最新刊期
卷 16 ， 期 6 ， 2012
- 摘要：Ground reflectance with different soybean residue covers（SRC） were measured with HR-768 portable spectroradiometer.Coincident with spectrum measurements,soybean residue cover were measured using photographic method.Linear regression analysis was used to evaluate the correlations between soybean residue cover and spectral reflectance,as well as its first order derivative and derived indices（namely ratio index and normalized difference index）.Characteristics of spectral responses of soybean residue were analyzed.With relative spectral response functions,bands reflectance of MODIS,TM,HJ-1B CCD1 and IRS were simulated respectively to establish soybean residue cover estimation model.The results indicate that soybean residue can be distinguished from soil using its unique absorption feature in the spectral range of 2050 nm to 2150 nm and 2250 nm to 2350 nm.The spectral characteristics of soybean residue are similar to that of corn and wheat residue except for an absorption feature in the spectral range of 920 nm to 967 nm.Parameters that are suitable for soybean residue cover estimation were identified using hyperspectral data,which includes reflectance at wavelength of 941.6 nm,first derivation of reflectance at wavelength of 2151.8 nm,normalized difference index between reflectance at wavelengths of 1461.3 nm and 2404.4 nm,and ratio index between reflectance at wavelengths of 2247 nm and 608.6 nm.Taking broad band data as data source,ratio index between shortwave infrared reflectance and red reflectance performs the best in soybean residue cover estimation.关键词：soybean;fraction of crop residue cover;spectral characteristic;linear regression;estimation model
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发布时间：2021-06-10 - 摘要：In high resolution X-band POLSAR image,the water body,cement roads and the bare soil are always at low level radar backscattering signals,which is caused by no Bragg scattering phenomenon in smooth surfaces.The prevalent H/AlphaWishart and Freeman-Durden methods cannot distinguish those targets.This paper explores the improved X-band classification algorithm based on the pre-classification result for low backscattering objects in urban areas.The occurrence plane which is combined by entropy and the standard deviation of the co-pol channel diff phase is used to refine the pre-classification.The experiments show that the overall accuracy is above 80% and Kappa coefficient is higher than 0.7.The improved method improves the potential to distinguish the mixture classes of the low backscattering objects.关键词：CETC38-XSAR;POLSAR;classification;entropy;phase standard deviation
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发布时间：2021-06-10 - 摘要：The multi-spectral optical remote sensing image registration is one of the important steps among the ground station preprocessing chain.The accuracy of registration is crucial to product quality assurance.Generally,an image correlation method based on pixel DN is widely used in the multi-spectral images registration processing.However,the registration accuracy of correlation method depends on the character of the landscape in the space camera’s view.The discrepancies of band-to-band registration are commonly observed in those images which are short of manifest feature points such as large scale water surface,desert,meadow,forest and seaport.In this paper,a linear CCD geometric bias model along CCD array and orbit directions of the BJ-1 small satellite multi-spectral camera is presented.The measured geometry bias is a constant value which is derived from the large amount of tie points between NIR and red or green and red bands along the image row and column directions.Finally,the experiment shows that the matched BJ-1 multi-spectral images can achieve sub-pixel registration accuracy without calculating the pixel DN correlation value between the raw images.And the proposed method has been used in the BJ-1 and DMCUK2 small satellite multi-spectral images registration preprocessing.关键词：remote sensing satellite;preprocessing;band registration;sub-pixel;geometric model
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发布时间：2021-06-10 - 摘要：As the Gaussian radial basis function（RBF） is based on the Euclidean distance of two spectral vectors,it is sensitive to spectral curve variations resulted from radiation intensity variation.When the spectral curves of same materials are different,the detection performance of the RBF based OCSVM objective detector will degradate.In order to solve this problem,a nonpositive definite kernel,named as the spectral Angel Cosine Kernel Measure（SACKM）,is proposed based on the spectral curves similarity description,and was applied to object detection based on an indefinite OCSVM method in hyperspectral imagery.Finally,the experiments were carried out with two hyperspectral images,which are used to validate the proposed method.关键词：hyperspectral imagery;non-positive definite kernel;indefinite one-class SVM;object detection
