The existing finite element numerical simulation method of groundwater flow has some defects in the three-dimensional visual spatial analysis and the expression of numerical calculation process and simulation results. In order to solve this issue, the key steps of the finite element analysis process including the conceptual model construction, spatial discretization, hydrogeological parameters extraction and initial condition assignment are taken into consideration respectively. Based on the finite element method and 3D GIS platform, the method and technique framework of the groundwater finite element numerical simulation under 3D GIS are proposed with the supports of GIS spatial analysis algorithms and computer graphics theory. In addition to describe the technique framework, the core algorithms’ implementation details are given and the complete process of 3D GIS groundwater flow simulation is presented. The groundwater simulation example demonstrates that the proposed method and technique framework are capable of simplifying the finite element analysis process and improving the calculation efficiency of the model. The whole technique framework can be integrated into 3D GIS platform, and furthermore the visualization of simulation process and calculation results can be achieved eventually.

The urban built-up area boundary is important basic information for urban studies, and is also the premise of the implementation of urban function space layout, the implementation of boundaries control. Accurate extract urban built-up area for urban construction, management and research has important guiding significance, but also reflects the city's comprehensive economic strength and the level of urbanization, one of the important indicators.The DMSP/OLS night light data has been widely used in the extraction of urban built-up areas. But due to the effects of saturated, diffuse, and low resolution problems, it is still a huge challenge to rely on the DMSP/OLS NTL mapping the urban built-up areas. In order to overcome the limitations of the data source itself, In this study, the application of hierarchical expert knowledge analysis, multi-source data extraction of the thematic information layer by layer into the extraction process, the construction of urban built-up area for the level of expert knowledge model to achieve the city built-area refinement extraction. The urban index （VANUI） was constructed by combining 250 m MODIS NDVI data with 1 km DMSP/OLS data. Based on the administrative boundary, the statistical area of the area is divided into the administrative boundary of each prefecture-level city, and the optimal segmentation threshold of each administrative unit VANUI feature image is calculated according to the regional segmentation method, so as to obtain 250 m urban boundary space information range. Meanwhile, Due to the low spatial resolution of the DMSP/OLS luminous data and the narrow range of light and light values, there is still a large gap between the optimal segmentation threshold and the built-up area. Therefore, this study proposed the maximum autocorrelation double threshold extraction method. The 30m Landsat 5 NDVI data were fused to obtain the maximum autocorrelation quadratic NDVI threshold in each 30m seed region by multi-scale segmentation of the regional threshold segmentation. According to the maximum autocorrelation threshold of each potential built-up area, each potential built-up area is revised one by one, and finally 30m urban built-up area is obtained. This paper takes the Beijing-Tianjin-Hebei region as the research area, the experimental results show that the total precision of extracting urban built-up area by multi-source remote sensing cooperative method is 92.9%, and it has higher validity and reliability in spatial distribution and statistical data. The results show that the results of the urban built-up area extracted by this method are not only the overall accuracy, but also the spatial extent of the visual interpretation, and the relative error of the statistical area in each prefecture-level city is small, which verifies the reliability and validity of the method in spatial distribution and statistical data, and avoids the error caused by subjective threshold selection. DMSP/OLS data can be used not only for urban area extraction, but also for the intensity and scope of human activities. Therefore, in the follow-up study, based on the identification of urban built-up area boundary, combined with the quantitative analysis of luminous data and evaluation of urban development area outside the expansion trend and internal dynamic changes for the DMSP/OLS luminous data to give full play to its effectiveness, Economic and historical values play a positive role in promoting.

Heatwave has become an extreme meteorological disaster which occurred frequently during the summer. Moreover, heatwave could evidently affect the healthy conditions of residents. Thus, study the spatial pattern of heatwave health risk would be helpful for us to prevent from and respond to the impacts of heatwaves. Using the historically meteorological datum of Xiamen, this study built a database of heatwave cases and analyzed the basic characteristics of heatwaves in Xiamen. Taking a heatwave event occurred in 2010 as a case, we analyzed the spatial pattern of heatwave health risk by using both the remote sensing data and the demographic data. It is concluded as the following statements. (1) The intensity of heatwaves in Xiamen is quite low, but its frequency is rather high. An intensive heatwave occurred occasionally. (2) The regions with high health risk are located in Xiamen Island, lying from the northeast toward the southwest. The regions with the highest healthy risk are located in the northern and southeastern Jiangtou sub-district, Huli district, and the most area of Xiagang sub-district and Siming district. (3) The human health risk pattern of Heatwave is associated with the spatial distribution of environmental and demographic factors. Generally, this study promotes and extends the scientific knowledge on the health risk of heatwaves.

