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.

This paper discusses the information quality-index of the space governance in digital agriculture.Digital Agriculture space governance originated in agricultural development in the renewal and transformation of land structure,any of the agricultural modernization and transformation planning and implementation,we need space admittance for updating project approval and space management control decision-making evaluation.Based on the evaluation of agricultural modernization and transformation,the establishment of access to space admittance and space management decision-making evaluation index system was realized.Through analysis of the factors affecting data quality,it is designed to the quality index system of the space governance in digital agriculture.

GML(Geographic Markup Language) is gradually accepted and widely used as an encoding,storage and exchange format for spatial information,and it offers a powful tool for implementing spatial information sharing and WebGIS development. As a graphic file format standard in the network era,SVG(Scalable Vector Graphic) represents graphic transmission development direction on the web,which integrates vector graphic,bitmap image and plain text merits and is naturally compatible with the network environment,so study on GML and SVG-based WebGIS and its application will have extensive practicality and application value. In this paper,GML and SVG are discussed firstly,especially in the role of open WebGIS,then an open WebGIS architecture is put forward which uses GML to store and integrate geographic information and using SVG to implement web display and operation for geographic information. Finally,taking a campus map issuing system as an example,an open WebGIS application system is set up and discussed.

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.

The high-resolution DEM and DOM data is an accurate description of the topography and geomorphology, and it is also an important source data for landslide information extraction. At first,according to the requirement of landslide information extraction,we use the UAV platform equipped with mini SLR camera combined with the GPS data measured in the field, as the image acquisition method. According to the characteristics of the UAV images, we use the basic principle of photography measurement and computer vision algorithms to obtain the high-resolution DEM and DOM images, which greatly preserves the rich spectral and texture information. Then, with the help of the ESP auxiliary tool we get optimal segmentation scale of the DOM. Based on the fuzzy classification and SVM algorithm to construct a decision tree, which we used to achieve the object oriented classification and information extraction. Finally, according to the spatial feature and distribution of study area we determine the high risk area. By the morphology and texture analysis and accuracy assessment of the landslide area, we show that the producer’s accuracy and user's accuracy of the landslide area are 84.65% , 91.44%. The result proves that the UAV remote sensing has a high value in the field of landslide information extraction.

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.

自然和人为的灾害每年都使远东的中国和她的周边国家蒙受了巨大的经济损失。为了能快速地对这些灾害作出反应以减少损失,有效和及时地从外层空间监测灾害已成为了一项迫切的国家需要。为了改进现行系统的覆盖范围和覆盖周期,曾建议采用地球观测卫星网。然而,常规遥感卫星的高成本至今还使得这项建议难以实施。萨瑞大学的萨瑞卫星技术有限公司(SSTL)已经研制了一套性能高、寿命长的微型卫星,该卫星利用先进的对地观测有效载荷,具有较强的星载处理能力。利用该套卫星就可以极低的成本获得从空中对地球的常规观测。每颗微型卫星只需费用约250万美元,因此,投资不到1800万美元就能构建由7颗卫星组成的卫星网(星座)。微型卫星重量轻、体积小,只需一个小的发射器就可以把整个网发射到低地球轨道中。

Over the past two decades, with rapid urbanization in Guangzhou, urban fringes experienced drastically land use changes. In this paper, taking the Extend South Area of Guangzhou as a typical example of urban fringe, based on GIS (Geography Information System) and RS (Remote Science) technology, land use vector of the study area in 1990, 1995, 2000 and 2005 were interpreted from Landsat TM images. Dynamic degree, fractal dimension and stability index of each main land use type in each year were calculated. Results showed that: from 1990 to 2005, land use of the Extend South Area of Guangzhou experienced obvious changes under the strong forces of urbanization of core area in Guangzhou. According to the change characteristics of land use, two phases of study period are followings. Firstly, from 1990 to 1995, the structure of land use changed tempestuously. In this period, the increase of construction land and decrease of farmland was the main process, with great increase of fractal dimension and decrease of stability index. Secondly, from 1995-2005, increasing speed of construction slowed down, farmland and forest land started to increase, and increase of fractal dimension and stability index became slighter, regional structure of land use experienced a beneficial development.

