The research of imports of foreign direct investment(FDI)on the host country's economic growth is an issue in the study of international investment and economic growth.Along with the increase of FDI in our country,the evidence from China plays an important role to deepen the study in the field.In the paper,based on the data from different provinces and different areas(Eastern,Middle and Western Areas) from 1992 to 2004 in China,we use a modified De Mello's model to improve the robust city of the results.Like other similar studies,our research proves that FDI have a positive effect on China's economic growth.But at the same time,our research distinguished from others in that it shows FDI's different impact on Eastern,Middle and Western Areas.Compared with Middle Area,FDI's impact on Western Area is statistically lower,which means Western Area should reform its investment environment to improve the FDI's efficiency.Regression results also show that compared with Middle Area,FDI impact on Eastern Area isn't significantly higher.While such result is a little bit perplexing,it may reveal FDI's "crowd out" effect in the Eastern Area.

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。

今天能够参加中国科学中心的第一次会议,同时在此之前跟着陈先生,廖院士、何秘书长一块去莫斯科参加这次欧亚科学院院士大会,被选为欧亚科学院院士,对我来说是很大的荣誉。这次到莫斯科参加大会,感受很深,刚才大家谈到俄罗斯,原苏联,它的整个科学,曾对我国的发展,有一段起过很大的影响。这次去后我的感受很深,俄罗斯人民对我们的友好感情非常深。

Target classification and recognition (TCR) of high resolution remote sensing image is an important approach of image analysis, for the understanding of earth observation system (EOS), and for extracting information from the automatic target recognition (ATR) system, which has important values in military and civil fields. This paper reviews the latest progress and key technologies between domestic and international remote sensing image TCR in optical, infrared, synthetic aperture radar (SAR) and synthetic aperture sonar (SAS). The main research levels and the contents of high resolution remote sensing image TCR are firstly discussed. Then, the key technologies and their existing problems of high resolution remote sensing image TCR are deeply analyzed, from aspects such as filtering and noise reduction, feature extraction, target detection, scene classification, target classification and target recognition. Finally, combined with the related technologies including parallel computing, neural computing and cognitive computing, the new methods of TCR are discussed. Specifically, the main framework includes three aspects, which are detailed in the following. Firstly, the predominant techniques of high resolution remote sensing image processing are discussed based on high performance parallel computing. And the hybrid parallel architecture of high resolution remote sensing image processing based on Apache Hadoop, open multi-processing (OpenMP) and compute unified device architecture (CUDA) are also presented in this paper. Secondly, application prospects of TCR accuracy promotion are analyzed based on a thorough study of neuromorphic computing, and the method of multi-level remote sensing image target recognition based on the deep neural network (DNN) is introduced. Thirdly, the model and algorithm of big data uncertainty analysis for remote sensing images are discussed based on probabilistic graphical model (PGM) of cognitive computing, and the multi-scale remote sensing image scene description is given based on hierarchical topic model (HTM). Moreover, according to the related research of multi-media neural cognitive computing (MNCC), we discuss the development trend and research direction of TCR for remote sensing images big data in the future.

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.

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.

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.

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.

The component-based GIS system has enormous advantages in seamless integration and the flexibility of the system.It stands for the development trend of GIS.Applying the ComGIS based technology,a specific GIS system for monitoring and management of the Minjiang River Estuary wetland based on MapObjects and Visual Basic has been developed in this research.The spatial visualization analysis of the wetlands' dynamic change,in turn,can be implemented.

‘八五’农作物遥感估产国家攻关项目的研究·解决了一批主要农作物遥感估产中的关键技术问题,如播种面积提取技术信息复合技术、遥感估产模型建立的技术和全数字化电脑估产技术等。

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.

Two basic dimensions for describing the human social development and human cultural phenomena are space and time. Previous humanities research emphasizes much of the attribution of phenomena itself and time dimension because of the technologic limitation and epistemological difference. Sometimes these research ignored the space dimension or retained the attitude of excluding it. Fortunately, more and more scholars have rethought the importance of spatial coordination system and begun to use spatial thinking in their research. These scholars come from the discipline of history, philosophy, literature, economics, sociology, anthropology, archeology, geography, politics, statistics, etc. This article, based on the instructive thought of space and integrated humanities and social science research, intends to take modern geographic information science and methodology and related space technology as a platform, to tentatively discuss the spatio -temporal characteristics of multi-disciplinary humanity and social science research. Emphases are given particularly to the spatial attribute, space distribution, spatially mutual affection and space evolution rule of the economic and cultural phenomena in human society. In this article, the authors put forward the elementary thought of spatially integrated humanities and social science research which includes basic concept, research object, basic methodology and development direction and wish it can promote the discussion.

