The date and seasonal variations usually result in different atmospheric and illumination effects on the satellite remote sensing images and thus can cause errors in remote sensing applications.Accordingly,pre-processing of multitemporal images using absolute or relative radiometric correction procedures between multitemporal remote sensing images has become critical for reducing radiometric differences.Among various methods,the optimum one is based solely on the digital image and requiring no in-situ field measurements during the satellite overflight.This is achieved through image normalization technique.Taking three pairs of multi-temporal Landsat Thematic Mapper/Enhanced Thematic Mapper plus images as examples,this paper quantitatively compared and evaluated two image normalization models using the criteria of relative noise,root mean square error(RMSE) and slope value derived from the pseudo-invariant feature method.One of the evaluated models is the commonly-used Illumination Correction Model(ICM) proposed by Markham(1986) and Irish(2001).The other model is the Illumination and Atmospheric Correction Model(IACM/IACMt) recently developed by the Remote Sensing and GIS Laboratory of the Utah State University(2004).The results of the comparison and evaluation reveal that,in general,when the seasons and sun azimuth angles of multitemporal images are different or the images have obvious atmospheric effects,the relative noise and the RESE values of the image can be considerably reduced after image normalization,the slopes of scatter plots of the normalized images are more close to 1 when compared with those of unnormalized images,and the seam line between multitemporal images mosaicked using normalized images is almost invisible.However,there is no significant difference between the normalized and unnormalized images when the seasons and sun azimuth angles are similar and the atmospheric condition is also alike.As far as the normalization models are concerned,the IACMt can achieve the best result when the image was seriously atmospherically stained.Nevertheless,the application of the IACMt may sometimes bring noise to the image when the image is free of cloud and atmospheric effect is not serious.This is probably due to the overestimation of the τ value used in the model.

Sulfate and nitrate are the main components of fine particles in the urban atmosphere.Utilizing the rapid collection of atmospheric particles and the chemical component in line analysis system,the concentrations of sulfate and nitrate in fine particles from 2004 to 2007 in Beijing were observed.The results show that the average decline rate of nitrate is 7 %,about 0.7μg/m3,and the concentrations of sulfate declined from 28μg/m3 in 2006 to 18μg/m3 in 2007.There is a special analysis on regional meteorological characteristics,the characteristics of the concentrations of fine particles pollution,and the main chemical components of fine particles in the surrounding areas of Beijing from August 17 to 20 in 2007 when Beijing began a four-day test scheme to take 1.3m vehicles off the city's roads.The variations of the concentrations of sulfate and chloride combined with the backward trajectory calculations show that as the tracer of the pollutants in the surrounding areas of Beijing,the sulfate moves to Beijing with the weak south air mass,and as the tracer of sea air mass of south east China Sea,the wet air mass and chloride moves to Beijing with the airflow from south east.It proves that the south air mass helps tp transport the fine particles in the surrounding areas of Beijing to Beijing.

Geo-info Tupu methodology is a new direction for geographic researches,and it's not only a way for presentation but also a method of analysis in geo-information science.Based on the idea of Geo-info Tupu and digital mountain altitudinal belts(digital MABs),the objective of this paper is to construct the models of multi-scales spatial patterns in altitudinal belts and develop the digital framework that identifies the horizontal and vertical differentiation from multi-source data.According to three patterns of digital identification,i.e.,single flank,single peak and multiple peaks,this paper develops different algorithms using the Matlab programme.Contrasting the identification patterns,we indicate the relative merits among them in digital identification and Tupu visualization,and show clearly their special scale for the study regions.Based on the VB.NET platform,we build a programming system,named "Mountain Altitudinal Belts Digital Identification System"(MABsDIS),which provides several modules with useful tool sets,such as data in-out module,data processing module and graphic plotting module.Using the MABsDIS software,the mountain altitudinal belts are identified from digital terrain models and digital vegetation data in the Helan Mountains,China.The study reveals that the digital identification of MABs could enrich the source materials of mountain researches and enhance the digital comparison and analysis method of MABs.And it also could reveal more geographical information than ever before and is an effective attempt for Geo-info Tupu practices.