It is very important to study the characteristics of spatial pattern and variation of soil nutrients and analyze the effect of topographical factors on the spatial distribution of soil nutrients for the effective use and management of soil nutrients. In this paper, the combination of GIS and Geostatistics methods were applied to analyze the spatial distribution characteristics and variation pattern of soil nutrients (organic matter, available nitrogen, available phosphors and available potassium) in the agricultural land of southeast hilly area of Fuzhou. We further studied the correlation between soil nutrients content and topographical factors (topography degrees, elevation, topographic wetness index, deposition and transport index and gradient). The results showed that: the range of organic matter, available nitrogen, available phosphors and available potassium contents were between 1.10~89.5 g/kg, 1.00~461 mg/kg, 0.300~298 mg/kg, 4.00~399 mg/kg and the range of variation coefficients were 35.3~99.0%, which belonged to moderate variability. There was obviously different in the spatial abundance of soil nutrients in the cultivated land. In most of the area, the organic matter and available phosphors content were abundant, available nitrogen content was a little above average level and available potassium content was relatively scarce. The nugget coefficient of organic matter, available nitrogen, available phosphors and available potassium were 32.0%, 37.3%,50.0% and 50.0%, respectively. They were medium spatial autocorrelation, indicating that they were controlled by structure and randomness. Spatial autocorrelation scale of organic matter and available nitrogen were large. They change smoothly in each direction (0°, 45°, 90° and 135°) when the step length was less than 0.3 km.and are isotropic. The variation of effective phosphorus and available potassium was small. Their direction of change was complex and they are anisotropy. These results suggested that the government needed to strengthen guidance of fertilization. Nitrogen fertilizer amount should be maintained and the potash should be increased reasonably. The organic fertilizer and phosphate fertilization should be decreased.. In addition, in the subsequent investigation, the setup of sample points should consider density and direction and appropriately increase the sampling of effective phosphorus and available potassium while nitrogen and organic matter and alkali solution sampling can be reduced based on the study.

Multi-source remote sensing data fusion is the development trend of remote sensing technology in depth. This paper analyzes in detail algorithmic application characteristics of multi-source remote sensing data from three levels of pixel-based, feature-based and decision-based fusion processings. Take Fengning County for example, specific applications of remote sensing data fusion methods in information extraction are illuminated. The data used in this study is firstly pre-processed, then the principal components of Landsat TM data in 1999 are analyzed, the first three principal components account for 97.8% of the total information, the resulted image of inversed principal components transformation is clearer and has more abundant levels. To extract information from remote sensing image, we select the fusion image from Landsat TM pan and multi-spectral bands after principal components transformation, color composition scheme of bands 4, 3, 2 and bands 5, 4, 3, and vegetation index and greenness index after tasseled cap transformation are analyzed, the remote sensing image information fusion with DEM and spatial data of GIS database can also improve the accuracy of remote sensing information extraction. Problems to be resolved and future direction of multi-source remote sensing data fusion are put forward.

Spatial-temporal trajectory classification aims at predicting the category of a spatial-temporal trajectory. The classification of spatial-temporal trajectories plays an important role in urban planning, personalized user recommendation and so on. The process of trajectory classification includes three stages: trajectory preprocessing, feature extraction and classification. This paper reviews the recent research progress on trajectory classification. Firstly, we introduce the process of trajectory classification. Then, the trajectory classification algorithms are classified into three categories according to the method of feature extraction, including the trajectory classification algorithm based on motion feature, the trajectory classification algorithm based on classification rule and the trajectory classification algorithm based on image signal analysis. We also discuss the basic ideas, advantages and disadvantages of these algorithms. Thirdly, we compare the existing classification algorithms according to the sensors, feature extraction and classifiers used in these algorithms. Finally, we introduce the challenges of the existing trajectory classification algorithms.

