suitability. As a conclusion, the model can represent flooding events and model dynamic flood information effectively, as well as provide a good approach to represent and share flood information.

Land-use change has been a key component for global environmental change. The conversion matrix is a fundamental tool in the analysis of land-use change. In order to obtain as much information as possible from the conversion matrix, two new patterns of land-use change, which were named as displacement and substitution, were proposed. Accordingly, the total change that characterized in an individual category is then divided into net change, displacement, and substitution. The calculation formulas for the displacement and substitution were also derived. The land-use change among eight land categories of Jinjiang watershed that locate in southeast China, was taken as an example to illustrate the proposed methods. The results show that great changes have taken place in the area from 1985 to 2006. The garden area, built-up land and unused land increased remarkably, while the dry land and grassland decreased, with the waters kept almost unchanged. The swaps between the above six land categories were relatively few, and the main format of change is in the pattern of displacement. Most of the changes in irrigated land and forestland happened in their spatial location swaps. However, for irrigated land, it was mainly displaced by the forestland or dry land; and for forestland, it was mainly substituted with garden area and grassland. The results also indicate that the new patterns—displacement and substitution, are helpful for the analysis of land-use change.

Virtual plant is a potentially powerful tool for analyzing plant growth processes and the relationship between plant growth and environment. In order to provide an intuitive representation of forest growth and be adaptive to forest management at a deeper level, the forest growth model should be integrated with 3D tree architectural model. Individual tree growth simulation is the foundation of the simulation of forest ecosystem. The aim of this study was to link an empirical forest growth model and a 3D architectural model to dynamically simulate growth processes of an individual tree. Individual-level simulation of Cunninghamia lanceolata was implemented by integrating a 3D parametric model and a distance-independent individual tree growth dynamics model. The 3D parametric model was created in ParaTree, a system developed by our work group. First of all, according to the morphological characteristics of Cunninghamia lanceolata, parametric modeling method is adopted to generate a 3D model. Then the tree height, diameter at breast height, height under branch, and the whorls of branches are predicted in the growth model based on a site quality, planting density and age. Geometric descriptive parameters of 3D tree model are then updated according to the architectural parameters. Finally, the parametric curve is applied to adjust stem diameter and tree diameter, the length of the branches, branching angle and so on to make the model change with tree growth. Taking the forest resources inventory data of Wuyi forest farm of Zhangping in Fujian for an example, we simulate the growth dynamics of Cunninghamia lanceolata and express the global morphological structure characteristics at each growth stage. The growth at average of individual trees in a forest stand was represented intuitively by the means. Linking the parameters of 3D model to some existing tree empirical growth models is conducive to reuse a lot of growth models .

Gridded population distribution data are increasingly expanding their uses in a wide range of fields, such as resource utilization, disaster response and relief, environment protection, and economic research. The enhancement of resolution with detailed precision is a perpetual topic in population gridding research. In this paper, a 100m gridded population dataset was established for Yan’an city by developing a method that distributed the population based on the land use data with improved settlement information. Data used here include township boundary data, township-level demographic data, land use data, TM image, town-village settlement point data, and DMSP/OLS nighttime light images. Two approaches were used to improve the detailed information of settlement distribution. First, we identify the rural settlement information from land use data and enhance the information by the village point data obtained from Google Earth. Second, we downscale the DMSP/OLS data by spatial interpolation. The sum of light emission, lit area and unlit area under different land use types in each town were counted to be used as the independent variables, and the statistical population of each town were used as the dependent variable. A stepwise regression method was adopted to simulate their relationship. Finally, the sum of night light emission, the unlit area of build-up area, the unlit area of grassland, and the lit area of farmland were put into constructing the ultimate equation. All variables were significant under the level of 0.01 and the coefficient of multiple correlation is 0.872. We estimated the population at township level for selected towns as a validation. Through using the equation, we found that the mean error between the estimation and the statistical population is lower than 5%. The above analysis suggests that the proposed modeling strategy is highly efficient. As a result, we calculate the weight and distribute the population through the equation in the formation of 100m grid, by taking township as the unit. In summary, the gridding method used in this study can obviously improve the output resolution and the distribution details. Also, the expression of the final equation is relative simple. As a conclusion, this paper has its significance in guiding the population gridding research in the county level areas like Yan’an city.

