Object-oriented classification of high spatial resolution remote sensing imagery is a very popular theme in the field of remote sensing science.A new approach of object\|oriented combining improved watershed transform with spatial clustering is proposed to classify high resolution remote sensing imagery in this paper.Firstly,gradient image is obtained by applying phase congruency model to the QuickBird panchromatic image with log Gabor wavelet filters from multi\|scale and multi-direction.Extended minima transform and minima imposition are used to get foreground marking of interesting objects and present gradient reconstruction,thus to achieve better segmentation using watershed transform based on these improvement measures.Secondly,spectral feature is obtained from multi\|spectral remote sensing images,texture vector is achieved by Gabor wavelet and selected by Independence Component Analyses,and clustering based on the two features of objects.Finally,topological relationships between objects are fully considered in order to classify the uncertain objects after the former clustering.Results of experiments demonstrate that the new method can get desired classification results and improve the automatization of remote sensing data classification to some extent.
A method used for extracting multiscale features is applied to the optical remote sensing cloud images.They are decomposed to multiscale space and the features of images are expanded during the process,from which a multiscale feature vector can be acquired.Provided identical feature algorithm and classifier,it is illustrated by experiment that multiscale expanded features can help raise the precision of classification,from which better performance of classifying clouds and earth targets can be achieved.
Remote sensing images have been widely used in spatial visualization and decision making for urban or regional planning.In order to improve the methodologies of thematic imagery cartography for spatial planning,the content and categories of imagery maps,the framework of planning thematic imagery mapping,and the images functional roles in planning mapping process,are redefined and explained.Besides,a new strategy of syncretized visual design is proposed,which takes the harmonization between vector and raster objects,base and theme layers as its core problem,and the design of colors,symbols,space composition and decoration as its main task,as well as the configuration of visual variables as its key approach.As a conclusion,one map example demonstrates the strategys effectiveness on representing the plans concepts and spatial structures.
Satellite image fusion is always a focus in remote sensing field.According to data sources difference,image fusion can be divided into two broad categories:fusion of images using different sensors data and using same sensor data.Five recently proposed/modified fusion algorithms have been employed to test the fusion results of the two categories.The image pair,TM+ SPOT pan,was used to test fusion between different image sources,while the pair,IKONOS MS+ pan,was employed to test fusion between same sensor data.The study reveals that the overall results of fusion between same sensor data are better than those of fusion between different sensors image sources.The selected fusion algorithms have different performance in image fusion results between the two categories.The SVR transform is suitable for both categories of image fusion.It can greatly improve the spatial resolution,information quantity and clarity,but retain spectral information of the original multispectral image.The SFIM\|fused image has the highest spectral fidelity in both categories of image fusion,but has the lowest spatial frequency information gain.Although the MB transform can improve the spatial resolution of the original image,it generally failed to improve spectral fidelity,information quantity and clarity.The Ehlers transform is more suitable for image fusion between different sensors data while the WT is more applicable to image fusion between same sensor data.
Auto registration of remotely-sensed imagery is a concerned problem in remote sensing image processing and photogrammetry.In this paper,IDL(Interactive Data Language),which is a very popular programming language in data analyzing and image conversion,is contacted with GCPs(Ground Control Points) image database.By using correlation coefficient method,we do the auto registration.The results show that our matching approach performs perfect.It is not only high accuracy but also strong practicality.
Airborne LIDAR is a new technology that can obtain high\|precision three-dimensional geographical data quickly.Filtering process for LIDAR points cloud data is to separate the non\|ground points from the ground points.Several important useful filtering algorithms for LIDAR points cloud data\|\|mathematical morphology based filtering algorithm,slope based filtering algorithm,TIN based filtering algorithm,pseudo scanning lines based filtering algorithm,etc.have been introduced,discussed and contrasted.their advantages and disadvantages,the improving advice to each filtering algorithms also have been presented in the paper.
The techniques for estimation of aboveground biomass were studied in Fengning Man Autonomous County,Hebei Province,using SPOT5 images and filed sample measurement data based on the estimate method by vegetation types.The study results shown that a multiple regression model,which was composed of 4 band spectral reflectance of SPOT5 images and Mid\|infrared Vegetation Index (VI3) derived from SPOT5 images,can be used for estimating forest biomass,the coefficient of determination (R2) reached 0.540.Through the correlation analysis of bush and grassland biomasses with various vegetation indices,it was found that the exponential model based on Ratio Vegetation Index (RVI) was the optimal model for estimating bush biomass,and the NDVI\|based simple linear model was the optimal model for estimating grassland biomass,with R2 values of 0.711 and 0.790.The distribution map of biomass in Fengning county was made using SPOT5 images acquired in 2008.The map reflect that the total aboveground biomass (except the croplands) in 2008 in Fengning is 3.706×107 t,with a average of 51.223 t/hm2,in which,the total forest biomass is 3.578×107 t,the total bush biomass is 1.048×106 t,and the total grassland biomass is 2.277×105 t.