Bashibulake uranium deposit, which located in the northwest fringe of Tarim basin in Xinjiang Uygur Autonomous Region, was considered to be closely related with oil-reduced fading alteration. However, the evidences about the oil-reduced fading alteration genesis mainly came from the geological and geochemical microscopic researches. In this paper, the enhancement processing of Quickbird high spatial resolution satellite remote sensing data was firstly made on the basis of analyzing the geological characteristics of uranium mineralizing fading alteration sandstone and the band feature of Quickbird data. Through above processing, the ability of Quickbird images to interpret the fading alteration sandstone was further promoted. Secondly, the features about shape, spatial distribution for oil-reduced fading alteration sandstone which exposed on the Bashibulake uranium ore area were analyzed using the enhanced Quickbird images. Analysis included the following three aspects. One was the general distribution for the fading alteration sandstone from the wide scale of the uranium ore area and its around area. The second was the shape feature and spatial distribution characteristics for the purple red sandstone, which was not under subjected of fading alteration, from the scale of the whole uranium mineralization district. The third was the shape and spatial expand feature for the grey yellow fading alteration sandstone that is located in the internal of a large unfading purple red sandstone from the more large scale of the east uranium ore area. Above results provided the macroscopic evidence from both positive and negative aspects to verify the uranium mineralizing fading sandstone was generated by the oil-reduced alteration, rather than the original sediment genesis. In the same time, the idea about whole spatial distribution of the fading alteration sandstone can provide important information for uranium prospect in the outer edge of Bashibulake uranium mineralization area. All above researches fully show the great application potential for Quickbird high spatial resolution satellite remote sensing data on uranium mineralization exploration.

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.

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.

To explore the applicability of the covariance localization method in the Ensemble Transform Kalman Filter (ETKF) scheme, we firstly analyze some difficulties of the covariance localization method applied to the ETKF scheme in theory. In order to solve the current problem, then we develop an approximate covariance localization method for ETKF, which is accomplished through the Schur product on ensemble perturbations, and finally we test the suitability and the effect of the approximate covariance localization method in ETKF by combining the Lorenz - 96 model. This model is often used to do performance evaluation in data assimilation. The results show that the covariance localization method cannot be directly applied to ETKF assimilation, although it can eliminate some spurious correlations in the background error covariance matrix and increase the rank of the background error covariance matrix. Because the effective object of Schur product in the covariance localization method is the background error covariance matrix, but the update equations of the ETKF only contain the ensemble perturbation matrix, excluding the background error covariance matrix. Moreover, the dimensions between the correlation coefficient matrix and the ensemble perturbation matrix are different, so an approximate covariance localization method is developed. By the experiment, it shows that the approximate covariance localization method can be applied in the ETKF, but the approximate Schur product disrupts the dynamic balances of ETKF assimilation system ,which leads to bad assimilation results. The local analysis method is widely used to solve the localization problem in data assimilation systems, so we try to apply it into the ETKF scheme. The results show that the local analysis method can be directly applied to ETKF, it can remove the spurious correlations in background error covariance matrix and obtain better assimilation results. This paper is a theoretical innovation and experimental exploration, it helps the related researchers to do further studies on the localization in the data assimilation.

In recent years,internet map is developing rapidly and more and more spatial information are settled in the internet terminal.Internet map has been an effective way to transfer and distribute geographic information,which has been also an important tool for people to obtain information.However,as the most direct and important method of geographic information expression,a series of problems exist when the map symbol is applied on internet,such as theory imperfectness,inadequacy in sharing,difficulties to expand,lack of vector symbols and so on.The theories and methods of symbol design and expression,which belong to the paper map and desktop mapping system,can't be transplanted to internet map symbol system directly.In order to solve these problems,related work which based on the full study of existing map symbol theories is carried out and a new conceptual model of internet map symbol is put forward.According to the conceptual model,the paper builds a descriptive system for internet map symbol,and the validity of the whole theory is tested in combination with online statistical map making and distribution system and census map plotting system,which are developed by Institute of Geographic Sciences and Natural Resources Research,CAS.

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.

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 Dunhuang test site is situated in the northwest corner of the Gobi desert near the city of Dunhuang. The calibration area is (400×400)m ² and situated in the centre of a relative homogeneous and flat zone of (30×40)km ². During August to September, 2000, China Center for Resources Satellite Data and Application (CRESDA) conducted a field measurement campaign for determining the characteristics of the ground reflectance and of the atmosphere. The results show that the test site has a very good homogeneity with a variation coefficient of the reflectance in any channel lower than 3%. The ground reflectance increases progressively from 0.18 at 485 nm to 0.26 at 830 nm. Atmospheric measurements show that at 0.55 μm the total atmospheric optical depth (about 0.34) and the aerosol optical depth (about 0.26) are relatively low and the effect of atmospheric water vapour content is also relatively small. These preliminary results show that the selected test site is well adapted to the absolute radiometric calibiration of in-flight satellite sensors such as CBERS-1 CCD.

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.