Delaunay triangulation in the plane is a fundamental tool for building DEMs of triangulated irregular networks and generating Voronoi diagrams from points in the plane.There has been a lot of algorithms for generating Delaunay triangulation/ Of these algorithms,triangle-expanding method and point-interpolation method's average time complexity is O(n²),while Divide-and-Conquer algorithm and other divide-merge methods have the linear time complexity but the steps are more complex and their probability of occurring float-point computed error increased.The author of this article proposed a new algorithm as following:first,sorting the point set according to horizontal coordinates of each point,so the points are distributed from left to right spatially;then creating an initial triangulation based on the first 3 points to append the next point to triangulation each time and generate new triangles simultaneously;finally we get a triangulation created from the whole point set;the triangulation must be optimized by LOP method in order to turn it into Delaunay triangulation.The key originality of this algorithm is the triangulation method which results in high efficiency with the average time complexity of O(n) and the advantage of simplicity of this algorithm.

Discrete or continuous rainfall data are required to run many GIS models for environment and planning.The paper attempts to make a general comparison on different spatial interpolation methods.It carried out a study on four spatial interpolation methods: Inverse Distance Weighing(IDW),Local Polynomial,Ordinary Kriging and co-Kriging with respect to elevation.Daily rainfall data obtained from 36 rainfall stations during 27 inconsecutive days in the rainy season of 2006 in Shenzhen was employed in this study.Cross validation of the results shows that the four methods could to some extent reflect the rainfall situation of the region,yet the four interpolated surfaces are more smoothing than the practical circumstance.Particularly,IDW is the most smoothing one of the four.Besides,all the criteria(Mean Error,Mean Absolute Error,Root Mean Square Error and Percentage Error)that brought up in our study to measure accuracy of the four methods demonstrated that Ordinary Kriging and co-Kriging methods are superior to Local Polynomial and IDW.Inclusion of elevation in the co-Kriging method does not lead to improvement of result compared with Ordinary Kriging method.Furthermore,the interpolation data was grouped according to elevation and average daily rainfall and the same criteria above was bought to the statistics of those groups.Comparison on the criteria reveals that,the interpolated result on rain gauge stations with high elevation tend to larger than the observed data,and those rain gauge stations with low elevation are on the contrary.The interpolation error increases sharply while the average daily rainfall is bigger than 50mm.

Cyanobacteria blooms in Taihu Lake have exerted impacts on the ecological,economic and social aspects of the surrounding areas.The monitoring and early warning to the cyanobacteria blooms make great sense to the administration of Taihu water environment.Based on research of the remote sensing monitoring and early warning on the cyanobacteria blooms,the paper is in terms of building the information system to analyse the process about cyanobacteria blooms in Taihu,system analysis is presented according to the workflow of the processs of monitoring and early warning to the cyanobacteria blooms based on remote sensing,then framework of the system is addressed,which is programmed by computer language in C# and IDL,and the framework has the advantage of containing modules easily.In order to enhance the information system flexibility,two key techniques are adopted including the system integration and soft pattern.System integration technique can merge the IDL into framework of the system,and the soft pattern technique is able to organize modules in the framework efficiently.

FCM(Fuzzy C-Means) algorithm has good clustering efficiency,therefore it is widely used in the field of image segmentation.But it has the problem of clustering center initialization.Good initial clustering centers will constrain the value function to the overall situation optimal solution rapidly.However,inappropriate initial clustering centers,not only need more iterative times,but also may possibly caused the algorithm finally restrained to the partial optimal solution.Aim to solve the problem of clustering center initialization,the paper proposes a new approach of FCM based on cloud model which is a conversion model with uncertainty between a quality concept expressed by natural language and its quantity number expression.This method in this paper combines cloud model with FCM clustering algorithm,and is applicable in the field of remote sensing image segmentation.It uses the method of cloud transformation to determine the value and number of clustering centers automatically according to the characteristics of the samples,and with less iteration times to reach the optimal solution of the overall situation.The method improves the efficiency of traditional FCM image segmentation of remote sensing image,with excellent stability and intelligence.The paper also chose three remote sensing images of TM to carry out image segmentation experiments using the methods of cloud model based FCM,and compared it with the traditional FCM method.Experimental results prove that by using our method we can reduce the iterative times and enhance the efficiency of Fuzzy C-Mean clustering algorithm.