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发布时间：2021-06-10 - 摘要：Continuous simulation of crop growth parameters at spatial-time scale is a key technique for monitoring crop growth status and precision agriculture.This paper realized the spatial-time scale continuous simulation of growth parameters with the assimilation of remote sensing information into crop growth model,monitoring growth parameters changes on spatial-time scale.Construct a model named WOPROSAIL with the coupling of crop growth model WOFOST and canopy radiative transfer model Prospect+Sail（PROSAIL）.Then particle swarm optimization（PSO） algorithm was used to minimize difference between observed values of soil adjusted vegetation index（SAVI） derived from CCD data and simulated values of soil adjusted vegetation index（SAVI’） calculated by coupling model for optimizing initial parameters of WOFOST.Regionalization of parameters was achieved with MODIS data retrieval,then by inputting these regional parameters,optimized WOFOST model,initial parameters of which were optimized,was driven for each pixel and then regional growth parameters were calculated,achieving continuous simulation of crop growth parameters on spatial-time scale.Finally,a region scale remote sensing-crop simulation assimilation framework model named RS-WOPROSAIL was constructed.The results indicated that assimilation model solved the discontinuity of spatial scale simulation by crop growth model and time scale retrieval by remote sensing information.Growth parameters simulated by optimized crop growth model,including leaf area index（LAI）,weight of storage organs（WSO） and total above ground production（TAGP）,preferably reflected the changes of rice growth status on spatial-time scale,and the relative error between simulation yield and actual measurements was 27.4%.关键词：crop growth model;prosail model;particle swarm optimization algorithm;assimilation;crop growth parameters;spatial-time scale continuous simulation
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发布时间：2021-06-10 - 摘要：Gaussian process（GP） represents a powerful theoretical framework for Bayesian classification.Despite GP classifier have gained prominence in recent years,it remains an approach whose potentialities are not yet sufficiently known in remote sensing community.This paper gives a thorough investigation of GP CLASSIFIER for high resolution（HR） multi-temporal image change detection.Firstly,we give a detailed analysis of the capabilities of GP classifier in theory.Secondly,we elaborately explore the advantages and disadvantages of the GP classifiers.Finally,we design several experiments to test the performance of the GP classifier for HR remote sensing image change detection.Moreover,we propose a novel approach for improving the capacities of GP classifier in remote sensing image change detection.The proposed context-sensitive change detection method is achieved by analyzing the posterior probability of probabilistic GP classifier within a markov random field（MRF） framework.In particular,the method consists of two steps:（1） A supervised initialization is founded on a probabilistic GP classifier;（2） A MRF regularization aims at refining the posterior probability by employing the spatial context information.Five experiments carried out on HR remote sensing image set validate the power of GP classifier for change detection and also the effectiveness of our proposed methods.关键词：Gaussian process（GP）;change detection;high resolution（HR）;support vector machine（SVM）;markov random field（MRF）
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发布时间：2021-06-10 - 摘要：As one of the most important payloads on Chang’E-1 satellite,interference imaging spectrometer（IIM） has acquired large amount of hyperspectral data.However,it is still a great challenge to retrieve minerals distribution information of the lunar surface due to the limited spectral wavelength range of IIM data（480—960 nm） which does not cover spectral absorption features of lunar minerals completely.At present,precise quantitative mineral distributions or credible surveys of lunar surface are lacking to validate the retrieved results.In this paper,we perfomed simulation of IIM spectral data based on spectral linear mixing method with four main lunar minerals（plagioclase,clinopyroxene,olivine and ilmenite）.We analyzed the accuracy of mineral endmembers extraction and implementeda preliminary application with true IIM data.We simulated the spectra of lunar mare and highland according to different proportion of plagioclase and ilmenite respectively.We added random noises of the same trend as IIM and employed four endmember extraction approaches(vertex component analysis,independent component analysis,minimum volume simplex analysis,simplex identification via split augmented lagrangian to extract endmembers.We used spectral angle distance（SAD） as a criteria for accuracy analysis.The results show that all the SADs of endmembers extracted by MVSA and SISAL are lower than 0.1.Plagioclase（the SADs that are lower than 0.015） can always be extracted by all approaches.All SADs of clinopyroxene and ilmenite are lower than 0.1 with olivine having the lowest extraction accuracy.关键词：lunar;mineral;endmember extraction;Chang’E-1;IIM simulation