Land use mapping using remote sensing techniques supplies essential datasets for scientific researches including global climate change, regional sustainable development and so on. The evaluation information on the accuracy of the land use mapping determines the integrity, reliability, usability, controllability and shareability of the land use maps obtained by the applications of remote sensing techniques. In this paper, the methods, processes and results of multiple temporal land use mapping for China's coastal zone using remote sensing techniques were overviewed, and the land use maps in 2010 and 2015 were selected for accuracy evaluation. The validation samples were collected based on Google Earth and the confusion matrices were established for the whole coastal zone and its sub-regions, respectively. Then, the overall accuracy and Kappa coefficient were calculated. Main findings are as follows: (1) Results of land use mapping in 2010 and 2015 using remote sensing techniques achieved high accuracy. For the entire coastal zone in China, the overall accuracy came to 95.15% and 93.98%, with the Kappa coefficients of 0.9357 and 0.9229 in 2010 and 2015, respectively. (2) The accuracy of land use mapping in China's coastal zone exhibited obvious regional differences. The best accuracy was found in the coastal area of Jiangsu province in 2010, and very high accuracy were found in the coastal area of Hebei-Tianjin, Shanghai city, Hainan province and Taiwan province in 2015, while the worst accuracy was found in the coastal area of Fujian province in both 2010 and 2015. (3) The accuracy of land use mapping in China's coastal zone exhibited obvious typological differences. The very high accuracy (both producer precision and user precision) were achieved for farmland, forest, grassland and saltwater wetlands, and the high accuracy for built-up, freshwater wetlands and human made saltwater wetland, while the worst accuracy for unused land. (4) The misclassification between cultivated land and forest land, construction land and grassland is quite significant. Inland water bodies were easily misclassified into cultivated land, forest land and construction land. Artificial salt water wetlands were easily misclassified into cultivated land and construction land, and unused land. It was easy to mistakenly classify the unused land as cultivated land. These are the issues that should be paid more attention during the continuous update of the land use maps in the future. This study provides supports for the dynamic monitoring and scientific researches on coastal land use changes.

Land Use and Land Cover (LULC) classification products play an indispensable role in ecosystem assessment, climate change simulation, national geographical condition monitoring, and macro-control policy analysis at the global scale; consistency analysis is the precondition of applying various LULC classification products. This paper assessed the area consistency and spatial consistency of five LULC classification products - MCD12Q1-2010, GlobCover2009, CCI-LC2010, FROM-GLC2010 and GlobeLand30-2010- in the global coastal zones. The five products were compared in terms of the deviation coefficient, correlation coefficient, error matrix, and spatial confusion of LULC types. The main findings are as follows: (1) The spatial patterns of LULC in five products demonstrate relatively strong overall consistency, but can have significant local inconsistency. (2) The five products are qualitatively consistent yet quantitatively inconsistent in classifying the LULC in the global coastal zones ? in terms of structure, water ranks top one, followed by forest and unused land, next are farmland, grassland and shrubland, and lastly wetland and artificial surface, yet the exact area of each LULC type differs among different products. (3) For the correlation coefficient, overall accuracy and Kappa coefficient, MCD12Q1-2010/GlobCover2009 have the minimum values, 0.8814, 67.46% and 0.5748, respectively; while GlobCover2009/CCI-LC2010 have the maximum values, 0.9869, 81.50% and 0.7505, respectively; it is because GlobCover2009 and CCI-LC2010 obtained from the same production organization have the same classification system, while MCD12Q1-2010 is different from GlobCover2009 in terms of the production organization, data source, classification system, and classification method. (4) For the spatial confusion/misclassification between any two different products, grassland, shrubland, and wetland have the highest mix-up ratios, followed by farmland and artificial surface, and lastly forest, unused land, and water; this difference is because forest, unused land, and water have distinctive spectral characteristics and clear spatial textures, while grassland, shrubland, and wetland have similar spectral characteristics and fuzzy spatial distributions. (5) There are 28.81% land area in the global coastal zones with relatively low consistency, i.e., with severe spatial confusion; specifically, the misclassification of farmland, forest, grassland, shrubland, wetland, and unused land has direct influence on the spatial consistency of the five products. This paper is hoped to serve as a reference of selecting data from the five available LULC products for researching coastal zones.

Energy fixation and organic matter production of forest ecosystem were dominated by plants, which are impacted by their growth environment. The forest ecosystem has the characteristic of long life-span, which makes its research laborious and costly using field experiment. The virtual geographical environment can provide a new way for its research due to its character of trying to exceed the limit of time and space. In order to estimate the biomass and evaluate relationships among tree and environments, an L-systems based functional-structural model was developed for simulating the development of tree architecture, taking into account tree physiology and environment. The L-systems was used to represent the morphological development of tree. The basic growth unit was described in line with the development of young Chinese fir (Cunninghamia lanceolata). LSTree system integrated the photosynthesis, photosynthates allocation and morphogenesis models. The spatial distribution of solar radiation in tree canopy was simulated for calculating photosynthetically active radiation (PAR) of each leaf obtained. PAR is a key parameter for photosynthesis model to estimate biomass. The dynamic growth of an individual 3-to-4-year-old Chinese fir in Fuzhou was simulated in growing season. Based on the 2010 Fuzhou weather and Chinese fir photosynthetic characteristic, net photosynthesis rate and product were calculated for each stage. The amount of photosynthates allocated to the growth of new segments and leaves or branches and leave amplification are based on source-sink theory. The growth of tree is driven by available photosynthetic products after respiration losses were accounted for. The morphogenesis change in the young Chinese fir in response to environment was simulated dynamically in three dimensional representations. The result of net photosynthesis was compared to the previous field observation research, and it showed the simulation result was reasonable. The methodology has promising benefits to depicting the interaction of plant and environment, which will be valuable for estimation of organic matter production too.