The trend of regional pollutant dispersion requires pollution controlling be performed at regional scale.However,there is a conflict between this trend and the present environmental management system which carries out contamination control planning mainly limited to specific administrative area.It is necessary to study how to control contamination effectively at regional scale.The mode of several administrative areas combination is a feasible way to control environmental pollution.In the present study,we refer to lots of data about regional geography,economic geography and some case study of environment management system.At the sometime,the spatial differences of natural environment and social economic development are also considered.Then a scheme of regional environmental protection agency distribution was brought forward,including 5 branch bureaus directly governed by national environmental protection agency and 12 local branch bureaus governed by different provincial environmental protection agencies.This scheme takes into consideration not only the current regional environment situation,but also the future economic development.It may be valuable for reform of environmental management system in the future.

The common methods about research on the distribution of radiation in canopy are introduced.The principle of ray-tracing technology and its application in radiation transmission are described.A radiation transfer model is proposed for tree model based on forward ray tracing.The model hypothesis,processing flow and primary algorithm are expounded.Forward ray tracing is used to simulate transmission course of photosynthetically active radiation in tree canopy.Finally the special conversion method between HSV and RGB color space is adopted to clearly express distribution of radiation in canopy.On the basis of analyzing optical characteristics of leaves,the radiation transfer model is applied in the simulation of distribution of PAR in canopy.At the same time,we can get the reflectance rate,transmission rate and absorption rate.The simulative data have little difference with the actually measured data which indicated that the radiation transfer model based on forward ray tracing is effective.

In the early 1990s Frankhouser discovered the powerlaw relationship between the length L(r) of railway networks and the radius(r) of an area,and calculated the radial dimension value when he investigated the sub-railway in Stuttgart.Because of the scale-invariance in a statistical sense,fractal theory is a suited method for the distribution of highway transportation networks.Based on GIS technology,radial dimensions(D_L),ramification dimensions(D_b) and correlation coefficient(R²) of the distribution of highway transportation networks are measured and calculated in the 21 municipalities of Guangdong Province.According to the spatial pattern of highway transportation networks and the development characters of infrastructure,the province is zoned into four sub-areas(Pearl River Delta Area,East Coast Area,West Coast Area and Northern Guangdong Area) for analyzing the fractal characteristics of highway transportation networks.Pearl River Delta Area is the region with the biggest density,most complex structure,best connectivity and most mature function of transportation networks in the whole province.The fractal dimensions of highway transportation networks decay with distance from the Pearl River Delta Area to the fringe areas,while the decaying degree is lower in Coast Area and higher in North Guangdong Area.The fractal dimension value approximate 1.7 is likely a suitable indicator for the perfectness of transportation networks morphology,structure and function.The fractal dimension of Dongguan(1.6287) is greatly approaching the indicator;therefore,it can be determined that the transportation network is rather mature in this municipality.The results obtained show clearly,the combination of radial dimensions and ramification dimensions enables the comprehensive analysis of spatial pattern characteristics of density,structure,connectivity and function of transportation networks.

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.

The Wenchuan Earthquake of May 12,2008(Mw 8.0)caused great loss in property and lives.The damage caused by the earthquake has a strong spatial correlation with the geological structure of earthquake-stricken areas.Historical seismicity in this area show explicit temporal-spatial pattern,indicating that multidiscipline must be employed prudently in identifying areas for resettlements in the disaster area.Wenchuan earthquake is similar to the Pinggu-Sanhe Earthquake(Mw 8.0)of 1679 in Beijing.It is therefore necessary to conduct a more in-depth study of the Beijing area that has repeatedly experienced seismic events,together with an analysis of its geological structure.Some historical experiences about mitigation of seismic risk in Beijing are also presented in this paper as reference,especially for future development of Wenchuan disaster area.

