CBERS-02B can acquire different spatial resolution and multi-spectral data which improves its application ability greatly.In order to verify HR data mapping ability,we made test on what model is suitable for geo-rectification and how many GCPs should be acquired to get a satisfaction result.We also made research on how to cope with the mosaic problem caused by narrow swath and vector image methods is proposed for image acquired at same path and how many public GCPs within overlap region should be acquired is suggested for image acquired at same row.
In this paper a Hierarchical Multispectral Gauss Markov Random Field (HMGMRF) model and its corresponding segmentation algorithm are proposed by modifying approach of anticipation dispersion of Gauss Markov Random Field (GMRF).In the segmentation procedure,the HMGMRF model is first used to analyze variational tendency of each land-cover classes in multispectral bands (i.e.multispectral texture characters of land-cover classes),neighborhood space is extended from single layer to multi-layer by introducing correlations of the spectral bands of remote sensing imagery,dimension of texture character is extended,thus capability to describe texture characters of the model is improved.Then,based on Bayesian principle,Expectation Maximization algorithm is accompanied by the estimation of model parameter on each land-cover classes.Finally,based on intensity texture characters,Maximum a posteriori is employed to perform image segmentation.Experimental results show that the proposed HMGMRF model-based segmentation algorithm is more capable in differentiating land cover classes and thus can achieve higher segmentation accuracy.
With only few images for choice,how to mosaic images of different seasonal and produce good mosaic image is a very common technological problem.The main difficulty for this problem is how to minish the color difference between mosaicing images.In this paper,taking two SPOT5 satellite images of Xiamen city,with different seasonal,acquired in different year and with large color difference,as a case,we used several image processing methods,including rescale,raster fill,extraction of feature information and classification etc.to decrease the color difference of two kind ground features:patch one and irregular pieces one.The methods proposed in this paper make possible produce good mosaic images and they are very practical.
The space-borne microwave radiometer is a satellite payload designed to measure the atmospheric liquid water content and vapor content. In this paper, some issues about design the digital unit, such as redundancy design and reliability design, of a spaceborne microwave radiometer are presented. Test results validates that the design can meet the requirement of the system.
The orbit design of satellite altimeter need to consider orbit height,eccentricity,orbit inclination and repeat cycle etc.parameters.This paper introduces some factors relate to altimeter orbit and sampling patterns.This paper also describes of design criterion of altimeter orbit,focusing on analysis of T/P altimeter orbit parameters.On the basis of above analysis,this paper presents the scheme of HY-2 satellite altimeter orbit design and the sampling pattern.
The data matching method adopted by NASA Goddard Space Flight Center is introduced,and the grid size is rectified according the real spaceborne data characteristics.And a refined grid is used.Spaceborne radar and ground-based radar data matched in time are chosen and space matching is carried out using the two methods.Qualitative and quantitative comparisons are made to show that the methods are valid and their characteristics are analyzed.
The construction of digital watershed plays an important role in the modernization process of water resources management and utilization in China.Using remote sensing technology to extract water information has become a significant way of providing data resources for digital watershed construction.In this paper,the unique characteristics of water bodies' simultaneous strong absorption at near and middle infrared bands (corresponding to the Band 4,Band 5 and Band 7 of Landsat TM/ETM+ imagery,respectively) has been revealed by a careful study of spectral features of water bodies with different surrounding land use/cover types,and based on that,a new water index (NWI) for water information extraction has been proposed.The new index distinguishes itself from other conventional water indexes by its usage of Band 7 of Landsat data which has rarely been reported in the literature.Using a ETM+ image acquired on March 4,2001 (path 119,row 43) and taking Xiamen Island as study area,the NWI,with atmospheric correction,has been tested in the reservoir,lake,sea and cage culture areas with various backgrounds.The overall accuracy of the water information extraction result reaches 90.4%.Therefore,it can be concluded that the NWI is effective in quickly and accurately extracting water information using remotely sensed data.
Taking Lishui County in Nanjing as research area,rural water-body of Lishui County was carried out grey related degree analysis based on grey system theory using free CBERS-CCD data and ground data measured synchronously.The biggest related degree wave band group (b3/b1) was chosen as a model factor to build dynamic monitoring model of rural water-body transparency,for studying the correlation of rural water-body transparency and CBERS grey data of four bands.At last the model was applied to rural water-body of Lishui County on July 30th in 2007,the result from monitoring rural water-body using this model revealed the factual distributed situation of water-body transparency objectively.The result showed that rural water-body transparency was correlated with CBERS band 1 and band 3 significantly; modeling for dynamic monitoring rural water-body transparency was y=-15 529x3+53 244x2 -60 600x+22 938,x=b3/b1(R2=0.92,F=15.26,P=0.01),with a quite high precision answering for model needing.Using the CBERS data monitoring rural water-body transparency had a great practical significance and application prospect.