The world's largest dam project and Chinese Western Region Development project was implemented in recent decades in the Three Gorge Reservoir Area (TGRA). These human activities lead to and influence widespread cropland change. In this study we used remote sensing data for dynamic monitoring of cropland in TGRA over 15 years before and after the Three Gorges Project and found that cropland plantation index become 0.25 in 2007 in TGRA, cropland of 0.069 hectare per capita in 2007 is lower than 0.089 hectare per capita of critical line based on estimate of the national total cropland control of 18 billion Mu (1.2 billion hectare). Cropland lost 59 655 hectare during the Three Gorges Project construction, that is to say, annual loss of cropland is 3 977 hectare. With the change of cropland, the ratio of the cropland occupied to the cropland reclamation is 26∶1, such an unbalanced situation means a rapid decrease in land capacity. Meanwhile, high-yield cropland accounts for 61% of cropland loss, resulting to a decline in entire cropland quality. It aggravated the deterioration between cropland supply and food requirement. However, the urbanization process decreases rural population and alleviates the pressure of cropland resources per capita. The driving forces of cropland decline included urban development, "Grain for Green" Project, reservoir submergence and orchard plantation, among them urban development is a key factor. The reservoir submergence accounts for 16% of total cropland loss. Up to now, cropland on slopes more than 25 degree accounts for 20% of total cropland area, that means a high risk of serious soil erosion. As for the long run "Grain for Green" Project which aims at improving the ecological environment, there is still many to do in the future.

The spatial distribution of population at fine-scale has increasingly become research hotspot and a difficulty issue in the field of population geography. It has practical application value and scientific significance for relevant researches, such as disaster assessment, resource allocation and construction of smart cities. The population is concentrated in the urban area. Revealing the population distribution difference in this area is the core content of spatializing population data at the fine scale. In this paper, the urban area of Xuanzhou District was selected as the research area. The population distribution vector data at residential building scale was established by proposing a spatialization method based on urban public facility elements. The method classified residential building patches. And it treated residential building patches as population distribution locations in geographical space with community boundary and community-level demographic data as the control unit. A multiple regression model of patch area and population was constructed. The spatialization method used in this study can reveal the detailed information about the population distribution in urban area. Results show that: ① The population distribution data, obtained by adopting urban public facility elements, is proved to be high accurate and reliable. The number of patches with estimated population in a reasonable range is 35.4% of 779 residential building patches. And the proportion of patches with relative errors of ±20% in population estimation is 61.2%. Moreover, the Chengdong community and Sijia community served as accuracy verification units, the absolute relative error of population estimation in these communities is less than 9%; ② Urban public facility elements, especially primary and secondary schools and kindergartens, vegetable markets and fruit shops, are important factors for accurate estimation of population within a residential building. Their estimation accuracy of number of people is high ifor multi-storied building, but lower for moderate high-rise building.

Marine GIS has become one of the important developing domains of GIS sciences Both scholars in GIS and in oceanography are interested in it The basic representation is considered as one of the most important problems This article presents a data model to solve the problem It includes three database: basic database, data warehouse and database for marine phenomena; two data analyzing mode: data pre disposing and feature analyzing It uses multi level extended grid data structure with two kinds of global grid scheme One is equal angle, the other is equal area grid scheme They have some new marine chara cteristics.

Path planning is a process to find the optimal path from the starting node to the destination node.Tens of algorithms have been designed to resolve the shortest path problem,in which the Dijkstra algorithm is always thought to be the most mature and classical one.However,its higher time complexity greatly restricts its practical application.Besides,for most path planning algorithms,the road network is considered as an ordinary plane network and the spatial distribution characteristics are ignored,therefore,the path planning algorithm can not do well in real road network.In order to improve the searching efficiency of the traditional Dijkstra algorithm and to meet the requirement of real-time vehicle navigation,a path planning algorithm based on SuperMap is designed by utilizing the network editing function of SuperMap GIS platform.Firstly,with the spatial distribution characteristics,a road network is built in SuperMap.In this process,we take three-dimensional transport and one-way road network into consideration,making the road network built in SuperMap able to reproduce the real road network.For three-dimensional transport,we set the parameters of non-broken lines and make sure the roads not in the same plane have no intersections;for one-way roads,the forward resistance and reverse resistance are set with different weights.Secondly,in order to improve the searching efficiency of the traditional Dijkstra algorithm,we propose a method to restrict the searching area.According to the coordinate relationships of the starting node and the destination node,we create a hexagon area,which contains the staring node and the destination node,as the restricted searching area,and make the algorithm able to search the shortest path within the restricted searching area on the theoretical basis of the classic Dijkstra algorithm.Thirdly,based on the actual needs,the path planning algorithm with certain constraints is designed.The constraints are prohibit a certain way and must pass through a certain point.At last,we apply the algorithm proposed in this paper to urban road network and compare it with traditional Dijkstra algorithm.The results show that,due to the searching area is restricted reasonably,the two algorithms get the same shortest path,but the time spent by the algorithm proposed in this paper is much less.Besides,the algorithm proposed in this paper can do well in path planning with constraints.Thus,the improved Dijkstra algorithm based on SuperMap GIS has a strong practicability,and can be used in real-time vehicle navigation.