Label-setting algorithm is one of the most classic shortest path algorithm,and widely used in the field of transportation.In the field of transportation,the shortest time path is more significant than the shortest length path.And the shortest time path is related with many factors such as the hierarchy of the roadway,the average speed and the delay from one roadway to another.In general,a logic road network is produced from a real one in this way: the real roadway is Abstracted as an arc in the logic network and the node is the crossing.After a brief description of some typical kinds of transportation network data model,an arc-labeling time shortest path algorithm is discussed here,which is more suitable than the node-labeling shortest path algorithm.The principle and theory analysis are presented in this article as well as the base data and running structure.In the following the characteristics and advantages of the arc-labeling algorithm,compared to node-labeling algorithm,are given.That it is more easily to calculate the delay and trace the time shortest path in arc-labeling algorithm.By the theory analysis and experiment test,it is proved that the arc-labeling algorithm can take the traffic informat affect and turning delay into account easily.So it is a practical shortest time path algorithm.

As the web platform continues to mature,we see an increasing number of amazing technologies that take Geographic Information Systems(GIS) visualization applications to new levels of power and usability.By integrating new powerful technologies into GIS systems,we get higher performance results with additional functionalities.The most recent development capturing the attention of the browser-based-application developers is the component development technology based Google Maps and Joomla.In this paper,the authors describe the recent situation of Google Maps and analyse its realization application in Joomla site,then provide a set of Google Maps design frame and four modules in Joomla.The component is implemented by using PHP and Java script language based on Joomla framework and Google Maps API.With the component,we can embed Google Maps in own web pages simply,draw markers and lines on the map fleetly,and build sophisticated applications with our own objective easily.

Based on the 250m bands of MODIS and near-real-time sampling data,Solid Suspended Matter Concentration(SSMC) are quantitatively retrieved using linear model.The result shows that the SSC of Taihu Lake has the highest correlation coefficient with MODIS band 1 and the lowest correlation coefficient with MODIS band 2;of all the 250m-band combinations,SSMC has the highest correlation coefficient with M1+M2,so the SSMC quantitative retrieval model was built through the correlation analysis.This plays an important role in the SSMC time-space distribution analysis using high time-resolution remote sensing data.

Texture is one kind of important feature for information extraction or target recognition from high spatial remotely sensed imagery.In this paper,a Gabor filtering based method to recognize residential areas from remotely sensed imagery is proposed based on that it often takes on obviously directional textures of the rural residential areas on the panchromatic imagery of the Beijing-1 micro-satellite system.Part of the Gabor filtering method includes the following steps: 1)to extract multi-scale,multi-oriented texture features with the Gabor filter group,2) to rectify and smooth the features with feature filtering;and 3)to segment the image with k-means clustering.With these steps,the initial residential areas can be extracted but with many deficiencies which include the existence of interspaces,holes and useless patches within many residential areas mainly because they are only obtained with image clustering.To resolve these problems,a morphological scale space based method is used to dissolve these residential patches with iteratively enlarged closing operators.Firstly,a pair of closing,opening operators are used to remove all the noises.A scale space is then constructed by using closing operator with structuring elements of increasing size.By doing so,the connected components(the set of pixels with neighborhood relationships) in the image will merge into each other gradually and become a single cluster in the end.This is essentially a binary image segmentation process,and can also be treated as a hierarchical clustering. The final number of clusters is the one which survives(relatively,not absolutely) the longest scale range,and the clustering which first realizes this number of clusters is the most suitable segmentation.Several experiments are carried out to validate the method,which includes the comparison to the classical texture analyzing method of co-occurrence matrix.