South-West Line project is major inter-basin water transfer project diverting water from main stream and branch of the Yangtze River upstream into the Yellow River upstream,and it is great significance to solve shortage of the Yellow River Water Resources.But prior to the implementation of the project,it is necessary to objective evaluate water diversion areas on the ecological environment quality.In this paper,based on a large number of field investigations and laboratory comprehensive analysis the eco-environment of west route diverting water region was evaluated.Throughout the course of the study mainly use modern remote sensing technology and geographic information system analysis methods,integrated thinking in geo-ecological system theory and under the guidance of the study area from the effects of environmental quality factor of the six layers of data,overlaid to form a comprehensive environment index layer data,its were divided into four regional environment.The Composite Index from the natural environment of space analysis showed that integrated the natural environment index Class 1 and Class 2 district have good natural conditions,concentrated in the eastern part of the study area,and account for research area 50%.Three areas are more sensitive natural areas,mainly located in the western part of the plateau region of diverting water; four areas are relatively fragile natural environment,the poor regions,mainly located in the high-cold region of water diversion zone.Therefore,the Class 1 and Class 2 district have some of the natural environment of anti-jamming capabilities,in the appropriate environmental protection measures,can be a certain scale of the project; three district works,we must pay special attention to all of the natural environment the protection measures,intensify environmental protection efforts and input on the four areas of the building will cause greater damage to the environment,it is not appropriate to carry out the works building.
Based on the image database of Grand canal,taking spot5 image as the main data,First,image processing such as geometric correction,image fusion,image mosaics is carried out; then different types of image signs in different regions are established; On this basis interactive interpretation is executed; After that the post-processing of vector data and quality inspection are expected; And if there is no problem with the data,stitching layers and edge treatment should be treated.Finally,the land use database of the grand canal within two kilometers is constructed at the scale 1∶50000 by importing all the data with ArcCatalog.The result shows that it's effective to construct the land use database using the technology route shown above.It has a series of characteristics such as short cycle,high efficiency,accuracy and so on.
The Model of Atmospheric Transport and Chemistry (MATCH) is used in this work to simulate the spatial distribution and seasonal variation of AOD(λ=550nm) over China in 2006,by taking NCEP/NCAR reanalysis data as its meteorological input.The AOD obtained by MATCH is then compared with the MODIS (MODerate resolution Imaging Spectro-radiometer) satellite data and the CSHNET (the Chinese Sun Hazemeter Network) observational data.The comparison of the results in this work with MOD08_M3 indicates that MATCH has the basic ability to simulate the AOD variability over China region.The correlation coefficient between the simulation and the observational data is 0.693 (with α<0.0001).The simulated results in this work show that the AOD over China varies greatly with different regions and seasons.The higher value of AOD occurred in North China,Central China and South China,whereas the lower values of AOD are mainly located in Northwest China,Northeast China and Tibetan Plateau.The AOD over China is mainly generated by sulfate aerosol,secondly by organic aerosol,and the least by black carbon and sea\|salt aerosol.
We take the Water Quality of Weihe River in Shaanxi Province as our research object.The monitoring data in situ and the SPOT-5 remote sensing image data in the corresponding time are obtained.We correct the SPOT-5 remote sensing image by seven atmospheric correction methods such as dark-object methods (DOS),radiative transfer models etc.With the corrected remote sensing data,we retrieve some water quality parameters by means of multiple linear regression,support vector machine (SVM) and BP neural network.The results show that it is feasible to retrieve water quality of Weihe River through remote sensing data,the atmospheric correction can improve the accuracy of the retrieving to a certain extent.The method of eliminating the dark-object each band after radiometric calibration for remote sensing images is a better method for SPOT-5 remote sensing image.