This article estimated the precision of the precipitation simulated by 15 IPCC AR5 (the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, IPCC AR5) GCMs (Global Climate Models) and the multi-model ensemble (MME), based on the observed precipitation from 660 stations in China during 1996 to 2005. We firstly extracted the model simulation value at the corresponding position of the meteorological station, using the bilinear interpolation method, and took the average value of different models at the same station as the multi-model ensemble simulation value, then estimated the precision of the precipitation simulated by 15 IPCC AR5 GCMs and MME based on the observation of meteorological station. There were four evaluation parameters, including Corr (correlation coefficient), Bias, MRE (Mean Relative Error), and RMSE (Root Mean Square Error). Results show that the biases of the average daily precipitations simulated by IPCC AR5 GCMs present a gradually downward trend from northwest to southeast, and the RMSEs show a gradually increasing trend from northwest to southeast, while MREs in the east are less than those in the west. 82.3% of the average daily precipitations simulated by MRI-CGCM3 have relatively small biases, ranging from -0.5 to 0.5. The precisions of average daily precipitations simulated by BNU and MIROC-ESM are lower than that of others. Compared with other models, the MME simulation has the largest percentages of which the correlation coefficients are more than 0.5, MREs are less than 0.5, and RMSEs are less than 4mm, which accounted for 64.8%, 25.8% and 86.4% respectively. And the percentage of the biases ranging from -0.5 to 0.5 is relatively large, which is 56.7%, indicating that the simulation precision of MME is better than that of any other GCMs, and the MME can reduce the uncertainty of a single GCM simulation in future scenarios. Therefore, it is more scientific and reasonable to select the precipitation simulated by MME as the climate change condition, while studying subjects related to climate change.

Land surface temperature (LST) and fractional vegetation coverage （FVC） are important indicators of ecological environment changes. Studying the temporal and spatial variations of LST and FVC as well as their interaction in Fujian Province are of great significance to the evaluation of ecological environment construction and improvement of regional ecological environment. In this study, the temporal and spatial variations of LST in Fujian Province and the interaction between LST and FVC are analyzed, based on the reconstruction time series data of MODIS 11A2 LST and 13Q1 NDVI from 2001-2015. The results showed that: (1) The overall LST in Fujian Province presented a slight downward trend from 2001 to 2015, and the downward trend of LST is more pronounced after 2010. The spatial distribution of LST and FVC had a good negative correlation consistency, which implies the LST value is lower in the higher area while the LST is higher in the lower FVC area. (2) LST is negatively correlated with FVC, DEM and latitude. And their negative correlation was increased or decreased regularly with the change of months in a year .The negative correlation between FVC and LST was higher in summer and became lower in winter with the correlation coefficient reduced from 0.7 to 0.4. (3) The decreasing trend of LST with the increase of FVC is piecewise linear and has an obvious "FVC inflection point". In front and behind "FVC inflection point", the decreasing trends of LST with the increase of FVC are "slowly first and fast afterwards" in summer and "fast followed by slow "in winter. Moreover, the difference of LST decreasing rate with the increase of FVC becomes smaller in spring and autumn. In summer, when FVC is greater than 0.4, the LST can reduce about 0.77 °C with FVC value increase 0.1, and the cooling effect is about twice as much as that when FVC is less than 0.4. Therefore, if we want to effectively reduce LST in summer, we should make the surface vegetation cover more than 40%。Only in this way can vegetation play a better role in cooling. (4) From January to August, the negative correlation of FVC on LST has a lag, and vegetation change has a greater impact on the spatial and temporal distribution of the next month's LST. This study has a certain significance for the construction and evaluation of ecological environment in Fujian Province, and provide an important reference for the development of vegetation to suppress regional high temperature.