Along with the continuous development of computer technology, internet and wireless communication technology, digital map visualization, as the core of geographic information system, has been widely used. At the same time, with the increasing number of embedded software and hardware, a variety of heterogeneous platforms bring great challenges to the development of embedded geographic information system. Therefore, it is important to study the digital map visualization method for cross-platform purpose. Firstly, after comparing the differences of middleware between the embedded system and desktop system, this paper summarizes the characteristics of the embedded middleware, and analyses the platform differences and resource restrictions for digital map visualization in the embedded environment. Based on the concept of middleware, a cross-platform middleware of digital map visualization with three layers: EMD_MW was constructed. The middleware utilizes the operating system abstraction layer to prevent the heterogeneity from different embedded operating systems, and to abstract the operating system message forwarding and the graphic interfaces associated with the digital map visualization. Meanwhile, the model utilizes the framework layer to dispel the differences among data storage services, to improve the base graphic interfaces, and to provide relevant digital map display interfaces through the function layer. Then, the abstraction layer, service framework and function layer of EMD_WM were designed and realized. Finally, several engineering applications based on EMD_MW were presented. These examples indicate that, the embedded cross-platform middleware model for digital map visualization has a good cross-platform performance, and it can effectively solve the problem of digital map display on different embedded platforms.

Great changes have taken place in China's urban scale system during the last 30 years. The driving forces that cannot be ignored include following factors: the population urbanization propelled by its aggregation, the land urbanization driven by its revenue, and the economic urbanization promoted by GDP. Using the analytical tools of GIS integrating three factors of resident population, built-up area and economic output, we constructed Zipf-PLE model for a in-depth research on the spatial pattern of China's urban scale system. The result shows that: (1) in 2010, China's urban scale system is matured with completed levels of hierarchy, which is reflected by a relatively rational pyramid-shaped pattern with larger scale locates in the middle while smaller scale stays at the bottom. The urban scale system structure in the western region has the highest rationality, which presents a pyramid-shaped pattern with larger scale at the bottom and smaller scale at the top. The urban scale system structure in the eastern regions is relatively sound and contains the largest quantity of medium-sized cities, indicating a pyramid-shaped pattern with larger scale in the middle and smaller scale at both ends. The urban scale system structure in the central regions is featured by its incomplete urban system hierarchy, which lacks megacities especially, and presents a pattern with larger scale in both the middle and the bottom, while having smaller scale at the top. (2) The overall urban scale system in China at the provincial level is rational, with 90.32% of the provinces being moderately rational. Among all 27 provinces, except 4 municipalities, the urban scale system patterns of 8 provinces are inclined to disperse and the other 19 tend to concentrate. (3) Furthermore, we allocate the provincial urban scale systems in China into different categories according to their rationality rankings, which are: the high-level (with 11 provinces and municipalities including Beijing, Shanghai, Tianjin, Chongqing, Xinjiang, Heilongjiang, Guangxi, Gansu, Fujian and Jilin), the relatively high-level (with 12 provinces of Guangdong, Shanxi, Yunnan, Hunan, Guizhou, Liaoning, Jiangxi, Jiangsu, Zhejiang, Sichuan, Hebei and Henan), the medium-level (provinces of Hubei, Shandong and Anhui), the low-level (provinces of Hainan, Mongolia and Ningxia), and the irrational areas (provinces of Qinghai and Tibet).

Runoff nodes, which could be captured from every watershed on earth, are one type of the real geographical entities within the river-network. Generally, runoff nodes often locate at sites where lower grade of runoffs merging themselves into a more advanced trunk stream. It is clear that runoff nodes carry a lot of hydraulic and landform information. Although many reports have documents related to runoff nodes, the quantitative measuring researches, that concerning the geographical information of runoff nodes and taking advantages of valid theories or methods, are still rare. This may prevent people from further understanding the existence of runoff nodes in nature. Aimed to solve the aforementioned issue, this paper employs the Theory of Rough Sets (TRS) to develop a new landscape metric for perfectly characterizing the geographical features of runoff nodes. Firstly, according to current knowledge about runoff nodes, this paper extracts the potential information carried by runoff nodes. Secondly, this paper reviews some typical valid methods on how to extract runoff nodes from Digital Elevation Models (DEM). Thirdly, this paper presents the feature information index of runoff nodes (FIIRN) and illustrates the relevant computing procedures. Based on these researches and preparations, this paper carries out a case study of FIIRN for seven special regions from the Loess Plateau of China (which well represents the typical loess landscapes existed in the world). The experimental materials of DEM data are predominantly characterized with 5 meters of resolution. With the help of ArcGIS 10.1 software, this paper extracts all runoff nodes from the experimental sample regions according to their geometric features in the runoff network. Then, this paper computes the values of FIIRN using Excel 2003 and MATLAB 7.7. Surprisingly, the results show that FIIRN can effectively map the complete geographical information of a given watershed unit. Therefore, as we concluded in this paper, that FIIRN can play a valuable role for mining the information from watershed units in future. In fact, FIIRN should be considered as an optimal parameter for analyzing the morphological patterns of watershed units.

