Wetlands are considered an integral part of the global ecosystem.Enhancement of their scientific management informed by quantitative,accurate and repeatable observations of wetlands' landscape would obviously be significant.Taking the northeast of the Sanjiang Plain as a case study,we use classification and regression tree (CART) algorithm for purposes of mining classification rules from training samples.Classification tree model of wetland information extraction was built from these samples through CART algorithm,which integrates spectral,texture and the assistant geographical characteristics.The classification results based on CART algorithm were checked by statistical confusion matrix accuracy assessment using field GPS samples.Validation shows that total classification accuracy is 82.65%,Kappa coefficient is 0.7935.The results had suggested that the accuracy of classification based on the CART algorithm was higher than the MLC supervised classification method.The developed method is portable,relatively easy to implement,and should be applicable in other settings and larger extents.
It has some advantages to detect the inundation extent using Synthetic Aperture Radar (SAR) images.In this paper,Change Vector Analysis (CVA) is a valuable approach for the surface inundation extent.As a result from the case study in Poyang Lake wetland,the multipolarized Envisat ASAR data is used to detect the inundation extent,and the change areas were extracted using the classification method of decision tree.Finally,the potential utility in Change Vector Analysis for change detection of SAR images was discussed.
Recently with the rapid development of economy,the great change of land use/cover would make land surface temperature increased.Urban heat island effect has become more prominent.In this study,we choose Wuhan city as an experimental area.Landsat 7 ETM+ images (July 9,2002.) was selected to retrieve land use/cover types by maximum likelihood method and land surface temperature using mono-window algorithm,and then computed landscape metrics and mean land surface temperature of all kinds of land use.Finally grey relational analysis was used quantitatively to analyze impacts of landscapes pattern on land surface temperature.The results show that: ① In the landscape pattern,water and build-up consisted of large patches and paddy and glebe consisted of small patches.② It was obvious that there is a thermal gradient between Central Business District (CBD) and the countryside.In terms of the spatial pattern of the land brightness temperature,the most extensive UHI was distributed in Hankou,Hanyang and Wuchang.Urban heat islands distribution in Dongxi Lake,Caidian,Hannan and Jiangxia was scattered with some little heat islands.③ Interspersion and Juxtaposition Index (IJI) and Percentage of like Adjacencies (PLADJ) and Largest Patch Index (LPI) were the most important factors that influence the land surface temperature.
Paleoclimate can be extricated from alluvial fan by using full-polarized Synthetic Aperture Radar (SAR).Polarization coherence ρ is an important parameter to characterize the ground scatterers (|ρ| is polarization coherence coefficient,the phase of ρ is phase difference).In this paper,the distribution of ρ is extricated from Bodunqi Alluvial Fan using Shuttle Imaging Radar-C (SIR-C) L band fully-polarized data.The results show that ρhhvv(ρ between Shh and Svv) can well characterize the alluvial fan.Besides,we researched the relationship between ρ and ground parameters of Bodunqi Alluvial Fan such as roughness and moisture in this paper.It indicates that the phase difference between Shh and Svv and the |ρ| between Srr and Sll can be affected by ground parameters.
From December 2002 to January 2003,an Arctic stratospheric sudden warming occurred,which led to a strong distortion of thermodynamics fields and chemical characterization.Data from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on board the European research satellite,Environmental Satellite (ENVISAT) is used to analyze the event,and comparison with the NCEP temperature data and ozone sonde measurement.The results show that difference between MIPAS data and NCEP or ozone sonde measurement is small.During the sudden warming event,the increasing temperature spread downward to lower stratosphere.Retrieved horizontal and vertical distributions of N2O and CH4 show good consistency with potential vorticity field for the entire period.O3 and H2O are also limited by polar vortex,volume mixing ratio of O3 increased during the sudden warming,and O3 outside the vortex transport into the vortex.NO2 is not limited by polar vortex,and show low value over the polar region.HNO3 shows large value over polar region,but is not agreement with the polar vortex.
It is very difficult to classify forest vegetation in mountain areas because of the impact of complex terrain.In this paper a new method,sub-region classification based on multi-temporal remote sensing images,is proposed to deal with the classification of forest vegetation.Firstly,sunshiny and shadowy region was classified using terrain factors and reflectance data.This technology could avoid the problem of "different spectrum with the same feature" and "different feature with the same spectrum" in some region.Secondly,the forest vegetation could get better classification precision by avoiding the interactions of different plants with multi-temporal images.So it was enhanced that the separability of coniferous forest and broadleaf forest.Finally,the classification result showed that accuracy could be greatly improved by using sub-region classification based on multi-temporal remote sensing images.The overall accuracy and kappa coefficient was 81.3% and 0.72,respectively.So the method delivered in this essay has obviously technological advantages and important application potentiality in forest vegetation classification.