Terrain position is the basic morphologic feature on the surface of the Earth. The classification and extraction of terrain position have been widely applied in many research fields such as landform evolution, digital soil mapping and landscape ecological mapping. Proposed by Kang X et al. (2016), the multi-scale Geomorphons method maps terrain position by recognizing the morphology of each interest cell in a DEM according to its relative altitudes within the neighboring window. Multi-scale Geomorphons method can avoid the shortnesses of other classificaton methods, which are caused by different terrain attributes and a single analysis scale. However, there are still some drawbacks in the multi-scale Geomorphons method. For example, the classification results are fragmented and the domain of the analysis scale is difficult to determine. To solve the above problems, this paper presents a new method to classify terrain position, which is based on object-oriented segmentation and multi-scale Geomorphons. First of all, we propose an approach of determining the domain of optimal analysis scale of the multi-scale Geomorphons method. Then, the multi-scale segmentation and classification methods are constructed according to the initial terrain position data via the multi-scale Geomorphons method. At last, the presented method is evaluated by the experimental data of the DEM with 5 m resolution in the loess plateau region of northern Shaanxi. The experimental results show that: (1) the method of mean change-point analysis can effectively solve the problem which is difficult to determine the domain of the analysis scale of the multi-scale Geomorphons method. The domain of optimal analysis scale of the sample area is 5×5 to 33×33 cells. (2) The layer of each terrain position type with the value 0 for non-type cells and 255 for type cells is suitable for multi-scale segmentation. The parameters (i.e. scale, weight of shape and weight of compactness) for multi-scale segmentation have deep influence on segmentation results. There is optimal segmentation parameters for a experimental region. There is optimal segmentation parameter for an experimental region. (3) Comparing with the multi-scale Geomorphons method, the classification results of the present approach are more integrity and reasonable in the aspects of morphology correspondence and geological interpretation.

With rapid development of city construction,emergency events that endanger national security and people's safety occurred on occasion.It is necessary to establish an emergency management system and comprehensive emergency information system.Pipe analysis is a main application of GIS in the City Emergency Management Model.We can manage urban underground pipeline network and store information into computer orderly for data updating and resource sharing.The pipeline data in Guangzhou higher education mega center are used to demon- strate the application.A city emergency management model is built in the study by including three analysis modules (section analysis,vertical distance analysis,and analysis of pipe burst),and Guangzhou higher education mega center is selected as a study area for the three analyses by the visualization platform,By studying the Guangzhou higher education mega center pipeline network the authors analyze the three modules on the scope of application at the same time.The administrators of the pipe management can also make analysis of pipe burst,which is the most important spatial analysis function in pipe network analysis.The three modules of the emergency management model can be applied in pipe design,construction and service.

With the advance of the society and economy,Landuse is changing rapidly.Which results in the difficulties in timely dynamic monitor and updating the information of land use using traditional methods.Therefore,A better method to solve this difficulity.This paper discusses the principles and methods for dynamic monitoring landuse changes and timely updating the database of landuse using the morden spatial information technology,which are called '3S' technology, and provides the system development model and technique system by studying on the application principle about implementing dynamic monitor and updating for land use change by combining RS and GPS. Change data delamination and integrating analysis,object-oriented superposition-updating process and establishing the data fusion index are key technologies.

Real-time and accurate short-term traffic flow prediction, a critical technical problem in traffic control and guidance which is challenging and needs to be solved urgently in related research fields and engineering practice, still remains because of the hardship caused by the uncertainty and the temporal variability in traffic flow datasets acquired in different times. In order to improve the performance of the short-term traffic flow prediction, a new method based on similar data aggregation techniques and a modified KNN algorithm with varying K-value (KNN-SDA) was proposed and the related algorithm was also implemented and tested on actual measured datasets in this paper. Firstly state vectors were generated from the preprocessed traffic flow datasets by calculating the optimal time delay with the help of the mutual information theory. Each of our state vectors is composed of two parts, the first one of which is a regular state vector and the second one of which is a modified state vector which makes a contribution to a higher similarity between our state vectors and those in training datasets. Subsequently a historical traffic flow database of temporal series was constructed on the basis of results mentioned above for further experiments. After that, the proposed similar data aggregation techniques were applied to aggregate and clean data to obtain 144 training data sets in different times from historical traffic flow database, which would effectively improve the prediction accuracy and efficiency of the proposed algorithm. At last, the optimal K-values, each of which corresponded to a moment, were determined through the cross validation method. So far, the overall process of the KNN-SDA algorithm with varying K-value has been completed. In order to verify the performance of the proposed method, we compared the experimental results derived from our method with those from three other ones. It turns out that the KNN-SDA algorithm with varying K-value proposed in this article can improve the prediction accuracy significantly and ensure high execution efficiency as well.

