最新刊期
卷 19 ， 期 1 ， 2015
- 摘要：Atmospheric carbon dioxide（ CO2） is a primary greenhouse gas,whose concentration and geographic distribution are the key points in global change research. Since 1998,space-based observation has been an important technique for the remote sensing of CO2 concentration. We present an overview of the advances in space-based remote sensing of CO2,including the development of remote sensors and inverse algorithms,as well as the calibration of retrieved results. We analyze the uncertainties in inverse methods from observations of both thermal infrared and shortwave infrared techniques. The potential development of CO2 retrieval is discussed at the end of this paper.关键词：CO2;satellite remote sensing;thermal infrared hyperspectral;shortwave infrared hyperspectral;optimal estimation method
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发布时间：2021-06-10 - 摘要：Hygroscopic growth characteristics of particulate matter are one of the key issues that need to be addressed in satellite remote sensing of ground-level particulate matter. To solve this problem,the characteristics of the extinction properties of particulate matter as they change with air relative humidity need to be understood,and an accurate hygroscopic growth model of particulate matter should be established. A hygroscopic growth model suitable for Beijing is constructed by using the measurements from instruments deployed on the ground.First,the average particulate matter of mass extinction efficiency is calculated based on continuous measurements from the ground sites in Beijing over a period of two years. Result shows that average mass extinction efficiency of particulate matter increases with relative humidity continuously. The increase in the average particulate matter mass extinction efficiency is moderate when relative humidity increased from 20% to 85%,whereas it increased rapidly when relative humidity increased to 85%. Second,the hygroscopic growth factors of particulate matter in different levels are calculated based on the average particulate matter mass extinction efficiency; the change trend with time of the hygroscopic growth factors are consistent,with the maximum value observed in June and the minimum value in January. From January to June,the hygroscopic growth factors increased before gradually decreasing from July to December. Their values in December were slightly higher than those in January. Third,three hygroscopic growth models commonly used in Beijing are fitted based on these hygroscopic growth factors. The three models showed good applicability in Beijing.The third model is slightly better than the second model,and the second model is slightly better than the first. These models can be used in satellite remote sensing of ground-level particulate matter.关键词：aerosol;particulate matter;hygroscopic growth model;awerage mass exinction efficency;hygroscopic growth factor
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发布时间：2021-06-10 - 摘要：In the satellite aerosol retrieval scheme,determining the aerosol model directly affects the accuracy of most of the current aerosol optical depth retrieval algorithms. The dynamic aerosol models determined based on the extensive analysis of aerosol optical properties obtained from AErosol RObotic NETwork（ AERONET） sun-photometer observations are introduced to a new aerosol retrieval algorithm to derive the Aerosol Optical Depth（ AOD） using the PARASOL（ Polarization and Anisotropy of Reflectance for Atmospheric Science coupled with Observations from LiD AR） multi-angular and polarimetric measurements. The rationale of our algorithm is to initially establish LUTs（ Look Up Tables） using dynamic aerosol models in ten different AOD conditions: Model AOD∈[0. 0,0. 1],[0. 1,0. 2],[0. 2,0. 3],[0. 3,0. 5],[0. 5,0. 8],[0. 8,1. 0],[1. 0,1. 2],[1. 2,1. 5],[1. 5,1. 8],and [1. 8,2. 0]. The retrieved AOD and selected aerosol model must meet two requirements successively:（ 1） combination of the retrieved AOD and Model that leads to the best mimic of the TOA（ Top Of Atmosphere） polarized reflectance measurements;（ 2） the retrieved AOD in the Model AOD intervals,otherwise the retrieved AOD and the Model will be rejected. The accuracy of this algorithm is guaranteed by the iterative constraint between the aerosol model selection and the retrieved AOD,as well as the simultaneous use of two bands（ 670 nm and 865 nm）,multi-angular,and polarimetric measurements to constrain the retrievals. By applying this algorithm to a whole year of the 2012 PARASOL measurements in the North China Plain,typical cases,such as clean and polluted days,were analyzed to test this algorithm. The validation of the retrieved PARASOL AOD with those of AERONET in Beijing showed reasonable agreement（ matched pairs N = 101,square correlation coefficient R2= 0. 