Nowadays, issues regarding to housing affairs can be easily dealt through online queries and transactions, which provide a brand new data source for researches about residential space. This article mainly focuses on the causes of variations in activeness degree for different second-hand housing areas in Nanjing, through web data mining and a series of kernel density estimations. Based on three typical case studies of the Hexi district, Daguang district and Confucius Temple area, this article summarizes the underlying influential mechanism for the second-hand housing activeness in Nanjing. Research result has shown that the second-hand housing in Nanjing has a structure of “one core with three blocks”, in which the Gulou and Jianye districts are considered to be the core. Meanwhile, the sales volume in districts with highly educated inhabitants, such as Xuanwu district which lies in the eastern part of Nanjing and Jiangning district which lies in the southern part, have a low degree of activeness due to the solidified and sophisticated residential space development. There are two main factors contributing to the differentiation of activeness in second-hand housing, which are summarized as the internal factor and the external factor. The multivariate regression analysis model suggests that the internal factor is consists of the housing price, the number of building stories, the percentage of greenery coverage, and the house decoration condition. The external factor is considered to be consist of the accessibility and quality of adjacent subway stations, schools and other supporting facilities and services.

Land change survey is an important survey for investigating national conditions and national strength. The purpose of land change survey are: identify the nationwide land use status and changes in the year of concern; maintain the accuracy and timeliness of national land survey data and the basic information of the comprehensive land and resource supervision platform; and meet the requirements of land and resource management as well as economic and social development. Officially released land change survey results are the basis for the implementation of planning, management, protection and reasonable utilization of land and resources, the strategic planning of national economic and social development, and other relevant special-purpose plans. There still are problems that need to be solved, such as how to ensure the authenticity and accuracy of land change survey results, how to improve the work efficiency of land change survey with new technology, and how to shorten the error modification time. The purpose of this paper is to evaluate the quality of land change survey database and analyze the causes of database errors. For a quantitative analysis of the changes of database quality in 2010, 2011 and 2012, comparative methods were employed. Methods known as Moran's I and local Moran's I were adopted to analyze the spatial dependence in observations of database errors among administrative units, and to reveal the change of spatial distribution and the anomaly characteristics of database errors in local areas. To be specific, five steps are required for quality evaluation and pattern analysis. Firstly, the descriptive chart of original errors at the county level is processed in batch transaction by software, and then is aggregated into database tables. Secondly, since the quality inspection rules were found inconsistent among 2010, 2011 and 2012, it is impossible to use a comparison analysis method, thus we preprocessed the data and acquired the common quality inspection rules for the three-year period. The third step is to use the comparison analysis method to assess the database quality from different aspects, including the defect levels, the main check items of errors and the spatial distribution. The fourth step is to define the database errors by observing through the global autocorrelation method in analyzing the land change survey of Hebei province, and obtaining the spatial distribution characteristics and the influential factors of database errors. Finally, the spatial pattern of the phenomenon was reflected and the causes of database errors were explained. The results showed that the quality of the database of Hebei province in 2012 have been improved significantly according to the number of errors, the defect levels and the spatial distributions in assessment. In addition, the distribution of Hebei’s database errors were high autocorrelated with the fluctuation of aggregation level, while the generation of local anomaly was usually derived from artificial error. It is concluded that throughout the quality analysis of the research database and its space distribution pattern in three years, we can evaluate the changes of database quality objectively and identify the causes of database errors effectively, therefore provide a forecasting and monitoring approach to new land change surveys.