最新刊期
卷 16 ， 期 4 ， 2012
- 摘要：Traditional change detection approaches from multi-temporal remote sensing images are mainly based on spectral information in original images,without utilizing other derived features,such as texture,geometrical structure and shape.With the increasing spatial resolution in remote sensing imagery,change detection only relying on spectral information cannot guarantee the completeness and accuracy of change targets,suggesting the importance to integrate the merits of different features.After extracting multiple features from original images,two change detection procedures based on information fusion strategies are proposed in this paper:weighted similarity distance in one-dimensional feature space,and fuzzy set theory and support vector machines in n-dimensional feature space,respectively.Multi-temporal QuickBird high-resolution images are used as experimental data for land cover change detection over urban areas,and the results demonstrate the effectiveness of the proposed method.By integrating the merits of different features,the stability and applicability can be improved,and the structure and shape can be well preserved to highlight the important change targets at the same time.关键词：change detection;information fusion;multiple features;fuzzy set theory;support vector machine
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发布时间：2021-06-10 - 摘要：Considering the low accuracy of Synthetic Aperture Radar （SAR） image segmentation in the marine spill oil detection,a segmentation method of marine spill oil images based on Tsallis entropy multilevel thresholding and improved Chan Vese （CV）model is proposed in this paper. First, the multi-threshold selection algorithm based on Tsallis entropy is used to make a coarse segmentation for marine spill oil images. The obtained spill oil region and its coarse contour provide local region and initial contour for CV model, respectively, which are used to reduce the scene complexity of CV model and its sensitivity to initial situation.The traditional CV model only considers the mean value of each region of image instead of the local information of image. Though it can get non-gradient defined image boundary, there are errors in the segmented results. We use an improved CV model with the motion factor, thus the segmentation errors are reduced and the convergence speed is increased. Experimental results show that the our method not only dispenses with initial condition, but also ensures accurate segmentation boundary and efficient operation.关键词：marine spill oil detection;Synthetic Aperture Radar remote sensing image;image segmentation;Tsallis entropy;improved CV model
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发布时间：2021-06-10 - 摘要：Considering the uncertainty in image matching caused by repetitive textures and occlusions, this paper presents a multi-view image matching algorithm for feature point under the moving Z-Plane constraint. This algorithm projects the feature points extracted from multiple images onto different height planes, then uses the grid cells in the Z-Plane to constrain the corresponding matching candidate. It carries on the selective matching for multiple images depending on the projection rays in the grid cell, so as to avoid the problem caused by occlusions. Finally, the validity of the algorithm proposed in this paper is verified by the experiments using four UltraCamX （UCX） digital aerial images, the algorithm is shown to have reliable matching results.关键词：multi-view image matching;feature points matching;moving Z-Plane constraint;grid cell;occlusion
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发布时间：2021-06-10 - 摘要：We presents an effective signal splicing method for dual-receiver mie scattering lidar.The main idea of this method is to find the best spliced region where both near-range signal and far-range signal have high signal-to-noise ratios and to obtain the functional relationship between these two kinds of signals so as to achieve effective splicing and retrieval of near-range signal and far-range signal.The signal splicing result has both advantages of low detection dead zone in near-range signal and high detection height in far-range signal.The signal retrieval result demonstrates that this method can splice signals accurately andobtain highly accurate optical properties of aerosols.关键词：dual-receiver;lidar;aerosol;signal splicing;atmospheric remote sensing