Logistics essentially refers to material entities movement process with distinct spatial measurement and spatial characteristics, where integration and application of spatial information techniques and other modern techniques of logistics management are needed. This is a new interdisciplinary research fields where to extent spatial information services combined with web services and geospatial analysis to the area of logistics management, and then integrate the concept of spatial information services into modern logistics services system to carry out logistics oriented spatial information web services access, integration and application. What's more, the key point to analyze logistics spatial phenomenon from the geographic perspective. Based on OGC web service framework, this paper we have put forward design and built the architecture of logistics spatial information services mainly include the mechanism for service integration, high-efficiency call and service composition and the model of integration based on web services, which clear its inherent elements and the relationship. Besides, we designed and developed the mechanism for service composition based on Net-Petri and Logistics Web of web service engine, which resolved the problems of dynamic access, high-efficiency call and real-time integrate to the logistics spatial information services. This work provided a new way and measure to the spatial information services being further developed and applied in the logistics area. By this way, even though the logistics information system constructors don't have a professional GIS background, they can also call spatial information service in their own programs. According to our study, the means of techniques of integrating and applying the logistics spatial information services, which achieve the dynamically composited and collaboratively integrated effectiveness and the practical experience for logistics spatial information service system construction.

我代表建设部祝贺全国地理信息系统技术与应用工作会议的召开,感谢国家科委长期以来对建设部科技工作的大力支持。建设部在城市规划领域应用地理信息技术取得了一定成绩,下面我简要介绍一下有关情况。 建设部是国务院综合管理全国建设事业的职能部门,其中一项重要职责是指导和管理全国的城市规划工作。建设部十分重视地理信息系统技术在城市规划领域中的应用,并给予积极支持和引导。地理信息系统技术在城市规划领域得到较好地应用、推广,并取得明显成效,这与城市规划在城市现代化建设中的地位和作用密切相关。

Ecological restoration is an important way to adjust the structure and function of ecosystem in order to cope with the excessive interference of land use. Scientific mastery of restoration pattern and farmland pattern evolution has a profound significance on the management of regional ecological environment and the conservation of vegetation in Loess Plateau. This study, taking Yan'an City in Loess Plateau as a typical area, explores the spatial differentiation characteristics of farmland variation and restoration status from the overall characteristics of ecological restoration, topographic factors and regional differences since ecological restoration. The results show that the arable land of Yan'an City decreased from 11752.80 km² to 9149.93km² due to the ecology restoration during 2000-2013. The returned farmland is 2756.85 km², and the returned farmland index is 22.15%. The cultivated land was mostly converted to forest and grassland accounting for 95.29% of the total amount. Farmland and the returned farmland area was mainly distributed in slope (6~25°) and the altitude level of II（925~1115 m）, III（1115~1275 m）, IV（1275~1442 m）, which accounted for more than 70% of the area. The degree of farmland returning increased gradually with the increase of slope, with the land reclamation rate decreased gradually with the increase of slope and elevation. The highest degree of ecological restoration is the altitude level of IV, and the least is altitude level of III. The ecological restoration rate of 2005-2013 was higher than that of 2000-2005. The area and extent of restoration in county decreased from north to south. The center of farmland returning and cultivated land is located in the boundary of Ansai county and Baota District which are in the north of Yan’an City. The center of ecological restoration was changing from northeast to southwest while the center of cultivated land was changing from north to south. This study may provide more scientific and reasonable reference for ecological conservation and construction of ecological civilization in Loess Plateau by the analysis of spatial-temporal differentiation characteristics of ecological restoration in Yan'an city.

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.

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.

The geosensor networks system of mine ground disaster monitoring is a integrating system implemented by comprehensive application of geomatics technology, that is, satellite remote sensing, geographic information systems, satellite positioning, Georobots, ground based SAR, and sensor networks. It is of great practical significance to predict the mine ground disasters timely and accurately, in order to prevent and reduce the loss of mine ground deformation disaster. The main research contents of the geosensor networks system of mine ground disaster monitoring include data whole processing theory and method, geographic grid and function partition, data fusion, spatial data clustering analysis, disaster effect analysis, intelligent forecasting models and theory, spatial database and service platform system. Using time-series monitoring data of multiphase geosensor networks, the high-resolution satellite remote sensing monitoring data and the function partition data, the dynamic deformation field can be established over mining region based on the research of spatiotemporal variations, so as to evaluate the effectiveness of the dynamic deformation field by measured data and optimize the deformation field model. Finally we can develop the geosensor networks GIS system of mine ground disasters monitoring and realize the integrating management of monitoring data and analyzing for the purpose of mine safety production and ground deformation monitoring and forecasting.