71,root mean square error RMSE = 0. 15,and 91% of all the samples lie within 0. 2 AOD thresholds）. To validate the regional suitability of this algorithm,four temporary ground-based CE318 sites（ Tianjin,Tiangang,Tanggu,and Qichang） in North China as a part of our Jing-Jin-Tang aerosol experiment in March 2012 were also adopted to validate. Good agreements are also shown in these four sites.In dynamic aerosol model retrieval algorithm,the aerosol model is associated with the AOD magnitude by prior knowledge,constraining the retrieved AOD and selected aerosol model simultaneously.关键词：AERONET;Dynamic aerosol model;multi-angular;polarmetric;aerosol inversion algorithm
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发布时间：2021-06-10 - 摘要：The applicability of column-averaged CO2dry-air mixing ratio（ XCO2） data derived from Greenhouse Gases Observing Satellite（ GOSAT） observations should be comprehensibly analyzed. Such assessment is important to reveal spatiotemporal variations in atmospheric CO2 concentration at the global and regional scales,as the XCO2 retrieval bias of GOSAT has decreased to 1—2 ppm. We analyzed and evaluated the spatial and temporal variations in XCO2 at a global and regional scale using GOSAT data from 2010 to 2012. Furthermore,we preliminarily analyzed the response of GOSAT data to anthropogenic emissions. Two data sets of XCO2 from the OCO team of NASA（ ACOS） and the Japan National Institute of Environmental Studies（ NIES） GOSAT team,respectively,were used with different retrieval algorithms for GOSAT observations. ACOS-XCO2 is generally approximately 2 ppm higher than NIES-XCO2,whereas similar variability at space and time is shown in the two data sets. The annual increment of global averaged atmospheric XCO2 concentration is 1. 8 ppm from 2010 to 2011 and 2. 0 ppm from 2011 to 2012; the seasonal variation is4—6 ppm in the Northern Hemisphere and approximately 2 ppm in the Southern Hemisphere; this finding is generally consistent with the statistical results of CO2 variability from ground-based measurements. In addition,GOSAT observations respond weakly to the anthropogenic emissions on the basis of correlation analysis between yearly averaged GOSAT XCO2 and cumulative yearly anthropogenic emissions obtained from the Emissions Database for Global Atmospheric Research data. Our results demonstrate that GOSAT observations can detect the spatial and seasonal variability in CO2 at a global and regional scale. These observations can be applied in monitoring the cumulative effects of anthropogenic emissions at the regional scale,although GOSAT encounters difficulty in detecting the variation magnitude of CO2 induced by the point source emission because of the unrefined spatial resolution of GOSAT footprints.关键词：GOSAT;atmospheric CO2concentration;temporal and spatial variation;anthropogenic emissions
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发布时间：2021-06-10 - 摘要：CO2 is a primary greenhouse gas in the atmosphere and many scientific missions from all over the world are focused on space-based remote sensing of CO2 using shortwave infrared technique. We present an improved method to retrieve CO2 column abundance from space-based observations in a shortwave infrared band. We analyze the sensitivities of CO2 observations to aerosol scattering and atmospheric temperature profiling using the forward model. We also evaluate the reduced accuracy of CO2 retrieval caused by aerosol scattering and 1K random error of temperature profiles. We propose a Modified Damped Newton Method（ MDNM） for CO2 retrieval and present the retrieval samples to evaluate the performance of the proposed algorithm. Sensitivity studies show that the influence of aerosol scattering and temperature on CO2 remote sensing and scattering can cause a misestimate of up to 13. 2 ppm of CO2 concentration. We retrieve the CO2 column abundance from GOSAT L1 B data using MDNM method,and the results are compared with ground-based measurements from Total Carbon Column Observing Network（ TCCON）. The correlation coefficient R-square between the retrieved results and TCCON measurements is 0. 729. Sensitivity studies show that aerosol scattering can cause a significant error in CO2 retrieval. A comparison between satellite retrievals and ground-based measurements shows good agreement. The proposed MDNM method is preliminarily proven to accurate.关键词：CO2;MDNM;Retrieve;GOSAT