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发布时间：2021-06-10 - 摘要：Based on the 10-year（2001—2010） time series of Moderate-resolution Imaging Spectroradiometer（MODIS） Normalized Difference Vegetation Index（NDVI） products and meteorological station data in the area of Southwest China,we extracted the NDVI values for the footprint of meteorological measurements and calculated the percentage of precipitation anomaly（Pa）and D index（difference between precipitation and potential evapotranspiration） as two drought indices.We then involved the information on vegetation types（Vegetation type map of China’s landmass,2000） conducted a compressive spatial-temporal regression analyses against these two meteorological drought indices and NDVI anomaly at seasonal time scales.The results showing that:（1） For most vegetation types,NDVI anomaly significantly corresponded to D index with a lag of about one month（R2>= 0.7,P<0.01）;（2） These correlations were higher for the drought-sensitive vegetation types（i.e.dry land:R2= 0.83;grassland:R2=0.71） than other types;（3） The spatial distribution of NDVI anomaly was relatively consistent with that of D index especially in drought season while it was only consistent with Pain very drought season or for drought sensitive vegetation types.关键词：NDVI;drought;percentage of precipitation anomaly;D index;Southwest China
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发布时间：2021-06-10 - 摘要：In this paper,the split window technique and the atmospheric motion vectors technique are combined to retrieve the wind vectors from the 11 μm and 12 μm channels on the VISSR onboard the FY-2E geostationary satellite.The sensitivity analysis for at-sensor radiance under different atmosphere conditions indicate that it is possible to treat sand aerosol as tracer of difference images to achieve wind vectors in the low-level moisture fields of the dust outbreak region.On difference image,the gray value of the sand tracer is too small to be used by the Cloud-motion Wind Inferring System（CWIS）,so the linear equationis used to amplify the difference.Finally,a comparison between the wind field over dust storm outbreak area extracted from the difference images using this technique and that obtained from the NCEP reanalysis data shows a good relative accuracy.As a result,the VISSR split window could be used to retrieve wind vectors in the low-level moisture fields over relatively cloud-free areas of the dust outbreak regions.关键词：dust aerosol;difference image;wind field in clear sky region;dust storm track forecast;VISSR split windows channels
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发布时间：2021-06-10 - 摘要：Development of remote sensing makes it possible to estimate Gross Primary Productivity（GPP） regionally.In recent years,a lot of researches on GPP estimation based on remote sensing data were conducted.In this study,meteorological and moderate-resolution imaging spectroradiometer（MODIS） data at A’rou（AR） freeze/thaw observation station,which is located in upper stream of Heihe River Basin,was collected to drive four remote-sensing based GPP models:Vegetation Photosynthesis Model（VPM）,Temperature and Greenness model（TG）,Vegetation Index model（VI） and Eddy Covariance-Light Use Efficiency model（EC-LUE）.GPP observed by Eddy Covariance（EC） was used to validate the results from the four models.It is indicated that GPP,NEE and ER at AR station were 804.2 gC/m2/yr,129.6 gC/m2/yr and 673.6 gC/m2/yr,respectively in 2009,indicating that 83.8% of carbon fixed by photosynthesis was released to atmosphere by ecosystem respiration.All the four models can predict GPP of alpine meadow very well.Determination coefficient between observed GPP and predicted GPP was larger than 0.94in 2009,and was larger than 0.84 during growing season.关键词：alpine meadow;gross primary productivity;light use efficiency model;MODIS;eddy covariance
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发布时间：2021-06-10 - 摘要：In order to improve public participation in urban spatial planning and properly deal with spatial conflicts among all kinds of actors participating in urban spatial planning,an interactive urban spatial planning model based on multi-agent systems and a social system（multi-agent systems）.Agents participating in urban spatial planning can exchange knowledge and information with each other frequently,and f inally achieve a consistent decision to form an acceptable urban planning scheme through feedbacks and coordinations.The model is further applied to simulate site selection of construction project in Yuelu District of Changsha City and results show that this model not only better simulates the interaction among various agents under different scenarios,but also provides solutions to spatial conflict in the process of multi-actor urban planning.关键词：urban spatial planning;public participation;site selection of construction project;scenario simulation;multi-agentsystems
