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.

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.

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.

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.

前言 人类认识自然经历了漫长的历史过程,地学是人类认识自然的科学。随着探测器从地面→航空→航天高度的增加及观测技术的进步,人类对自然的认识也在经历着一个从局部到整体,从片面到全面,队概念描述到数学物理模型乃至量化表示的过程。技术的发展推动了科学理论的进步,新理论的完善又向技术提出更高的要求,成为技术发展的动力源泉。这种相互促进共同发展将是一种无止境的循环过程。技术是工具,认识是理论,行动是目的。这是不可分割的一个整体,哪个环节出问题都达不到目的。

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 paper analyzes three plans on extraction of vegetation cover rate using remote sensing, i.e., experience model plan,vegetation index plan and mix-pix analytical plan and identifies their force, precision and existing problems in actual application. It points out what affects the wide application of precision of vegetation index transform plan abroad is the choose of the maximum NDVI - complete vegetation cover.Based upon this it introduces an improved model of vegetation index transform plan using the maximum NDVI value of the high resolution satellite image as the homogenous pixel's NDVI value to replace the NDVI value of the middle resolution satellite image, set up vegetation cover extraction model so as to develop a method for obtaining large scale vegetation cover with the aid of middle resolution satellite image. Practice proves this method is simple and practical, suitable for large scale macroscopic monitoring by applying middle resolution satellite image.

Geographic features change detection has became a vital component of the national geographical information 12th Five-Year-Plan and the national geographic general survey. In web pages, billions of geographic feature changes were contained, especially in government official websites, news homepages, social portals and etc. The web pages of these websites update frequently, which could provide the latest data for geographic infor-mation change detection. Considering the complex characteristics of the web geographic information description, this paper did some valuable achievements. First of all, the geographic information knowledge base was established by summarizing the geographic information words and phrases, which could give the great supports to geographic information semantics change detection. Then, the web geographic information was obtained using two kinds of web crawler technologies. Combining the Google Custom Search crawler and general topic crawler, the web geographic information obtainment could be more complete in both scope and depth. Thirdly, the geographic information was parsed and extracted from the web text, which showed users the related features, place names, times and attributes. Last but not least, the prototype system was finally developed and the results were analyzed. The experiments indicated that the accuracy of related web pages obtainment and features change detection were over 74% and 70% respectively. In addition, the results of geographic information change detection highly relied on the integrity of knowledge base, which need to be completed further. Moreover, the uncertainty and fuzziness of web geographic information also limited the change detection results. Therefore, the web page based geographic information change detection could be a supplementary method of geographic information change detection. Combining the traditional surveying detection and remote-sensing imagery detection methods, it could solve the problems of continuous updating and timely updating of geographic information efficiently.

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.

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.

Because spatial data has the features of spatial position,unstructured,spatial relationship and vast amount etc,memory access performance on spatial data becomes one of the most important indexes for geo-spatial database evaluation.BeyonDB,researched and developed under the support of National "863" Program,is the geo-spatial database system with independent intellectual property rights.Because at present,there is no software supporting performance comparison test of geo-spatial database and in order to objectively assess its performance index,it is necessary to design,research and develop a kind of performance comparison test software of geo-spatial database.Functional objectives of performance comparison test software of geo-spatial database are firstly analyzed in the paper,i.e.to support performance comparison test between BeyonDB and international leading geo-spatial database system,meanwhile,it can simply extend into other geo-spatial database;to support performance test of loading and inquiring of spatial data;to support testing methods of both SQL sentence and test script,and test report should be automatically generated and output based on "Template" method.As to performance comparison test software of geo-spatial database,we adopt object-oriented design philosophy and method,rationally use software design pattern.General framework design of the software and detailed design of main control,function command interface,access interface of spatial data and output of test results etc.are provided in this paper.After completing the design,we put forward methods of realizing functions of the software,development tool,main interface of the software,output interface of test results and other results.At present,the software has been successfully applied to performance comparison test between BeyonDB and Oracle Spatial,BeyonDB and PostGIS,which greatly improves test efficiency and enables test results to be objective and impartial.Finally,future research emphases of the software are defined in the paper.