Phenology consistency information was extracted from MODIS NDVI time series data of plain single\|rice district northern Zhejiang.NDVI time series data were treated using discrete fourier transformation method in order to rectify the wrong data.Land use map was used to derive the NDVI time series data of cultivated land in study area.Maximum values of time series data per pixel were extracted to make analysis about the regional crop phenology characteristics.The result showed that rice had better phenology consistency than rape and wheat,and phenology information got from 8 days composite data was more detailed than that from 16 days composite data.Growing period response of rice to NDVI time series was much better than that of rape and wheat.The result indicates that the potential senses of MODIS NDVI time series to analyzing regional crop phonologies.
We present a comparative study of two object\|oriented land cover classification schemes based on high spatial resolution imagery in Beijing urban areas.Results indicate that optimized classification scheme produces a more enhanced accuracy than the generalized one.However,further comprehensive comparison reveals that the generalized scheme is more efficient and its classification rules can be easier to transport to additional areas of the same imagery and to other imageries of the same quality.In addition,land cover classification derived from generalized scheme is more systematic and robust.Hence,we conclude that if absolute accuracy is the desired goal for classification,optimized scheme is recommended; yet if the transportability and consistency are preferred,generalized scheme is more satisfactory,which also has important implications for timely and accurately land cover mapping,quantitative monitoring and assessing ecological consequences of urbanization and effective urban land planning and management.
Based on the research of theoretical analysis on three pattern recognition parameters(i.e.tracking or pattern matching techniques),and the work of contrasting three tracking techniques applied in deriving cloud motion winds,a possible warranty of the method of gradient analysis tracer selection can be got.A discrete formula for computing gradient is also provided.Further more,the method of gradient analysis tracer selection is consummated.Cloud motion winds are derived from the tracers selected by the consummated method and after a wind field analysis on the cloud motion winds,the cloud motion winds are compared with the rawinsonde winds.The result shows that the cloud motion winds have a good quality and a high density,and the wind structure of weather system can be seen clearly from them.
By the analysis technology of derivative spectrum,the quantitative relation of the LAI with the canopy derivative spectrum and their derived parameters were studied in different peanut varieties under different nitrogen levels.The results showed that the correlation of peanut derivative spectrum with LAI was stable in 680~750 nm of red\|edge region,which was positive in the range of 680~710 nm,but negative in the range of 710~750 nm.And their correlations arrived at the largest at 685 nm and 735 nm.Within the trilateral parameters,the amplitude parameters were superior to the area parameters and the position parameters,and only the area,amplitude and position parameters of red edge correlated best with the peanut LAI,whose correlation coefficients were -0.9345,-0.9869 and 0.7632 respectively.Among the derived parameters,RDr.b,RDr.y and NDDr.y were significantly correlated with the peanut LAI,while the other derived parameters were negatively correlated with LAI.The correlation coefficients of DSDr.b,DSDr.y and DDr.y with LAI were -0.9690,-0.9485 and -0.9764 respectively,all of which were higher.In conclusion,the first derivative spectrum,SDr.Dr,DSDr.b,DSDr.y and DDr.y of the two brands of 685 nm and 735 nm could be used to monitor the LAI of peanut.
The study is aimed to use CCD and IRS data on HJ\|1A/B satellite to monitor drought.It proposed the adapted application method for this new data source.Based on Vegetation Health Index which has been well applied in the world,the HJ data were used to monitor the emergency drought in Mekong river basin on March,2010.The result showed that the regional drought occurred in the majority of farmland in the Mekong river basin,and the region in China is the worst in terms of size and severity of drought.The changes on water area and water level in four hydropower stations which are located in the upstream of the basin were analyzed to discuss the hot topic:“Does upstream hydropower dams cause the current drought in Lower Mekong basin?” The result drew a conclusion that the dam construction was not directly related to the drought in Mekong river basin.This study showed the feasibility of HJ satellite applications on drought,and it would provide supplementary support information for policy\|making departments in China,even in Global.