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发布时间：2021-06-10 - 摘要：The development of a sub-millimeter（ 0. 1 mm to 1. 0 mm or 300 GHz to 3 THz） limb sounding technique has enhanced our knowledge of O3 processes. Sub-millimeter wave limb sounding is important because the sub-millimeter includes many spectral lines of trace gases,particularly the halogen family. This study aims to investigate the possibility of limb sounding of a high-flying vehicle plume. ARTS forward model is used to simulate the limb sounding of the plume compositions to study their sensitivity. The sub-millimeter wave limb sounding is sensitive to the concentration variations in H2 O,O2,OH,and HCl. When their concentration is increased five times,their limb sounding bright temperature will increase by 80 K,80 K,5 K,and 50 K,respectively. However,sub-millimeter wave limb sounding is not sensitive to concentration variations in CO,CO2,and NO. Based on a simulated trail of a vehicle flying at an altitude of 15 km,the sub-millimeter wave limb sounding radiance temperatures of the plume under different atmospheric backgrounds are calculated and compared; the different radiance temperatures of limb sounding and nadir viewing are also compared. The plume of the flying vehicle can be detected with a sub-millimeter wave limb sensor under any atmospheric background. However,it cannot be detected with the nadir viewing sensor. Therefore,the sub-millimeter wave limb sounding technique has an advantage over nadir viewing in detecting the plume of a high-flying vehicle,and its atmospheric background affects the limb sounding of the plume.关键词：high-flying vehicle;plume flow;sub-millimeter wave;limb sounding
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发布时间：2021-06-10 - 摘要：Forest Above Ground Biomass（ AGB） estimation is important for ecosystem monitoring and carbon cycling studies.Accurately estimating regional and global AGB can reduce the uncertainty of carbon budgets.Over the last six years,regional and global forest AGB have been derived from various remote sensing data,including spaceborne LiD AR data（ height and vertical structure parameters）,optical multispectral data（ Vegetation Index（ VI）,Leaf Area Index（ LAI）,Absorbed Photosynthetic Active Radiation（ APAR）,image texture,Digital Surface Model（ DSM） and optical point cloud）,and microwave data（ backscattering coefficient,coherence,scattering phase center height,and DEM）. In this study,we reviewed the advantages and limitations of three kinds of inversion methods,i. e.,parametric method based on single sensor data,non-parametric method based on multi-sensor data,and a method based on physical mechanism models.First,parametric method mainly obtains multiple regression equations by analyzing the statistical relationship between AGB and various remote sensing variables. The method is simple but strongly dependent on site and time. Second,non-parametric methods were used to solve nonlinear and high-dimensional problems,including decision trees,k-nearest neighbors,artificial neural network,and support vector machine method. Such method is widely used in global and regional AGB estimation,but it lacks a physical mechanism and its accuracy depends on the number of training data sets. Third,the method based on mechanism models includes direct inversion using semi-empirical models and a look-up table method based on forest forward simulation model. Method usage is limited because of the contradiction between the accuracy and complexity of the model.As for remote sensing data used in AGB estimation,the spectral variables extracted from optical data have been widely applied. Radar is unaffected by weather conditions and it is capable of obtaining signal from branches,trunks,and even understories. Backscattering coefficient with SAR image,interferometric coherence with InS AR,vertical structure with Pol-InS AR,and backscattering contribution ratio of ground and vegetation with PCT technology are all closely related to AGB. Advances in LiD AR technology have demonstrated a capability to obtain the height and three-dimensional structure of forests,but its limitations include canopy species recognition and lack of spaceborne data.AGB estimation by combining multi-source remote sensing data has become a development trend because the data obtained from different portions of the electromagnetic spectrum and different observation configurations provide comprehensive information on forests. However,the retrieval accuracy did not meet the demands of ecosystem monitoring and carbon cycling study thus far. The uncertainties were attributed to the complexity of forest structures,mixed pixels and scale effect,as well as errors in allometric equations. The four potential aspects of biomass inversion studies to improve accuracy are presented: forest physical mechanism model study,multi-sensor synergy method,biomass seasonal and time variation study,and future data sources support.关键词：forest above ground biomass;multiple regression;non-parametric method;mechanism model