Generalization of road network is one of the focuses in map generalization. Road network generalization can be considered as the combination of two processes. One is selective omission, and the other is the simplification of selected roads. Selective omission is the key process, in which it is hard to maintain the overall and key local structures of original networks. Many solutions have been proposed for road selective omission. But previous solutions cannot maintain these structures in the process of selective omission. It will solve the problem if we can build the hierarchical structure of road networks and make selection based on the structure. This paper presents a novel method for selective omission. The method first builds the hierarchical structure of road networks. It is based on Hierarchical Random Graph (HRG) which transforms a graph into a dendrogram, which is widely used in complex networks. HRG goes beyond simple clustering and provides clustering information at all levels of granularity for visualization. But HRG is over detailed for multi-scale representation as its dendrogram usually contains tens or even more layers. So, after building HRG of road networks, we propose a measure named Accumulated Probability Number (APN) to simply HRG hierarchy. APN reflects the importance of each road in the whole network. It should be noted that we use road ‘strokes' as vertices and the connections between them as edges when transforming a road network into a graph. The proposed approach is validated with case studies of road network generalization. Different patterns of road networks are considered including grid, ring-star-hybrid, grid-star-hybrid, irregular patterns. The corresponding Google Map is used as the reference for evaluation of road selection. The results of APN-based selection match well with the reference.

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.

Cloud-top height is an important factor in weather forecasting and monitoring. Accurate cloud-top height has important scientific significance for improving the quality of both weather analyses and numerical weather prediction. The geometric method to calculate cloud-top height using stereo image pair obtained from meteorological satellites has been recognized as providing relatively high precision, and has practical importance. However, this method does not fully consider cloud movement and typically assumes ideal ellipsoids in theory. Thus, the calculated cloud-top height still has a relatively large error in practice. In this study, cloud-movement speed was introduced into the collinearity equation of photogrammetry. We established a model to calculate the cloud-top height from the ASTER images (3B and 3N) with digital photogrammetry and remote sensing technology. Firstly, we created a stereo pair from ASTER images obtained on 25^th September 2012. Then, the cloud-movement speed was calculated through matching cloud points. Finally, the cloud-top heights with and without consideration of wind speed were both calculated. Compared with ground control points, the model error is determined to be within two pixels (about 30 meter). We further compared our results with MISR products, and found that the cloud-top height determined without using wind speed is consistent with the height obtained from MISR, the difference between them is about 300 meters. Our cloud-top height determined with wind speed considered, however is about 1400 meters higher than that of MISR without wind considered. Marchand and Naud had identified in their research that the cloud-top height obtained from MISR is about 1000 meters lower than Lidar observation. This implies that our results with consideration of wind speed are closer to the Lidar observations. Due to the fact that our method for determining cloud-top height is dependent on the cloud moving speed, and the results with wind speed included have led to a good estimation of cloud-top height, we conclude that the wind speed should be included in algorithms for cloud-top height determination.

中国地理学会地图学与 GIS专业委员会暨学术会议于 1 0月 2 5～ 2 9日在青岛举行。出席这次会议的代表有 90多位 ,分别来自全国各地 5 0多个单位 ,共收到论文近 60篇。会议围绕着“新世纪地图学与 GIS的开拓与创新”的主题 ,毋河海、杜道生、崔伟宏、池天河、曹桂发、黄杏元、马耀峰等 1 4位教授在大会上作了报告 ,有近 30位专家学者在分组会上作了报告。

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 gird scale effect is one of the basic issues on population data spatialization.For the demand of all kinds of spatial population data in the fields of resources and environment and global change models,a lot of researches have been done based on remote sensing and GIS technology both at home and abroad.But the models used are mostly on global(such as GPW,1995,5km),national(such as national population database,2000,1km) or provincial scale,and their resolution ranges from 1km to several kilometers.In recent years,there are studies on local distribution of population by using of high-resolution images.For all the researches,both the method of data source selection according to specific application and the analysis on production suitability are deficient.So,many uncertainties exit in population data application,especially in county level and secondary or tertiary rivers.To solve the problems mentioned above,in this article we mainly propose the method of scale effect analysis on population data spatialization.Taking Yiwu City,Zhejiang Province as the study area,using CBERS and IRS-P5 images we extract land use information and build a spatialization model to the statistical population data of rural towns,then get a set of population data gird ranging from 20m to 1km.Moreover,by comparing population data by grid and statistical population data in rural towns,the grid scale effect analysis is made;by comparing population data by grid and statistical population data in villages,the remote sensing data source scale effect analysis is made.The result of scale effect analysis shows: by using CBERS as data source,the suitable grid scale of production is 200m and its precision is 76%;by using P5 as a data source,the suitable grid scale of production is 100m and its precision is 84%.The method of scale effect analysis in spatial distribution of statistical population is argued in this paper and it can provide basic technical solutions and examples to optimum scale selection in the process of humanistic factors(such as population) spatialization.