Glaciers on the Tibetan Plateau play an important role in the earths climatic system.Regular survey of glacier change is almost impossible in most parts of the plateau.Remote sensing is a primary technique and becomes the only means in many places.GIS provides an efficient tool to analyze the status and the change of glaciers.We select the Lenglongling Mountain as the test area.Glacier variation in 1970, 1995, 1999, 2002 and 2009 were analyzed by means of satellite image and topographical map.The results indicate that the glacier area had decreased about 13.79% from 70s to 1995 and had decreased about 21.96% from 1995 to 1999, glacier area in 2002 had decreased about 10.54% compared with in 1999.And glacier area in 2009 had decreased about 6.35% compared with in 2002.
Ulan Buh Desert is one of Chinas major deserts.In recent years its rapid expansion has seriously affected the local ecological security.Desert vegetation is the most important ecological protection barrier in this region.Gaining the knowledge accurately of the distribution of vegetation is important.Calculated NDVI,and integrated principal component analysis combined with Gray Level Co\|occurrence Matrix texture analysis to analysis the ALOS image in the reserch area.Using NDVI and mean texture as the classification indices,the article determined the appropriate threshold range,and abstracted the vegetation information by using the decision tree method.The result shows that the decision tree method could use texture and other auxiliary information effectively,and achieve better classification results compared with traditional classification method.
We take Dongzhen Reservoir district of Putian as an example and present a methodology of exracting loquat information using support vector machine\|SVM and gray\|level co\|occurrence matrix from QuickBird image.Firstly,this paper calculating the textural measures using grey level co\|occurrence matrix and determining the optimum parameters for textural information by principal component analysis.Then the support vector machine was applied to classify the remote sensing imagery of the study area.Comparing with the result which depends only on spectrum information.The total classification accuracy for the former method has rised to 86.67% from 71.33%.Kappa coefficient change from 0.6410 to 0.8293.The increase of classification accuracy of exracting loquat information indicates that it is an effective method to fuse spectral and textural information on high\|resolution remote sensing classification.
Forest fire is a kind of worldwide natural calamity.It is extensively distributed with high occurrence frequency and destroys forest resources thus disturbing normal living order of people and leading to environmental deterioration.The Infrared Sensor carried by HJ\|1B (HJ\|1B IRS),its spatial resolution is 150 m and saturation temperature is more than 500 K.Its the only camera,which have been carried by Chinese satellite,to detect highest surface temperature in China at present.In this study,basing on analyzing the information of related bands of HJ\|1B IRS by using sampling method,an adapted windows thread condition forest fire identification methodology has been developed according to the character of HJ\|1B IRS.The automatic forest fire identification program has been developed by using HJ\|1B IRS Image and integration of background GIS data in IDL language.At the same time,by operating the program nearly one year,the fire identification method and identification results of precision have been validated by selecting the typical forest fires which have been taken place in northeast or south forest region of China.The validation results show that the truth precision is more than 90%,the missing identification precision low than 10%,but error is 0.So,the fire identification methodology can be satisfied the need for fire identification operation in China.
The relationships between NDVI and SAVI from MODIS(Terra) imagery on September 13 and 14,2004,and vegetation coverage derived from field measurements investigated at same time with MODIS data in central Tibetan Plateau are analyzed.Another hand,after selected typical grassland vegetation region in central Tibetan Plateau and whole Tibetan Plateau as two study areas,the accuracy of Carlson and Ripley algorithm of vegetation coverage is validated using field measurements in this paper.The main conclusions are as follows.
(1) The relationship coefficient between NDVI and vegetation coverage from field investigation is 0.95(R2= 0.90),between SAVI and vegetation coverage reaches 0.94(R2=0.89).
(2) There is high relationship between vegetation coverage based on the field measurements and estimation from Carlson and Ripley algorithm,coefficients are greater than 0.94; it was found that Carlson and Ripley algorithm is suitable for the middle grassland vegetation coverage.
(3) Overall,the vegetation coverage over Tibetan Plateau is low; the area of vegetation coverage lower than 20% covered more than 50% of total area.The vegetation coverage between 1%~10% is the largest area(35.36%) and it mainly distributed over northwestern area and south of Mountain Kunlun in Tibetan Plateau.The area of 100% of vegetation coverage is 122 538.88 km2 and it covered 10.72% of the total area,which distributed in southeastern Tibetan Plateau where dominated by forest vegetation.The distribution pattern of vegetation coverage over Tibetan Plateau decreases from southeast to northwest in Tibetan Plateau.