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发布时间：2021-06-10 - 摘要：The classif ication of C3 and C4 plant functional types has become an important issue in global change research,but the mechanism of using remote sensing data remains unclear.In this paper,a diurnal variation experiment was designed for soybean（C3 plant functional type） and maize（C4 plant functional type） to acquire canopy spectra under different illumination and temperature conditions,and chlorophyll fluorescence（ChlF） signals and photochemical reflectance index（PRI） were extracted from the canopy spectra.The results showed that:（1） the amplitudes of the diurnal variation in ChlF between soybean and maize were signif icantly different,as the relative ChlF of soybean increased rapidly under heat and high irradiance stresses in the afternoon,but the increasing trend was not found in maize;（2） there was also an apparent increase in the ratio f688/f760of ChlF intensities of soybean in the afternoon,but this did not appear in maize;（3） the midday photosynthetic depression occurred in C3 crops owing to the stressed light and temperature,with a rapid increase in PRI.However,there was no apparent noon depression in C4 crops.Based on the different characteristics between the responses of C3 and C4 crops to high irradiance and temperature stressws,we proposed a potential method to discriminate C3 and C4 plants by multitemporal and hyper spectral remote sensing data.关键词：C3 and C4 plant functional types;hyper spectral;chlorophyll fluorescence（ChlF）;photochemical reflectance index（PRI）
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发布时间：2021-06-10 - 摘要：Atmospheric correction is inevitable in estimating land surface temperature and land surface emissivity using hyperspectral thermal infrared data.The Autonomous Atmospheric Compensation（AAC） and In-scene Atmospheric Compensation（ISAC） are the two main methods for atmospheric correction of hyper-spectral thermal data.Those two methods were applied to the simulated datasets.Results show that the high accuracy of the AAC method,except for the tropic atmosphere,and the root mean stand error（RMSE） of the transmittance and the up-welling radiance for the AAC method is less than 0.002 and 0.004 W.m-2.sr-1.cm,respectively.On the contrary,the error of the ISAC method is large,and the error of the transmittance varies from 0.05 to 0.3 and the error of the up-welling radiance changes from 0.003 W.m.sr.cm to 0.035 W.m.sr.cm.The error increases as the increase of total precipitable water of the atmosphere.Analysis on the impact of heterogeneity of atmosphere on accuracy of atmospheric correction shows that the accuracy of AAC approach is influenced significantly by the heterogeneity of atmosphere.It is necessary to develop atmospheric correction methods for hyper-spectral thermal infrared data of low spatial resolution to overcome the drawback of requiring homogeneous atmosphere by existing atmospheric correction approaches.关键词：hyper-spectral thermal infrared;land surface temperature;land surface emissivity;atmospheric correction
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发布时间：2021-06-10 - 摘要：The iterative technique for multi-source remote sensing data classification is presented in accordance with the advantages of multi-source data in feature extraction.In the method,the Advanced Synthetic Aperture Radar（ASAR） backscatter coefficient is normalized by the incident angle at first.Then,a classifier based on the Bayesian theory and Markov random fields（MRF） is developed,and the Vertical-Vertical,Vertical-Horizontal（VV,VH） polarizations of ASAR and all the seven TM bands are used as inputs of the classifier to get the class labels of each pixel of the images.Finally,the method is validate,the necessities of normalization and integration of TM and ASAR are discussed.The results show that the precision of classification in this paper is 89.4%,which is increased by 4.1% and 11.5% compared with the methods of without normalization and using single TM data.These analyses illustrate that synthesis of multi-souce remote sensing data is an efficient classification method.关键词：multi-source remote sensing;normalization;Bayesian theory;Markov random fields（MRF）
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发布时间：2021-06-10 - 摘要：We proposed a new atmospheric correction approach for HJ-1 CCD datasets,in which the aerosol optical depth（AOD）is acquired based on the relationships between surface reflectance of the blue band and red band over dense dark vegetation（DDV）regions.The atmospheric correction look-up tables（LUTs） were introduced to provide atmospheric correction coefficients under different aerosol loadings and sun-view geometry.The comparison of the results with intraday MODIS（Moderate Resolution Imaging Spectroradiometer） surface reflectance out-puts（MOD09） indicated the proposed atmospheric correction method has preferable accuracy.We did uncertainty analyses from the aspects of AOD retrieval accuracy,radiometric calibration accuracy,altitude impact and atmospheric water vapor con-tent impact.关键词：HJ-1 CCD;atmospheric correction;look-up tables（LUTs）;surface reflectance;MODIS;aerosol optical depth（AOD）