Geospatial data is a kind of strategic information resource and is widely used in economic,social and environmental applications.GIS vector data is closely related to the overall situation of socio-economic development and national security due to its high production cost and high precisions.In recent years,researches about copyright protection of GIS vector data mainly focus on copyright marking techniques.To meet the requirements of copyright protection for spatial data files,a real-time copyright protection scheme for spatial data files is proposed in this study,based on the Copyright Marking technology,especially on the Digital Watermarking technology which was only used for the authentication,file system filter driver technology and encryption technology,which can be used for dynamic encryption and decryption of data files and real-time detection of copyright marking.This scheme achieves the purposes to keep confidential,detect copyright marking in a real-time way and control access.In addition, it lowers the limitations on the capacity of copyright marking information and the robustness of embedding algorithms.

The new generation of spaceborne laser satellite ICESat-2 (the Ice, Cloud, and land Elevation Satellite-2) of NASA (National Aeronautics and Space Administration) has adopted a newly designed micropulse photon counting system, which is the very first time that this technology gets applied in the space environment. Thanks to the high sensitivity of single photon detection technology, it can be seen from the currently released data product (both from the airborne simulators and the simulation data) that there is huge noise in the atmosphere and even below the ground. Therefore, preliminary research on these relevant experimental data to investigate the methods for separating signal photons from noise photons are important for the future applications. MATLAS data, which simulate the expected performance of the ICESat-2 ATLAS (Advanced Topographic Laser Altimeter System) instrument, was chosen to test our machine learning-based approach from two test sites in Oregon and Virginia in the United States. We first derived 12 features, such as the kNN (k-Nearest Neighbour) distance, based on the characteristics of photon point clouds data. Then we applied feature selection techniques by ranking variable importance using Random Forest. Three most representative features were chosen according to the variable importance ranking and we built a Random Forest classifier trained by the sample points we had selected. The established models were further applied to the whole study area. The final classification results indicate that the classifier we constructed had good performance to distinguish signal photons from noise photons. In terms of the mean values of the statistical indicators in the test sites, the overall classification accuracy was 96.79%, and the Kappa coefficient was 0.94. The producer and user accuracies were 97.1% and 96.8%, respectively. Additionally, the results show that our method not only worked well on data of relatively lower noise rate on flat terrain surfaces but also achieved good results for those with higher noise rate on complex terrain surfaces. To conclude, our method showes good potential to be applied to larger areas, for especially the classification of the photon counting LiDAR data in the future.

Based on the fact that the urban and regional geographic information development is quite uneven in China, this paper introduces an idea to measure the levels of geographic information development in urban areas using methods of questionnaire survey and case study. The authors discuss the natures and characteristics of geographic information from multiple perspectives, and present several development indicators such as professional and related organization, data investment and budget, data production and supply, data quality and standard, information infrastructure, related law, policy and regulation, application and benefit, and degree of data sharing. The related development degree index, questionnaire design, and case study design should consider these indicators carefully according to the research purpose. Finally, it is suggested that the government administrators and / or professional organizations should conduct a nationwide evaluation of urban geographic information development and formulate general strategies for China's long-term urban geographic information development and application.

Urban sprawl is a common problem in the process of rapid urban development. Due to differences in economic systems and other aspects, the characteristics and driving factors of urban sprawl in China are quite different from those in Western countries. The urban sprawl in China is accompanied by the disorderly development of land in the process of rapid urbanization. Based on the summary of domestic and international theoretical and empirical research, this paper chooses the elasticity of urbanized land to urbanized population to characterize the urban sprawl. This article analyzes the urban sprawl of 214 prefecture-level municipal districts from 1996 to 2014, and summarizes the following characteristics of its sprawl tendency: stable sprawl, adjustable sprawl, steady and high-speed sprawl, steady and low-speed sprawl. We summarize the following characteristics of its sprawl intensity: no sprawl, general spread and highly sprawl. In addition, we construct the panel model to explore the driving factors of urban sprawl from the aspects of the industrial structure, the government expenditure, the education development level, the traffic development level, the globalization level and market-oriented level. The results are as follows: (1) the issue of urban sprawl has a path dependence. Under the guidance of the development program with rapid economic growth, the high level of sprawl will continue for the rest of the year. (2) In the urban development mode oriented by economic construction, the development of secondary sector will significantly aggravate the urban spread. However, by promoting the development of the tertiary sector, local governments can attract foreign investment to optimize the structure of economic development and alleviate the problem of urban sprawl. (3) The influence of road construction, marketization level and college education level on the spread of cities is small or insignificant. Finally, we summarize the types, drivers and path dependence of urban sprawl and put forward policy proposals to control the urban sprawl from the perspectives of industrial structure and development.