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.

Soil salinization is the process of increasing the salt content in the soil. Salinization occurs when the groundwater table is between two and three meters from the surface of the soil in arid lands. The salts from the groundwater are raised by capillary action to the surface of the soil, and it affects human and natural resources, such as native vegetation and crops, animals, infrastructure, agricultural inputs, biodiversity, aquatic ecosystems and water supply quality in the environment. Factors such as climate, features of landscape, soils, drainage, aspect and the effects of human activities all impact on the severity and occurrence of salinization. Therefore, it is an important concern to evaluate and monitor soil salinity in order to take protective measures against further deterioration of the soil. Traditionally, soil salinity evaluation and monitoring are often carried out with intensive field work and sampling. Most previous studies have focused on differentiating salinized and non-salinized soil qualitatively by analyzing the salinity distribution and monitoring its dynamics. Remote Sensing (RS), Geographical Information Systems (GIS) and modeling have recently outperformed the traditional methods. Remotely sensed data has great potential for monitoring dynamic processes, including salinization. Remote sensing of surface features using aerial photography, videography, infrared thermometry, and multispectral scanners has been used intensively to identify and map salt-affected areas. Salinization has seriously restricted the sustainable development of agriculture and ecological security in the Yanqi Basin, Xinjiang, China. Therefore, accurate assessment and monitoring of soil salinization is particularly important. In this paper, based on the Landsat 8 OLI remote sensing data and measured data, the soil salinization evaluation model was established by using the four evaluation indexes of groundwater depth (GD), salinity index (SI), surface evapotranspiration (SET) and modified temperature vegetation dryness index (MTVDI) in Yanqi basin, Xinjiang. Results demonstrate that: (1) BP neural network model for training was combined with the field measured soil salinity data and the best performance was archived in 4-4-1 architecture (R²=0.864, RMSE=0.569) in the three networks. Compared with traditional multiple linear regression model (R²=0.741, RMSE=0.767), the artificial neural network can improve the predictive accuracy of soil salinization. (2) Soli salinization is strongly associated with GD、SI、SET and MTVDI, and the soil salinization are the results of different combinations of different combination effect factors. Salinization is mainly distributed in low groundwater level and unused area. (3) Most of the study area was salinized in different degrees of salinization, and the degradation of farmland led to further soil salinization and secondary soil salinization.

Urban potential is a quantitative indicator to measure the urban spatial interaction. It is used to describe the interaction force exerted to any place in the region, while taking into consideration that the interaction force is produced jointly by all the other surrounding cities. Urban population potential is the potential that is measured and indicated by urban population. GIS usually uses points to represent the spatial locations of cities and uses the point attribute field to store their urban population information. Therefore, the most convenient way to simulate urban population potential is to build a spatial analysis model based on the relevant point data. Obviously, this method has some disadvantages: on one hand, urban point data represented by latitude-longitude pattern in national fundamental geographic information datasets does not coincide with the urban population centroids in reality;on the other hand, most cities are usually composed of a variety of mutually separated urban land-use patches and these patches interact with each other within their urban precincts. To overcome the impacts of these disadvantages, this study has designed a simulation technology solution of urban population potential based on urban land-use patches. It takes the independent urban patches as the basic spatial analysis units and propose a method to divide grades for those urban patches in Beijing-Tianjin-Hebei region. Then, a time-consuming grid surface of Beijing-Tianjin-Hebei region is established. The numerical simulation of the urban population potential in Beijing-Tianjin-Hebei region is realized by making use of ArcGIS platform and modeling techniques of python accordingly. The method based on urban land-use patches could overcome the deficiency that the urban points do not coincide with urban population centroids in reality and it could reflect the spatial interactions of urban interior patches. Moreover, the simulation of urban population potential has further satisfied the requirements toward refinement.

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.