Regarded Sanjiang Plain as the research object,based on multi-temporal remote sensing data,dynamic process of the land use was analyzed using 1995 and 2000 year's land use maps.The transition probability matrix about the land use type between 1995 and 2000 was calculated.Under the help of the Markov Process,the land use transition probability matrix was built to predict the land use situation in year 2005.At first,the remote sensing interpretation data of 2005 was used to validate the Markov Process,showing that the Markov Process is efficient and suitable for prediction in the area.Except for wetland (0.26%),other land-use types difference between prediction and interpretation value is less than 0.20%.Then,the land use pattern in 2010 and 2015 was predicted using the Markov Process.The results find that if the current land use policy is kept in the next 10 years,the areas of farmland and grassland will markedly increase,and the areas of wetland and forest land will obviously decrease.The share of farmland and grassland increase from 56.21% and 3.71% in 2005 to 63.88% and 3.88% in 2015; the share of forest land and wetland decrease from 28.05% and 7.46% in 2005 to 25.53% and 5.39% in 2015.According to the results of the prediction,the land use pattern can be adjusted,which may serve as a scientific basis for regional ecological environment protection and land resource rational utilization.
Because of wide ranges,complicated terrains and disparate climates,it is an important problem to increase the classification accuracy for vegetation information extraction in wide ranges.In this paper,it uses division processing and joins vegetation phonological knowledge reflected by NDVI series data and auxiliary information including DEM and GIS data into the supervised classification system to extract vegetation of South Qinghai Plateau.The classification accuracy has reached more than 83.3% by using the method mentioned above and achieved better classification results.It is reliable to help select training areas,using vegetation phonological knowledge,visual interpretation and DEM data and taking land-use data into account.It makes training areas more accurate and improves the accuracy.
The coastal zone has been of importance for economic development and ecological restoration due to their rich natural resources and vulnerable ecosystems.There is significant changing because of intensified human activities in the coastal zone.Remote sensing can be conveniently used to inventory coastal resource and environment because field investigation is very difficult.How to qualitatively and quantitatively retrieve the coastal resource and environment information in these areas from multi-sensor,multi-channel,multi-temporal,and both active and passive satellite-borne remote sensing becomes a key issue for remote sensing application.Based on the advancement of current remote sensing technology,this paper briefly presents the progress of marine fishery resources and sea-ice fresh water resources investigation; inventory the bio-coastal resources,especially coral reef,mangrove,and sea grass etc; and marine pollution (e.g.harmful algae bloom and oil spill) and marine hazard (e.g.sea ice) detected by remotely sensed data.Finally,some key points for developing the remote sensing application are proposed.
In the last few decades,due to rapid economic development and urbanization,potentially harmful contamination of soils and vegetation has become increasingly serious in the world.Due to their persistent nature and long biological half-lives,contaminants can accumulate in the food chain.High contents of these contaminants are known to be very toxic to various biota.Hence,there is an increasing need to investigate the plant stress using the remote sensing method.Firstly,this paper pointed out the major factors affecting the spectral features of plants.These factors include chlorophyll concentration,cell structure and water content in leaves.The spectral variation of the stressed plants was analyzed.Secondly,the major indicators (vegetation index and red edge) by which to investigate plant stress using the remote sensing method were introduced.We also discussed the two applications of the remote sensing method for investigating plant stress.One is for heavy metal and the other is for oil contamination.We showed that appropriate vegetation index and the accurate position of red edge are the key to investigate vegetation stress.In the end,we showed the prospect of investigating vegetation stress using the remote sensing method for the future studies.
The interaction between vegetation and climate is a complicated process.Many vegetation models were developed to understand the mechanism of interacting between vegetation and climate and assess the effects of climate change on vegetation.Furthermore,vegetation models have progressed from Static Vegetation Models (SVMs) to Dynamic Global Vegetation Models (DGVMs).DGVMs include the dynamic biogeochemical models and dynamic biogeophysical models,which mainly simulate the vegetation physiological processes,the vegetation dynamics,the vegetation phenophase and the nutrient cycling.The widely used DGVMs in the world include LPJ,IBIS,VECODE,TRIFFID and so on.The present research on DGVMs mainly focuses on four points:① the improvement of the accuracy of DGVMs; ② the comparison among different models; ③ the integrated model of DGVMs and Climate Models; ④ the research on the Carbon Cycle Data Assimilation System (CCDAS).
MODIS sensor has advantages on snow monitoring.This paper provides an overview of the MODIS snow products and NDSI algorithm that has been developed to produce snow-cover map.The paper also presents an introduction of snow researching improvement that has been made in China and overseas,and gives a preview of future improving trends of MODIS application.Finally,presents a snow-cover map of Inner Mongolia based on MODIS.