31 Olympic venues,the road cycling field and the Olympic park of Beijing Olympic Games changed the urban land surface.In order to study the environmental characteristics and the influence of these buildings,several indexes,such as,normalized difference building index(NDBI),normalized difference water index(NDWI),seasonal day and night land surface temperature(LST)and normalized difference vegetation index(NDVI)were analyzed with different spatial and temporal resolution multi-source remote sensing data and GIS,which is helpful to achieve the goal of Green Olympic Games.LANDSAT TM5 remote sensing data with 30m spatial resolution and 16 days temporal resolution was used to extract the information about the NDBI and NDWI,which are not sensitive to time.EOS MODIS remote sensing products with 250m/1km spatial resolution were used to extract the information about the day/night LST and NDVI,which are sensitive to time.The study area for each venue was defined from its center to 1 km outside with the buffer zone analysis of GIS.By classing the Olympic venues into different types based on the building time,the geographical location and the open air states,the indexes of different kinds of venues were analyzed with their mean values and the standard variance.The results lead to the following conclusions:(1)The environmental characteristics of the 31 Olympic venues are different with the difference of their building time,geographical locations and the open air states.It is necessary to take all these factors into consideration in landscaping and the programming of the activities in these venues.(2)The environment characteristics of the road cycling field are close to that of the Olympic park of Beijing Olympic Games.They both present high building index,negative water index and high day/night land surface temperature in summer and autumn.And it is better to add some water body around them to increase the environment quality.

The resource of forest and grassland is abundant in China.Furthermore,forest and grassland are important to socio-economic development and environmental protection in China.But frequent fire occurrence in forest and grassland has become a great threat to economy and environment,especially in border area.Assessment study on fire danger rating is a meaningful way in forest and grassland management and can provide useful information to support fire management decisions.This paper firstly defined some concepts on fire danger,fire danger rating,fire danger index,and so on.Then the fire danger indicators were summarized and classified into fire categories.Their application in fire danger rating assessment was analyzed,too.The second key to fire danger rating assessment is how to construct the fire danger index algorithm.In the paper,we reviewed the evaluation methods in fire danger rating assessment study,including both qualitative and quantitative.And then,an application example on the fire danger rating assessment based on remote sensing was given.Four provinces in Northern China(Helongjiang,Jilin,Liaoning and Inner Mongolia) were selected as the study area.Five fire danger indicators retrieved from remotely-sensed data were integrated to calculate the fire danger index by the method of Analytical Hierarchy Process.According to the value of fire danger index,fire danger was classified into five ratings.Using the constituted criterion,fire danger rating distribution can be mapped and used to provide useful information for supporting fire management decisions in forest and grassland.

In recent years,quality and uncertainty of population data have attracted a mass of attention,but more attention was paid to uncertainty of population data itself and less to uncertainty that was results from inaccurate using.Population data that used in geo-science mainly includes modern population investigation data,population forecast data and historical population data.Different population data that come from different sources have different characters.When population data are used,attribute character,spatial character and temporal character of population data should be paid attention.As to attribute character,the main attention should pay to the differences of statistical indexes of population data,the differences of population data of statistical resources and the change of standard of setting up town or city.As to spatial character,the main attention should pay to illegibility and uncertainty of administrative borderline,adjustment and change of administrative regions and the difference between the study area and the statistical unit of population data.As to temporal character,the statistical time of population data should be cared for.When population data with different sources and time are used,they should be integrated firstly.The main measures include: reclassifying and recounting data based on different statistical indexes and standards of population data;recounting data based on adjustment of administrative regions,or spatializing population data;forecasting or calculating population data for special time based on accurate temporal character of population.