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发布时间：2021-06-10 - 摘要：The important function of land surface remote sensing products in scientific research and quantitative application lies in their capability to record spatial-temporal earth surface features at a relatively enhanced performance. Validating quantitative remote sensing products involves evaluating their accuracy,stability,and consistency to show the performance of these products. This study investigates the validation method at a global scale according to the features of land surface parameters. The validation method is categorized into five main types: validation based on a single-point ground measurement,validation based on multipoint ground measurement,validation based on high-resolution remote sensing data,cross validation,and indirect validation. The characteristics and applicability of these methods are expected to support developments in validation techniques and widen the application of remote sensing products.In situ data,as the basis of validation data sets,have been shown to influence validation method development. Given the differences in spatial resolution between ground measurement and satellite measurement,validation is adjusted according to land surface features and the parameter scale effect. For parameters that do not show obvious scale effects,a direct point-pixel comparison can be performed. However,most of the land surface parameters show scale effects when the land surface is heterogeneous.Therefore,multiple-point measurements within a pixel are necessary,with the average value of these points used to compare with satellite pixel values. If the land surface is heterogeneous and even the multiple points cannot capture the intra-pixel variation in the parameter features,a multi-scale validation strategy based on high-resolution imagery should be used to obtain unbiased pixel scale values.The satellite value matches well with the in situ value when land surface is homogeneous. However,a scale mismatch is observed between the ground-based measurement and coarse-scale satellite measurement in land surface heterogeneity. Using multiple-point measurement is necessary to capture the variance within a larger region or use a fine-scale map as a bridge between the ground-based value and coarse-scale remote sensing value. The average value of multiple points within a pixel scale can represent the pixel scale"ground truth"when the land surface is not considerably heterogeneous. Otherwise,the aggregate value of high-resolution imagery is closer to the pixel scale"ground truth"relative to multi-point measurement.This study has demonstrated that remote sensing product validation,including in situ sampling,scale effect,and precision assessment,is a significant and necessary step before remote sensing products are applied. The five main validation methods are validation based on a single-point ground measurement,validation based on multi-point ground measurement,validation based high-resolution remote sensing data,cross validation,and indirect validation. These methods could be used according to the heterogeneity of the land surface and the scale effects of parameters. For relatively homogeneous land surfaces,ground-based measurements are representative enough for the sample plot,and the scale effects can be ignored. For heterogeneous land surfaces,multipoint measurement observation,or multi-scale validation strategy based on high-resolution imagery are recommended to represent the pixel scale as"relative truth".关键词：land surface parameters;validation;quantitative remote sensing products;heterogeneity;scale effect
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发布时间：2021-06-10 - 摘要：We proposed a wide spectrum and rapid calculation model FALTRAN（ Fast Atmospheric Limb TRANsmission）,to solve the problems of current radiative transfer model in limb remote sensing. In FALTRAN:（ 1） Band model algorithm was employed and the molecular spectroscopy database was based on HITRAN2008.（ 2） Limb radiative transfer equation consists of scattering and thermal radiation was established,and according to the limb geometry characteristic,a Hemisphere Radiation Adding（ HRA） approach based on finite difference method was proposed to solve it. We investigated the atmospheric limb radiations under typical atmospheric modes in several commonly used remote sensing bands. Moreover,radiation contribution by two hemispheres was quantitative analyzed as well. Validation results show that the relative differences between FALTRAN and Combining Differential-Integral（ CDI） model are within 2%,and calculation results by FALTRAN have good agreement with Michelson Interferometer for Passive Atmospheric Sounding（ MIPAS） measurements. FALTRAN is proven to be reliable in the limb radiative transfer calculation.