Although the promotion of scientific data sharing has brought an unprecedented research opportunity,it still did not get rid of the traditional research process that is "collecting data-downloading data-analyzing data",which has severely hampered the efficiency of research output and the needs of data for researchers has been changed into the needs of information and knowledge.In this paper,taking China's socio-economic statistical data,vector data of national fundamental geographic administrative divisions as examples,in conjunction with ESRI and Google's global maps and image services,we discussed the virtual data integration methods of geo-multisource data and its visualization analysis application,so as to realize rapid knowledge discovery and information acquisition.The paper firstly described methods to publish the map data and attribute data as web services and then discussed three integration principles of multisource web services for the heterogeneous and homogeneous data:(1) all the records of attribute data are assigned a unique number as key fields for the association with a spatial map shape,so that the spatialization of attribute data could be realized;(2) all the spatial data are preprocessed to be suitable for integration by unifying their projections and coordinate systems;and(3) the integrity and accuracy of the data published for web services are ensured.Following the above three principles,the data were prepared.After publishing different types of data as web services,a scheme of online data statistical analysis and visualization based on integration data retrieved from multi-source web services were designed and a preliminary application system was developed.The results show that service-oriented technology can effectively solve the problems of multisource heterogeneous data integration and have obvious advantages as opposed to traditional data sharing and application system.Although the service-oriented technology has turned to be mature,there is still a long way to go for the wide and deep applications.According to our study,there still exist some problems such as the different data units from different sources,the complex operation processes and the ununiform service specification.In future studies,more attention should be paid to the standardization of different services,intelligent operations and application packaging,so as to promote the construction of E-Geoscience and provide all-round services for researchers ultimately.

With the rapid development of Internet and WebGIS,there are more and more extensive applications of the WebGIS statistics thematic maps in recent years.ArcIMS provides a way to make the statistics thematic map and releases it through the network,but its functionality is still not perfect.It can only provide two kinds of charts,i.e.pie and column charts,the type is very limited,and the aesthetics is not strong.What's more,as the feature-map and statistical thematic chart are generated on the server side at the same time and then transfered to the client side,so the load of server is high and network transmission is slow.The aim of this study was to provide a new method for making statistical thematic maps using ArcIMS combined FushionCharts,which is a chart component.The author refered to nearly 40 kinds of SWF files provided by FusionCharts,wrote a class which was used for converting the data's format into xml,then sended the SWF file and XML to the client,analysed through the flash plug-in of the client to generate statistical thematic chart,used the spatial geological place points coordinates,overlaid to feature-map which was made by ArcIMS on the server side to form the statistical thematic maps finally.This method generates the feature-map and thematic statistical chart on the server and client side,respectively.Compared with the traditional methods using ArcIMS only,it has a more simple production process;includes nearly 40 kinds of beautiful,highly interactive types of statistical thematic charts,making the form of charts abundant and visual,meeting the user's requirements more fully.In addition,it generates the feature-map on the client side separately,without the generation of thematic statistical chart formed on the server,so it is a good way to reduce the load of the server,making double the speed of network transmission.At last,a specific example of using this method is given,showing that it can make multiform,dynamic and good looking statistical thematic maps easier and faster.

3D GIS has become a focus field of GIS study currently,and high-resolution satellite image is an important data resource for the 3D GIS construction.In this paper,based on the high-resolution IKONOS satellite stereo images,using the method to extract the 3D visualization information of the research area,including DEM extraction,orthophoto map making,3D information and texture of the ground building,the progress of the DEM extraction was analyzed and the errors of the DEM were corrected.A technical method that uses the ERDAS IMAGINE and 3ds Max software to carry on hybrid modeling was put forward.By complementing the advantages of two kinds of software,this method can accomplish the modeling work of the ground building better.Finally,based on the VC++6.0 platform,combined with the DirectX SDK,the 3D visualization landscape was firstly constructed from two aspects,including the visualization of terrain and the loading of the ground feature models.In this process,in order to improve the operating speed,the Level of Detail algorithm and Mipmap technology were used to optimize the terrain visualization and the texture of the models.Further more,the diversification of the smog was simulated by constructing particle system and many factors of the environment and production facilities that can influence the movement of the smog were calculated and added.Through these work,the production activities of the special facility can be inferred,so it can provide support for the decision analysis.