The fractal dimensions,shape indices and compactness of the boundaries of 32 provinces(regions) of China have been calculated in this paper based on GIS software.The results show that the provinces with irregular shapes calculated with the method of fractal dimensions are provinces of Fujian,Zhejiang,Guangdong,Chongqing,Guizhou,etc.The provinces with regular shapes are in the order of Hainan,Xinjiang,Inner Mongolia,Tibet,Taiwan,Shanxi,etc.The provinces with large fractal dimensions are almost all located in southern China,which show obvious differences between the North and the South.The provinces with irregular shapes based on shape index come out as below: Hebei,Inner Mongolia,Shaanxi,Chongqing,Ningxia,and those with irregular shapes include Zhejiang,Guangxi,Hunan,Qinghai,Hainan and other provinces.Although no obvious differences can be shown the same as fractal results,yet some differences between the East and the West are identified.Those with irregular shapes based on compactness are in the order of Fujian,Gansu,Guangdong,Inner Mongolia,Chongqing,and other provinces with regular shapes are Shanghai,Xinjiang,Shanxi, Taiwan,Tibet and other provinces,which also show marked differences between the East and the West.Those with complex shapes(edge complex and greater fragmentation) are mostly concentrated in the eastern and coastal areas;and the other provinces with compact shapes are mainly concentrated in western regions,such as Xinjiang,Tibet,Qinghai.Between eastern provinces and western provinces,there are greater differences in the shape features.This paper studies the reasons and concludes that the root cause is the geographical and climate environment and historical human characteristics,and preliminarily analyzes the effects of the traffic,and other organizations impacted by the features.Meanwhile,the planar provincial outline can also reflect the transport connectivity and development level of inter-and intra-provinces.Quantitative study of the provincial space form is one of the important contents of research in regional geography and urban/regional planning.It is also an important direction of the regional research.

As the blue-green algae blooms in the Taihu Lake of China are more and more frequent,they have become a great threat to eco-environment,aquatic breeding industry and human health.In this paper,by summarizing current research conditions about the blue-green algae blooms forecast,with MODIS data and ground collecting data in Taihu Lake in China,the authors use a new concept to construct the blue-green algae blooms prediction model.This concept considers the optical characteristics of the four periods of the blue-green algae blooms and also the effects of the meteorologic environment.The model is hopefully to be used to the forecast and early warning in the future.

The construction of Beijing is experiencing a surprising speed and Beijing has become one of the largest metropolitans in the world.However,the features of an 800-year old capital still remain.This article analyzes the pattern of East and West Chang'an Street,north and south central axes;local color of subway line selection and design;ancient trees and city memories so as to help the readers understand the harmony and perfection of our cultural inheritance during the process of modernization.

A spatial outlier is a spatial object whose non-spatial attribute values are significantly deviated from the other data's in the dataset.How to detect spatial outliers from spatial dataset and to explain the reason causes the anomaly in practical application have become more and more interesting to many researchers.Spatial outliers mining can bring us a lot of interesting information,but for the complicated characteristic of spatial data,such as topological relation,orientation relation,measurement relation,and so on,traditional algorithms for outlier mining in business database seem to deficient in spatial dataset,the main problem lies in the difficulty to maintain spatial structure characteristics for most existing algorithms during the process of outlier mining.Thanks to the similarities between clustering and outlier mining,clustering based outlier mining is an important way to detect anomalies from dataset.However,due to the diversity of clustering algorithms,it is difficult to choose a proper one for outlier mining,and the main purpose of clustering is to find out the principal features of the dataset,outliers are the by-products of clustering.Based on minimum spanning tree clustering,a new algorithm for spatial outlier mining called SOM is proposed.The algorithm keeps basic spatial structure characteristics of spatial objects through the use of geometric structure: Delaunay triangulated irregular network and minimum spanning tree(MST),and it gains MST clustering by cutting off several most inconsistent edges of MST,so that it not only owns the function that it can acquire clusters from non-spherical and unbalanced datasets as the density-based cluster algorithms does,but also has the advantage that it doesn't depend on user's pre-set parameters,so the clustering result is usually more reasonable.Finally,the validity of SOM algorithm is validated by real application of geochemical soil elements dataset inspected to coastal areas of Fujian province,through analysis it is found that the algorithm is also applicable for spatial outlier mining in massive spatial dataset.