由中华人民共和国科学技术部主持 ,中国科学院成都山地灾害与环境所主编 ,南京地理与湖泊所、中国地质勘察技术院等 3 1个单位共同承担的国家重点科技项目《长江经济带可持续发展地图集》及其电子版由科学出版社正式向国内外出版发行。图集出版前通过了以徐冠华院士为首的评审委员会和以陈述彭院士为首的编纂委员会审议并分别作序。图集出版后中国科学院资环局在京组织了以孙鸿烈院士为主任 ,童庆禧院士为副主任的专家鉴定委员会 ,对图集成果进行鉴定。一致认为 :图集主题明确 ,选题精练 ,结构严谨 ,时代性强 ,对研究、决策与推动长江经济带的发展 ,促进当前西部大开发具有重要的科学实用价值。

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.

引言二十一世纪是人类全面认识、开发利用和保护海洋的新世纪。《中国21世纪议程》把海洋资源的可持续开发与保护作为主要行动方案领域之一,提出“要建立可持续利用海洋资源的综合管理体系,及海洋生态系统监测与保护体系和环境预报服务体系,我国拥有约300万平方公里的海洋国土。在我国陆上资源越来越匾乏,生存发展空间潜力愈来愈小的情况下,海洋提供了广阔的发展空间和丰富的资源。所以建立一个较为完善的实用性的海洋决策支持系统非常必要。

Mountain basal elevation (MBE) is the elevation of the base which mountains uplift from. The variation of MBE affects the redistribution of water and heat conditions in mountain areas, and the structure and distribution of mountain altitudinal belts. But so far, there has been no accurate and scientific concept of MBE and no effective method to quantitatively extract it. This paper discusses the features of MBE, and develops a new quantitative method for MBE extraction based on topographical features. There are several algorithms available for automated extraction of topographical features, including ridge line, valley line and the boundary of mountains, and most of the current approaches are mainly based on regular statistic unit. This paper takes Taiwan mountain areas for experimental zone, and uses ASTER GDEM at resolution of 30m. Firstly, extracting main ridge line and main valley line by terrain analysis and hydrological analysis, and using topographical features to extract the boundary of mountains. Then based on the result of extraction, the distribution and the value of MBE are determined. The results show that the mountain areas of Taiwan can be divided into six MBE areas (0m, 150m, 200m, 600m, 630m, and 650m). The results can represent the distribution of Taiwan mountain basal elevation. This MBE extracting method is based on sophisticated algorithms, so it can improve the efficiency of the extraction process and the accuracy of results. The method could promote the extraction of the world's mountain basal elevation and the quantitative research of mass elevation effect.

Smart client is the client application easy to deploy and manage. Taking the advantages both in B/S and C/S, it has a bright future in many different fields. Through analyzing the feasibility in data-sharing system and taking lake and watershed data-sharing system as an example, this paper introduces a method of how to design and build data-sharing system based on smart client. First, the paper divides the data-sharing system into six different parts, including user identification, data produce inquiry and order, data encryption and download management, data decryption and visualization, connection and updater management. It discusses the details of the technology which are applied in each part. Smart Client Application blocks are the essential components to build a smart client application. Lake and watershed data are the basic elements of the geo-data database. Lake and watershed data center has collected mass data for the scientific research of related fields. Building a data-sharing system is very important for scientists to access the essential data. Considering much of the data concerning the national security, this paper brings network security into data-sharing system. In order to build lake and watershed data-sharing system, we select Asp.net as its web developing environment, Vs.net to build form application, and Sql server as its database. Thus, part of the code in client development is given. All in all, this paper draws the conclusion that smart client can be used in various data-sharing projects. Otherwise, aiming at the demand of data-sharing, it puts forward the draft of the system with smart client.