The non-spectral characteristics play an important role in assisting the image classification in remote sensing,as these characteristics can avoid the mistake classification made by the "the same object with different spectrum" phenomenon.The texture characteristic is one kind non-spectral characteristic.It is also helpful to improve the classification precision.In this paper,the author takes the Delta Oasis of Weigan and Kuqa rivers for example,using ETM+ data; discussing the method of extracting of soil salinization.This paper reports the classification method based on support vector machine(SVM),and introduced the fundamental theory of SVM algorithm,then incorporating of spectrum and texture information.The classification result is compared with minimum distance classification，maximum likelihood classification,neural net classification and single data source(spectrum)SVM classification qualitatively and quantitatively.The research result shows that this method can effectively solve the problem of low accuracy and fracture classification result in single data source classification,it has high spread ability toward higher array input,the overall accuracy is 93.1795%,which increases by 3.1618% comparing with single data source SVM and increases by 4.8252% comparing with maximum likelihood classification,and increase by 7.4756% comparing with neural net classification,even increases by 11.1029% comparing wit minimum distance classification and thus acquires good effectiveness.The classification results were easier interpreted when compared with the conventional classification method.Therefore,the classification method based on SVM(Support Vector Machine)and incorporate the spectrum and texture information can be adapted to RS image classification and monitoring of soil salinization,furthermore,provides and effectives way for the things remote sensing information extraction.
In this paper,the main city of Shanghai is chosen as the study target,based on Landsat ETM+ images.Using Mono-window Algorithm to calculate land surface temperature,spatial variance of land surface temperature is analyzed by applying the Geostatistical method.The results show that the spatial difference of land surface temperature is significant and asymmetric distribution of east-west direction.The land surface temperature of Pudong area is obvious lower than Puxi area.The lowest temperature zone is located at the junction of the southern part of Pudong District and Nanhui District,but the highest temperature zone is distributed in Puxi area,including city centre along the Huangpu River,the southern of Baoshan District and northern of Putuo District.The land surface temperature is between highest and lowest temperature in other districts.From the view of the spatial variance of land surface temperature,at the lesser spatial scales,spatial heterogeneity caused by random factors is larger proportion of the total,and spatial autocorrelation is unconspicuous.With the scale augmenting,the spatial heterogeneity caused by random factors share decrease and spatial autocorrelation increase.When the grain size is 180m and 540m,the land surface temperature has the moderate degree of the spatial autocorrelation,and when the grain size increases to 1080m,the spatial autocorrelation of land surface temperature is obvious.
The application study highlights the potential of the synthetic aperture radar (SAR) imagery for South Korea's oil leak monitoring which happened in NOV.2007.Firstly,the paper analyzes the mechanism and limitations of SAR monitoring oil spill;secondly,the ability of ENVISAT-ASAR data as a case in the detection of oil spill pollution was carried out in this study.The digital image processing techniques included image enhancing,speckle filtering,edge detection filtering,,and image classification.In the end,based on the SAR comprehensive information,the edge of the oil spill was delineated.The edge overlay with sea wind and other important factors in GIS,the distribution,diffuse and environmental influence of oil spill can be mapped.This would provide a lot help for decides maker.
It demonstrates a procedure for rapidly estimating the intensity of surface urban heat island (SUHI) from direct-downloaded NOAA/AVHRR HRPT data using the ENVI image analysis software operating in batch mode.The processing stream provides for reading level-1b data,calibration,geometric correction,sub-setting imagery,calculation of surface temperature,cloud screening and image statistics.Then,this procedure was used to investigate the intra-annual characteristics of daytime SUHI intensity in Jinan city,Shandong province.The results show that:① SUHI phenomena exist over a majority of months throughout the year,especially from April through September;② the mean SUHI intensity is 2.77℃ and the most intense effect (more than 10℃) occurs during the period from the last ten-day of July to the middle ten days of August;③ the significant SUHI mainly appears in the summer,the spring takes second place,and the UHI in the autumn and the winter seems not obvious;④the SUHI intensity correlates positively to urban and suburban surface temperature with low regression coefficients.
Taking the establishment and management of land use database in Hebei Haixing county as example,this paper elaborated how to gain the land utilization information by means of RS technology,and how to carry out the open country investigation,gather the changing data and update the database by means of GPS technology,and how to use the GIS technology to establish and manage the database from beginning to end.
Impervious surface percent is an important index to indicate urbanization level; it can be used to study the change and spatial extension of urban area quantitatively.Multiple endmember spectral mixture analysis method was used to extract sub-pixel level of impervious surface percent from TM image.This paper applies that method to extract the impervious surface percent of Nanjing Metropolitan development area from two temporal TM images.Then based on impervious surface percent,the change and spatial sprawl of study area was analyzed qualitatively and quantitatively.