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发布时间：2021-06-10 - 摘要：为解决目前临边遥感大气辐射传输模型存在计算光谱窄和计算速度慢等问题,基于HITRAN2008数据库、带模式算法和临边辐射传输方程建立了0.2—20μm波段大气临边辐射传输的宽光谱快速计算模型FALTRAN。建立了含有散射辐射和热辐射的临边辐射传输方程,并依据临边几何特征提出了一种基于有限差分的半球辐射累加HRA解算方法。利用FALTRAN计算分析了几个常用的遥感波段内典型大气条件和切向高度时大气的临边辐射特性,并定量分析了左、右半球辐射对总辐射的贡献情况。模型校验结果表明,FALTRAN与CDI模型的计算结果相对差异在2%以内,并与MIPAS的测量结果符合很好,验证了FALTRAN在临边遥感中大气传输计算的可靠性。关键词：临边遥感;带模式算法;临边辐射传输方程;半球辐射累加;辐射贡献
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发布时间：2021-06-10 - 摘要：Existing research on optimal path algorithms are summarized,and the principles and actualities of cellular automaton（ CA） used in optimal path algorithms are analyzed. CA optimal path algorithms are optimized using two approaches. One approach is to use heuristic function in the CA model,the other is to consider the variform paths in optimal path analysis algorithms as selfadaptation models. The author conducted experiments to prove the high efficiency and self-adaptive property of the optimized algorithms and concluded that the efficiency of algorithm requires improvement.
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发布时间：2021-06-10 - 摘要：Spatial scale transformation is one of the basic and important scientific problems in quantitative remote sensing field.Spatial up-scaling has particularly drawn much attention,as it can effectively help solve difficult problems,e. g.,validation of quantitative remote sensing products. However,some issues remain concerning spatial up-scaling research.（ 1） The transformation formula established by statistical methods has no explicit physical meaning and its available range is limited.（ 2） The lack of reasonable retrieved physical models hampers the development of up-scaling based on these models. As an important retrieval method,the up-scaling of NDVI also faces these two issues. To address these problems using statistical and physical methods,continuous spatial scaling model（ CSSM） of NDVI on the basis of fractal theory was established. The CSSM exhibits a wide available scale range and partial physical meanings. However,the means of determining the most reasonable Level（ scale hierarchies） for establishing the model remains an important problem,which is studied in this research.In this research,a precise and rigorous method of determining the most reasonable Level was developed based on a five-index estimation system. The system integrates statistical estimation indices（ r,p,rlo,and rup） and an availability-in-validation index [largest error in validation,Maxofabs（ Error） ]. It was computed as follows. First,the NDVI CSSM of an image was established on each of the different Levels. Second,the indices（ r,p,rlo,and rup） on each Level were compared and analyzed. Third,the most reasonable Level could be computed based on the defined Maxofabs（ Error） to establish the widest scale CSSM.Shatian Byland（ Beihai City,Guangxi Zhuang Autonomous Region） was selected as the experimental area because of its variety of ground objects and high spatial heterogeneity. Taking the values（ r≥0. 8,p < 0. 05,rlo≥r≤rup and Maxofabs（ Error） ≤0. 05） as estimation system,the most reasonable Level（ Level = 267） was computed. On that Level,the model was log2 NDVI =1- 0. 0347log2 1/scale-1.1296 and its scale range was from 30 m to 8010 m. Within the range,validating the NDVI image on any scaleup-scale（ corresponding to the integral multiple of the 30 m resolution of ETM + image） could be implemented by the model.Furthermore,the sensitivity of the Level to values of the estimation system was analyzed. The Level would dynamically change when the threshold values of the five-index estimation system were different and the application purpose changed,which meant that the method in the research was steady and rigorous.In this research,the method of determining the most reasonable Level for establishing the CSSM of NDVI was developed based on a five-index [r,p,rlo,rup,and Maxofabs（ Error） ] estimation system. This model quantitatively described the transformation relationships of NDVI on continuous scales. On the basis of this result,NDVI validation of different low-resolution images could be implemented rapidly and effectively. This work results in a more systematic research on modeling the CSSM of NDVI.关键词：NDVI;spatial up-scaling;continuous spatial scaling model;Fractal;five-index estimation system