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发布时间：2021-06-10 - 摘要：Remotely sensed data is generally influenced by temporal factors such as Sun-target-satellite geometry and atmospheric conditions,which are major concerns in quantitative monitoring of long-term changes of the Earth’s surface.The inconsistencies are usually eliminated with radiometric normalization or cross-sensor calibration.In most cases,these strategies use statistical relationships among multi-temporal images,which do not meet the rigorous requirements of quantitative remote sensing.While MODIS Level-1B（L1B） products have wide applications,a mathematical relationship was derived among the pixel values of pseudo-invariant features（PIFs） of the multi-temporal images.The quantitative relationship was validated using visible and reflective infrared bands of MODIS L1B products.The results showed that the quantitative relationship consists of additive and multiplicative parts relying on sun-target-satellite geometry,atmospheric conditions and sensor parameters.The derived relationship had a good agreement with the multi-temporal relationship of PIF pixels obtained from individual images.It offers a quantitative basis for statistically based radiometric normalization or cross-sensor calibration.关键词：MODIS;multi-temporal relationship;pseudo-invariant features;quantitative remote sensing;radiometric normalization
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发布时间：2021-06-10 - 摘要：Topography affects the distribution of land surface microwave radiation and soil moisture.Therefore,it is one ofsignificant factors for passive microwave remote sensing.Using the spaceborne radiometer AMSR-E at C-band,a simplified microwave radiative transfer model for mountain areas was developed.Its implement for the relief effect estimations over QinghaiTibet Plateau shows due to topography brightness temperatures at vertical polarization are attenuated about 16 K,conversely,horizontal brightness temperatures are enhanced 18 K,and soil moisture is overestimated and even exceeds the maximum allowed retrieval error（4%）.Finally,the potential approach of the topographic correction is provided by the computation of the surface effective emissivity.关键词：passive microwave remote sensing;mountain areas;soil moisture retrieval;relief effects;Qinghai-Tibet Plateau
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发布时间：2021-06-10 - 摘要：Moderate-resolution Imaging Spectroradiometer（MODIS） data have been widely used in land cover classification with its advantages in multi-spectral and high-temporal features.The classification may suffer from uncertainty relevant to its moderate spatial resolution,yet the uncertainty remains unclear.To explore the issue,this paper used high spatial resolution data acquired from theAdvanced Space borne Thermal Emission and Reflection Radiometer（ASTER）.SinceASTER and MODIS are onboard the same satellite platform,which allows simultaneous multi-resolution observation at coincident nadirs.The Poyang Lake area was taken as the study area for its diverse land covers in low-water period.The high-resolution ASTER data were upscaled to the same coarse resolution as MODIS,with a scaling function developed from a triangular spread function.Different classification methods were applied respectively for land cover classification using either MODIS or upscaled ASTER data.The uncertainties in classified results were subsequently analyzed based on error matrix and a linear model.The evaluation revealed that the uncertainties contributed from scale difference and that from differences in spectral resolution and imaging mode were（6.6—11.2）:2.The scale-induced uncertainty also showed to be land-cover dependent.It was small for water body,but could be as large as 63% for forestland.The signif icance of scale effect is valuable for land cover classification,change detection analysis,scale effect evaluation,and uncertainty analysis in landscape ecology.关键词：MODIS;Poyang Lake;land cover classification;spatial scale;uncertainty
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发布时间：2021-06-10 - 摘要：<正>以"自然与文化遗产空间观测新时代"为主题的第四届国际遥感考古会议将于2012年10月24日-26日在北京召开。本次会议由联合国教科文组织（UNESCO ）、中国科学院和国家文物局联合主办,联合国教科文组织国际自然与文化遗产空间技术中心（HIST）与中国科学院对地观测与数字地球科学中心共同承办。会议将重
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