Similarity measuring of spatial topological relations is the important part of similarity measuring of spatial data, and also is the basic and key technology of spatial data retrieval and spatial scene query. Its meaning is to measure the similarity of topological relationships between multiple data entities in different sources, different sources scales of the same region. Common topological relations have been abstracted into nine topological predications. Current researches mainly focus on the topological relations similarity measuring between two simple entities, but mostly do not involve topological relations similarity measuring for the entire data sets, as well as the complex line targets. In this paper we present a method of measuring simple topological relations based on 9- intersection matrix, that is, the distance between two 9- intersection matrixes as the simple topological relations distance to measure the differences between two simple topological relations, so that we can get a simple topological relations similarity. Then considering the quantity similarity and dimension similarity between entity sets, we can get the simple topological relations similarity measuring model between entity sets. In this paper we establish a similarity measuring model of complex topological predication by using the strategy of decomposing- combination based on the simple topological relations similarity measuring model. Firstly, the complex topology relationship is broken down into a number of local topological relationships. Then through a combination of local topological relations similarity, we get the complex topology relationship similarity measuring model. At last, the method is used to measure similarity of different scales and different sources data. Experimental results show that the selection of cartographic generalization impact the topological relations similarity between entity sets mostly, and other factors with smaller impacts to the experimental data in this article. Experimental results also demonstrate that the topological relations similarity can be used to measure the changing degree of topological relations caused by the cartographic generalization.

This article discusses the method of using Wavelet Transform and Mathematics Morphologic Subject to extract the canal of the area objects on the high resolution remote sensing image. As the experiment showed, after the veins partition of the images using the Wavelet Transform, the habitat extraction on the high resolution remote sensing image can be implemented by using the sorts of operators combined by the basic operation of Mathematics Morphologic Subject, choosing the right structure element and the vector tracking, the result of the method can be directly used in the application of GIS.

Tu" in Chinese words, means maps representing spatial information in graphics , also including images, illustrates and other graphic forms of representing spa tial informatic;"Pu"is a system built according to thing's characteristics or time series. Geo Informatic Tupu has two characteristics with graphics and pedigree. Formed from a great deal of geo information in digit through graphic thinking and abstract generalization, Geo Informatic Tupu is a means and method of using computer multi dimensional and dynamic visualization technology to display and reveal the spatial configuration and spatial temporal change rule of earth system and its elements and phenomena. Five parts are discussed in this paper, they are: 1. the basic concept of Tupu; 2. the discussion of Geo Informatic Tu pu; 3. the basic process and steps of building Geo Informatic Tupu; 4.the example of Geo Informatic Tupu complex Informatic Tupu of natural landscape in China. 5. the meanings of and prospects for Geo Informatic Tupu.

The Longshoushan uranium metallogenic belt in Gansu Province is an important uranium metallogenic belt in China. Jiling uranium deposit is a representative alkali-metasomatism type uranium deposit in Longshoushan metallogenic belt. There are a wide variety of alterations in Jiling deposit. And these alterations have close relation to the uranium mineralization. The airborne hyperspectral technique can be used to obtain the surface alteration, structure and lithology distribution information of Jiling uranium deposit from a macroscopic perspective, which provides a basis for the uranium and polymetallic mineral exploration in Jiling deposit and its adjacent area. In this article, CASI/SASI/TASI airborne hyperspectral remote sensing techniques have been applied to the identification of hydrothermal alterations in Jiling alkali-metasomatism type uranium deposit as well as its adjacent district in Longshoushan area, Gansu Province. A variety of alteration minerals have been identified including alkali-feldspar, hematite, tremolite, medium-Al sericite, kaolinite, quartz and so on. These minerals are closely related to the alkali-metasomatism hydrothermal action in Jiling deposit. Besides, comprehensive analysis on alteration mineral, structure and lithology information in Jiling uranium deposit has been made. Study shows that the alteration minerals such as alkali-feldspar, tremolite, medium-Al sericite and quartz separately represent the different stages of hydrothermal alteration process in Jiling uranium deposit and its adjacent area, namely the early alkali-metasomatism stage, the middle neutral-metasomatism stage and the late acid-metasomatism stage. The main channel for alkali-metasomatism hydrothermal action is the composite of regional unconformity surface, deep and large faults, and contact zones of different lithologic units. The uranium mineralization zone in Jiling deposit is controlled by Malugou fault. In the uranium mineralization zone, tremolite, medium-Al sericite, and silicification are evident. And these alteration minerals have close relation to alkali-metasomatism in Jiling deposit. According to the airborne hyperspectral remote sensing charateristics in Jiling deposit, the main prediction criteria for the prospecting of alkali-metasomastism type uranium deposits in the Longshoushan Mountain are proposed. These criteria are of great significance for the prediction of new favorable uranium exploration areas and the new evaluation of old uranium mineralization stations and anomalies in the Longshoushan area.