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发布时间：2021-06-10 - 摘要：To build a comprehensive calibration field for airborne sensors,a set of artificial targets were designed during 2008 and 2009.The targets include resolution bar target,siemens star target,reflectance target,MTF（modulation transfer function） target,and spectral characteristic target for spatial-resolution evaluation,radiometric and spectral calibration of optical sensors.The targets can be washed,spliced,and reused,corresponding to high resolution and high flexibility of airborne remote sensing.To test optical characteristics of the targets,in-situ spectral measurement and bidirectional reflectance factor（BRF） measurement were conducted on reflectance target,MTF target and spectral characteristic target.The results show that,the targets have good spectral,lambertian and contrast characteristics,which can be used in airborne sensor calibration experiments and related applications.In this paper,the design and optical characteristics test of the targets are introduced in detail,which set an example for the design of aerospace and airborne remote sensing calibration field in future.关键词：airborne sensor calibration field;optical target;lambertian characteristic;radiometric calibration;spectral calibration
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发布时间：2021-06-10 - 摘要：The availability of very high resolution（VHR） satellite imagery has made analysis of remotely sensed data an increasingly effective tool for detection of post-earthquake urban building damage.While methods that use spectral information alone are often ineffective owing to spectral similarity between undamaged and damaged buildings,the detailed structure information discernable in VHR images makes it possible to add spatial and temporal features in the detection.This paper proposed a method to extract multi-temporal texture by the Pseudo Cross Variogram（PCV） and multiband texture by the Multivariate Variogram（MV）.The derived texture features were combined with spectral information for building damage detection in 2003 Bam earthquake using multi-temporal Quickbird images.The performance of the two texture features was evaluated at both optimalscale level and multi-scale level.The results showed that incorporating multi-temporal and multiband textures could significantly increase detection accuracy,and that multi-scale textures performed better than uni-scale textures.关键词：urban building damage detection;multiband texture;multi-temporal texture;multi-scale;high resolution;geostatic texture
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发布时间：2021-06-10 - 摘要：It is available to analyze on-orbit performance stability of MWRI by statistic histogram data of earth cold targets with stable brightness temperature.This paper analyzed on-orbit performance stability of MWRI by adopting the brightness temperature data onboard FY-3（02） satellite during February and July in 2011,showing that the MWRI onboard FY-3（02） meteorology satellite performs stable on-orbit,and the max fluctuation of the coldest reference values of all the 10 channels are less than 1.8 K.关键词：on-orbit performance stability;Earth cold target;statistic histogram method;microwave radiometer imager;FY-3
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发布时间：2021-06-10 - 摘要：Empirical sea surface temperature（SST） and sea surface wind speed（SSW） retrieval algorithms are developed,and validated based on the synchronous in situ data of Tropical Atmosphere Ocean project（TAO） buoy and the bright temperatures of FY-3B Microwave Radiometer Imager（MWRI）.The root mean square error（RMS） of the SST retrieval algorithm based on the ten channels’ bright temperature（TB） is 0.81℃,and the coefficient of correlation is 0.77.The results for SSW retrieval algorithm are 0.97 m/s and 0.78 respectively.关键词：FY-3B MWRI;sea surface temperature;sea surface wind speed;Tropical Atmosphere Ocean project;statistical retrieval algorithm