Increased heavy metal concentrations in cropland soil cause stress on many crops and decline crops′ quality.The objective of this article is to try a new method to monitoring heavy metal pollution in cropland like remote sensing,which can be applied to estimate Pb pollution on paddy plant. Experiment that paddy plants were cultivated in the potted soils manually contaminated by Pb was settled down to investigate the stress caused by Pb absorbed by paddy plants.In the developmental stages of seeding,early tillering,full tillering,jointing and booting,hyperspectral reflectance measurements on paddy plant canopy were done by a hyperspectral radiometer.Meanwhile,we got Pb concentrations in parts of paddy plant,and canopy leaves′ chlorophyll content.Quantitive relationship between Pb concentration in parts of paddy plant,canopy leaves′ chlorophyll content and canopy reflectance was studied.Results showed that chlorophyll content of canopy leaves and composition of chlorophyll,chlorophyll a and b vary obviously under Pb stress.The difference of canopy reflectance at the sensitive bands of 520nm～560nm and 630nm～690nm is most significant,and it differs from the three Pb treatments on rice from each other.Therefore,these spectral regions are validated as sensitive bands to Pb pollution on paddy plants.According to the first（620nm～670nm） and forth channel（545nm～564nm） of MODIS and sensitive band（760nm） in the near infrared region,552nm,672nm and 760nm were selected to construct composite normalized difference pollution index（CNDPI）.CNDPI discriminates all the three Pb contamination levels of paddy plants.At the early tillering stage,the canopy hyperspectral reflectance and CNDPI distinguish Pb pollution condition commendably.Therefore,monitoring Pb pollution on paddy plants with remote sensing data of raw canopy reflectance and CNDPI at the early tillering stage is a potential solution and new reference for heavy metal pollution condition monitoring technology.

国家遥感中心不仅是我们12个分部的直接领导,同时也是全国各省市、各部门20多个专业中心和400多个遥感单位的龙头;也是我国面向20多个双边和多边国际交流合作项目的归口联系单位。它成立的15年,正是党和人民把遥感连续列为国家科技攻关计划的15年。也是我国遥感科学事业走出国门,面向世界的15年。15年来遥感科学事业的成就进步,都是与国家遥感中心的战略规划、组织协调、领导有方分不开的。特别是与历届老领导的关怀和指导分不开的。

中国科学院每年有大量的科技成果涌现,如何转化为产品,形成产业,是深入贯彻科学技术面向国民经济主战场的重要问题。1995年,中国科学院与广西自治区共同探讨了年生产10吨卷曲霉素的药业合作项目,在双方上级主管部门的大力支持下,于1996年共同创建了南宁中科药业有限责任公司,实现了投资、生产、经营一体化,取得了可喜成果。

The development background, principle, technology structure, distinctive advantages and applications of new airborne 3D imaging system are presented briefly in this paper, and the flight checking and processed results are also given This system is a very important step to construct high efficient remote sensing earth observation system.

东方明珠——香港,位于我国南海之滨,珠江口东侧.其北以深圳河与广东省深圳经济特区接界,距广州市约150公里。全港范围由九龙半岛、香港岛和邻近小岛.新界及拥有的200多个大、小岛屿组成,总面积1070多平方公里,其中港岛和邻近小岛77.5平方公里,九龙及新九龙45.87平方公里,新界及拥有的岛屿946.7平方公里。

尊敬的国际欧亚科学院主席先生: 尊敬的院士先生,女士们、先生们: 值此国际欧亚科学院在北京开会之际,我受委托代表这次当选的中国七位新院士向大会和国际欧亚科学院的各位领导及全体院士们表示我们衷心的感谢。 我们首先怀着激动的心情向国际欧亚科学院表示我们的谢意,向在这次增选过程中曾给予我们帮助、支持、鼓励和推荐的各位院士先生们表示我们的谢意。 我们的当选,这是对我们的极大鼓励,是我们的莫大的荣誉,也是对中国科技工作者的鼓励和中国科技工作者的荣誉。