Vegetation coverage is one of the objective indicators that reflecting the basic conditions of vegetation,which is concerned by agriculture and ecology.A most potential and rapid method for measuring the vegetation coverage is to extract it from the digital photo of the land surface.However,there was a lack of mature method to realize this procedure precisely.This paper introduces a method that is imitating NDVI,which is used to process the digital photos and to extract the vegetation coverage rapidly.The accuracy of the proposed method is validated by the supervised classification to calculate the vegetation coverage.The comparison of the results of these two methods indicates that the imitating NDVI results are as good as the supervised classification ones.The imitating NDVI method is more rapid and automatic than supervised classification.This method proposed is valuable to precision agriculture practice.
Comprehensive and systematic permafrost background data play an important role in the Qinghai\|Xizang(Tibet) Plateau (QTP) permafrost research,offering basic scientific data for engineering construction,resource development,and ecological and environmental protection over the QTP.The ongoing work of National Infrastructure Project funded by the Ministry of Science and Technology of China titled “Investigation of permafrost and its environment over the Qinghai\|Xizang(Tibet) Plateau” will output a large amount of varied data from frozen soil background investigation.The system is specifically designed and developed as a data management Web application for the outputs of this research project,as well as for existing frozen soil data.Currently it manages drilling data,geophysical investigation data,soil profiles,vegetation investigation data,environmental monitoring data (including frozen soil active layer data,flux data,ground temperature,and meteorological observation data),and spatial data covering the study area.The 6 categories data are physically implemented as 23 data tables.The system includes 5 functional modules,i.e.,data input,management,query,display,and analysis and application modules.A variety of data visualization approaches have been implemented.We present the system and functional design,database design and key technology involved in the system implementation.Exemplary applications are also demonstrated.So far investigational data from the Wenquan field work conducted last autumn have been ingested into the system.More data will come into the system as the project advances.The paper offers a good example to future similar work to implement a frozen ground data and information system.
Discovering knowledge from spatial database is an important aspect for GIS application study.Discovering land use type knowledge from spatial database was discussed in Shimian country of Sichuan province.The forest resource investigation data were used to create GIS database,from which the landuse type layer was extracted.The raster database with the resolution of 10 m including DEM,annual temperature and annual precipitation were created by using GIS software.The knowledge of each land use type distribution along with the elevation,temperature and precipitation were discovered by the methods that the land use type layer was overlaid with the raster database,and the results were calculated.The spatial relationship knowledge among land use types was discovered by the method that the sharing boundary length of the land use type with another land use type was divided by the total boundary length of the land use type.The knowledge was benefit to the optimization use of the land and interpretation of the remote sensing images.The method of knowledge discovering can also be used in other regions or fields such as nature,society,economics and population.
In order to evaluate the influence of the debris on the inflatable antenna, the LS\|DYNA program was used to perform the analysis.We first simulate the gas in the reflector using solid elements, considering the coupling of membrane and gas. The result showed that the impact of debris can lead to gas leakage, the detail critical velocity with time was also analyzed. Finally we calculated the mass of gas needed to make up when adopting the continually making up scheme or inconsecutively one, which supports important statistics for the application of inflatable antenna.
A management service system of quasi\|real time processing for satellite data is designed based on the integration of Windows NT Service and socket application,a quasi\|real time satellite data auto\|processing system has been developed.A massive cloud\|eliminated database and a suited imagery info database have been set up without a large number of manual operations,IR\|brightness temperature tracing and anomaly warning for any monitored area has been implemented through the system.Through the development of this system,a lot of experiences in satellite thermal infrared remote sensing,the ground application system,the technology for processing the space\|earth integration observation data have been gained,and practical technology foundations and methods are provided for earthquake thermal infrared research.
Global change research is a cross\|century research theme organized by the international scientific and technological circles.It is now getting more and more attentions while the global environment problems become prominent day by day.Space observations is an indispensable and important method for global change research,it plays an important role in the research process.The tendency of scientific research could be reflected by bibliometrical analysis.Thomson Data Analyzer and Ucinet were used to do data mining and analysis of papers about space observations of global change research from SCIE database in this paper.The results indicate that space observations of global change research involved many interrelated fields,many researches were started from 1990,climate change,carbon cycle,land use change etc are the major research contents,remote sensing,modeling etc are the major research methods,The United States has a great advantage in this field.