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发布时间：2021-06-10 - 摘要：City is a very important land cover type on the earth,making understanding city microwave emissivity essential in improving soil moisture retrieval accuracy using passive microwave remote sensing data,especially in urbanized regions.In this paper,time series Advanced Microwave Scanning Radiometer for Earth Observing System（AMSR-E） data in 2008 and other auxiliary data were used to extract and analyze the characteristics of city emissivity in China.During the process,radio frequency interference（RFI） in each pixel was evaluated first and the effects were removed before emissivity calculation.Also we studied the characteristics and influencing factors of city emissivity during the year.The results show that with the extraction method,only two pure city pixels in China are found,which are Beijing and Shanghai,respectively.Satellite observed city brightness temperature can be affected by RFI,but its effects varied between cities,bands and sensor crossing time.After eliminating RFI,the city emissivity fluctuated slightly in a year and was more stable in descending time than in ascending time.Rainfall played an important role in city emissivity variation.There was an obvious negative correlation relationship between city emissivity and rainfall when rainfall reached a certain value.关键词：city microwave emissivity;RFI;characteristic analysis;rainfall;China
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发布时间：2021-06-10 - 摘要：Using split window algorithms developed by Sobrino,added a sufficient and simple cloud detection process for MODIS L1B data.Then based on land surface classification（land,water,snow & ice）,retrieved four land surface temperature images for clear sky in Naqu area over Tibetan Plateau in January,April,June and October in 2007,respectively.After that the derived LST was compared with the MODIS daily land surface temperature product and in-situ data from the Coordinated Enhanced Observing Period（CEOP） Asia-Australia Monsoon Project（CAMP） on Tibetan Plateau（CAMP/Tibet）.The results showed that the LST derived from the improved Sobrino method was in good accordance with the MODIS product and the average difference between LST and in-situ measurements was only 1.435 K.关键词：Tibetan Plateau;MODIS;split window algorithm;cloud detection;land surface temperature
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发布时间：2021-06-10 - 摘要：The discrete method is used to simulate emissivity of one dimension of rough surface with row structure.Compared to the emissivity measured by ground radiometer,the bias between measured and simulated emissivity is less than 0.01,and this confirms that the discrete method is feasibility to simulate emissivity of rough surface with row structure.At a given row structure,the difference of emissivity between row structure and flat smooth surface changes with observed azimuth angle,and the value falls in the range of 0.02 and 0.05.This indicates that emissivity of row structure surface is anisotropic,and it should be considered in the process of modeling microwave radiation of row structure surface.In addition,the error of soil moisture inversion caused by neglecting the existence of row structure is analyzed across different soil moisture,and results show that the absolute error of soil moisture is between 0 cm 3 /cm 3 and 0.1 cm 3 /cm 3 when soil moisture changes from 0.02 cm 3 /cm 3 to 0.5 cm 3 /cm 3.This error is greater than the error tolerance limit of soil moisture inversion.Therefore,in the process of farmland parameter inversion from passive microwave remote sensing,surface row structure effect cannot be ignored.关键词：row structure;soil moisture;microwave remote sensing;surface roughness
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发布时间：2021-06-10 - 摘要：Remote sensing cloud services are the remote sensing application services provided through a network as a way of on-demand sharing of integrated remote sensing information and technological resources based-on cloud computing.Up on the analysis of service models and technical requirements,the author highlights the key technologies of remote sensing cloud services,including remote sensing data cloud storage,processing,application and security.We propose an architecture and functional design of the remote sensing cloud service platform and introduce a prototype developed by our R&D team.This remote sensing cloud service prototype allows users to choose required remote sensing data and software,and automatically deploys them to a virtual computer that users can access through Internet to perform their remote sensing data processing and application.Experiments show that the remote sensing cloud service platform can gather remote sensing information,software and computing resources from different providers,and provides them for sharing on user’s demand.Such a remote sensing service platform can significantly promote remote sensing to public users and a healthy development of the remote sensing industry.关键词：remote sensing cloud services;remote sensing services;service platform;cloud computing;cloud services
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发布时间：2021-06-10 - 摘要：<正>中国NO卫星遥感监测图NO2浓度是评价近地表空气质量的一项重要指标,大气中NO2的时空分布变化对环境和气候具有显著影响。中国科学院遥感应用研究所大气遥感研究室开展了利用卫星遥感数据监测中国区域NO2浓度时空变化特征的研究。封面图片为利用OMI传感器获取的2011年中国NO2年平均浓度专题图,显示出中国区域NO2的空间分布格局。卫星遥感监测NO2技术可弥补地面站点监测在空间尺度上的不足、便于对大气污染
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发布时间：2021-06-10
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