Based on the analysis of the characteristics of different remote sensing satellite ground pre-processing systems,this paper points out several factors which restrict the implementation of general ground pre-processing system platform.A new multi-satellite ground pre-processing system based on workflow technology is proposed.And the scheme is applied to the practical project successfully.So the scheme allows for the easy extension of processing functions of different satellites in ground pre-processing system.
A non-linear strength wavelet filtering algorithm is proposed to remove noise from the hyper spectral images. First, the spectral curve is decomposed into high frequency coefficient and low frequency coefficient with wavelet transformation. Deviation is calculated with low frequency parts to determine the threshold of noise and detail feature. A non-linear filtering algorithm is proposed to deal with the noise and detail feature of high frequency coefficient with the deviation threshold of low frequency coefficient. Comparing with the result of mean filter smoothing and least squares smoothing, the non-linear strength wavelet filtering algorithm (nLWF) can obtain better effect in noise remove and detail feature conversation.
The spatial synchronization of the antenna footprints is a big methodical and technological challenge in spaceborne/airborne hybrid bi-static SAR(SA-BSAR),due to the fact that there is great difference between the velocities of the platforms.A method by performing beam steering on both sides has been given in the published literature.However,there are some disadvantages in that approach such as short imaging time,requiring complex processing and low azimuth resolution.To overcome these disadvantages,a new approach based on wide-beam illumination is proposed.The feasibility of the new approach is demonstrated by both numerical analysis and simulation results.Several performance parameters for the two methods are quantitatively compared.When the new approach is applied,the scene extension is slightly shorter while the imaging time is much longer and the azimuth resolution is higher.Advantages and disadvantages of each approach and their respective scopes of application are analyzed.
In order to solve the problem of large distortion on InSAR images,based on comparison of several registration methods on SAR and optical sensors images,a robust algorithm composed of coarse registration,Harris corner detection,correlation matching,Delaunay Triangulation is proposed.It has been proved by simulation that the method is applicable to InSAR complex images with large distortion.The accuracy of registration is at 0.1 pixel level.
Based on Lynett and Liu's horizontal fully two-dimensional internal solitary wave propagation model,this paper studies on series of SAR imaging of the internal wave polarity conversion process.After analyzing the simulated images during the depression internal waves converting to elevation ones,the conclusion that the radar signature of internal waves will be seriously weakened or disappeared during the polarity conversion was validated.Through comparing with the local ERS-2 satellite image this simulation also validates the effects of ocean topography on the propagation of internal waves such as fission and isobaths\|parallelized propagation direction.
According to the analysis of radiometric equalization,moment matching and histogram matching,an effective method for removing the stripe noise in CBERS-02 data is developed.The main idea of this method is,first of all,using histogram matching to remove the stripe noise along-track on the image,then applying linear directional filtering to remove the residual stripe noise along-track and across-track in the image.Results of CBERS-02 data showed that the proposed algorithm reduced stripe noises without degrading image quality.To evaluate performance of the proposed method,quantitative and qualitative analyses were carried out by visual inspection and quality indexes of destriped images.
As an important complementarity of aerial remote sensing,the UAVRSS(Unmanned Aviation Vehicle Remote Sensing System) has many advantages in specific field.Firstly,the paper described 4 times aviation experimentations,then based on the experiment images and aviation data of UAV,all images were mosaicked to a panorama image.And the mosaicked image was analyzed from many factors for evaluating the image quality.Finally,some improvements to the UAV image quality were discussed.
CBERS-02B carries a high-resolution and panchromatic HR camera and a multi-spectral CCD sensor.HR is high spatial resoluted and CCD is high spectral resoluted respectively.A intergrated and precise image can be acquired by fusing these two images.HSV、HPF、Brovey、IHS、SFIM and Wavelet transform are used to fuse Beijing'image of CBERS-02B HR and CCD.Through preservation of spatial detail and spectral information,fusion results are evaluated qualitatively and quantificationally.Several appropriate transforms are gained then.
Remote sensing has profound implication in ecosystem investigation and research.However,traditional multispectral remote sensing data usually focused on the mass screening.It was difficult to be used to inverse the complicated properties and biochemical parameters of ecosystem for the limitation of spectral resolution.Hyperspectral remote sensing,which measure large numbers of narrow spectral bands,could greatly improve the accuracy and types of input parameters of ecosystem models.In present study,we systemically reviewed the implication of hyperspectral remote sensing in ecosystem processes and properties based on expounding the principle and characteristics of hyperspectral remote sensing,and proposed the potential implication of hyperspectral remote sensing in ecology.
Synthetic aperture radar (SAR) has become one of the important tools to map the shallow water bottom topography.In this paper,progress on remote sensing of the shallow water bottom topography by SAR has been reviewed.Especially,SAR imaging mechanism and SAR imaging theory of the shallow water bottom topography and the shallow water bottom topography mapping by SAR are mainly introduced.Meanwhile,we discuss some issues in present of the study on remote sensing of the shallow water bottom topography by SAR and the research orientation in future.