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发布时间：2021-06-10 - 摘要：Remote sensing images are usually affected by light,angle,and other factors,thereby resulting in nonlinear mixed characteristics of a surface object spectrum. Thus,linear methods,such as Independent Component Analysis（ ICA）,have limitations. Kernel Independent Component Analysis（ KICA） achieves nonlinear transformation through the kernel function,and the data are mapped into a high-dimensional feature space,where the data are analyzed by ICA. As a result,detection errors from nonlinear mixing of the surface object spectrum are considerably reduced. Remote sensing images are usually large and complex. If they are analyzed directly by KICA,the computation will be large. Therefore,we propose a change detection method of remote sensing images of land cover based on multi-scale geometric analysis and KICA.First,multi-scale decomposition of remote sensing images is conducted by using multi-scale geometric analysis methods,such as contourlet transform,complex contourlet transform,and Nonsubsampled Contourlet Transform（ NSCT）. The decomposed components are transformed into partitioned vectors,which consist of low-frequency and high-frequency components. The vectors are then analyzed by KICA and mapped into a high-dimensional feature space by the kernel function,so that the mixing pattern of vectors is linear. In the space,mutually independent components are separated by ICA. The change component of land cover is selected and transformed into an image component. The change image is transformed into a binary image by using automatic thresholding method,and the final change detection result is obtained.Experimental results of the proposed method and recently proposed methods based on ICA,KICA,as well as wavelet and ICA are presented. Analysis and quantitative comparisons are conducted. Based on subjective visual effects,the isolated points and discrete regions in the results obtained by the proposed method decreased compared with those obtained by the methods based on ICA,KICA,as well as wavelet transform and ICA. The land edge is fully retained in the case of less isolated points,thereby reflecting more accurately actual change information of the surface. According to objective quantitative indicators,such as erroneous error,omission error,overall accuracy,and running time,the proposed method is more accurate than the methods based on ICA,KICA,as well as wavelet transform and ICA. The overall accuracy of the method based on NSCT and KICA is the highest,whereas the method based on contourlet transform and KICA shows a relatively high computational efficiency.Our method can separate change information of remote sensing images better. The method based on NSCT and KICA exhibits the smallest misjudgment and misdetection errors and preserves edge details better. The method based on contourlet and KICA shows relatively high detection efficiency.关键词：change detection;Kernel Independent Component Analysis（KICA）;multi-scale geometric analysis;contourlet transform;Nonsubsampled Contourlet Transform（NSCT）
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发布时间：2021-06-10 - 摘要：Validation is one of the most important processes used to evaluate whether remotely sensed products can accurately reflect land surface configuration. Leaf Area Index（ LAI） is a key parameter that represents vegetation canopy structures and growth conditions. Accurate evaluation of LAI products is the basis for applying them to land surface models. In this study,validation methods of coarse resolution MODIS and GLASS LAI products for heterogeneous pixels are established on the basis of the scaling effect and the scaling transformation. Considering spatial heterogeneity and growth difference,we transformed LAI from field measurements into a 1 km resolution scale with the aid of middle resolution images. We used average LAI and apparent LAI separately to validate the algorithms and products of MODIS and GLASS LAI. Two study areas,Hebi City and the Yingke Oasis,were selected for validation. Both MODIS and GLASS LAI products underestimate the true LAI in crop area. However,this result cannot be completely attributed to their algorithms. Instead,the primary reason is the heterogeneity and nonuniformity of the coarse pixels.Underestimation is evident in the Yingke Oasis,where heterogeneity is significant. Given that GLASS LAI product is the fusion of multiple LAI products,the mean value of this product is closer to the real situation,but the dynamic range is narrower than that of MODIS LAI product.
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发布时间：2021-06-10 - 摘要：真实性检验是评价遥感反演产品质量和验证遥感应用产品是否准确、真实地反映实际情况的重要途径。叶面积指数（LAI）是表征陆地植被结构和长势的关键参数,全面准确评价和验证LAI产品是产品用于陆面过程模型的前提。本文以MODIS LAI与GLASS LAI产品为研究对象,在尺度效应和尺度转换的基础上,建立了针对非均匀像元的低分辨率LAI产品真实性检验方法。在考虑空间异质性和植被长势差异的情况下,借助中分辨率的遥感影像,分别利用1 km像元平均叶面积指数和反演表观叶面积指数实现了对LAI算法和产品的真实性检验。为了比较作物长势差异和地表非均匀度对产品的影响,本文选择有代表性的河南鹤壁和甘肃张掖两个地区进行两种LAI产品真实性检验研究。研究结果表明,GLASS LAI和MODIS LAI产品均存在明显的低估现象。这并不是产品算法的问题,而是由于地表异质性和非均匀度的影响。在异质性更显著的张掖盈科灌区,低估现象更明显。GLASS LAI产品是多种LAI产品的融合,它的平均LAI比MODIS更接近真实情况,但是LAI的动态范围比MODIS窄。关键词：真实性检验;叶面积指数;尺度效应;尺度转换
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发布时间：2021-06-10 - 摘要：We proposed a method to estimate single scattering albedo of winter wheat over the North China Plain with AMSR-E passive microwave imagery. The relationships of single scattering albedo and optical depth between 6. 925 GHz and 10. 65 GHz were derived from simulations. To retrieve the single scattering albedo,the relationships were combined with the physical expressions of microwave vegetation indices derived from the first-order parameterized emission model. Comparisons with normalized difference vegetation index（ NDVI） obtained from daily MODIS reflectance product showed that the variations in winter wheat single scattering albedo were similar to those of winter wheat NDVI. However,several differences were observed. NDVI showed saturation from the heading stage to the milky stage of winter wheat,whereas single scattering albedo remained sensitive to the growth of winter wheat. Single scattering albedo offers certain advantages in reflecting the growth status of winter wheat.
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发布时间：2021-06-10 - 摘要：首先,基于冬小麦不同生育期的地面实测参数,构建了组成冬小麦冠层的、包括不同尺寸和含水量的介电散射体模拟数据库,并在此基础上建立冬小麦单散射反照率和光学厚度分别在C（6.925 GHz）和X（10.65 GHz）波段之间的依赖关系。然后,根据一阶参数化模型推导得到的微波植被指数MVIs（Microwave Vegetation Indices）的物理表达式,结合AMSR-E被动微波亮温数据,反演了华北平原地区冬小麦不同生育期的单散射反照率。与MODIS日归一化差异植被指数NDVI的对比结果显示:冬小麦单散射反照率与NDVI随时间的变化趋势大致相同,但在冬小麦的抽穗期到乳熟期,NDVI呈现饱和趋势,而单散射反照率对小麦的生长变化仍旧比较敏感,在指示冬小麦生长方面具有一定优势。关键词：单散射反照率;冬小麦;AMSR-E;参数化模型;微波植被指数;被动微波
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发布时间：2021-06-10 - 摘要：Dry-bulb temperature,which can represent the regional characteristics of thermal conditions,is one of the conventional meteorological elements measured over surfaces. Such measurement serves an important function in studying plant physiology,hydrology,the atmosphere,and the environment. Dry-bulb temperatures are usually calculated through linear fitting to original remote sensing data or approximate temperatures retrieved from remote sensing data. These methods are suitable for homogeneous areas with a stable atmospheric stratification and circulation pattern. However,a linear relation does not exist between surface temperature retrieved from remote sensing data and the actual dry temperature because of the limitations of algorithms and the complexity of the underlying surface. Dry-bulb temperatures cannot be calculated accurately with the use of traditional retrieval algorithms. Therefore,a support vector machine（ SVM） model was proposed in this study to calculate dry-bulb temperatures.Nanning City was selected as the research area. First,the temperature retrieved from remote sensing data was compared with in situ data. The relations among brightness temperature,temperature retrieved from remote sensing data,and actual dry-bulb temperature were confirmed. Calculating dry-bulb temperature by remote sensing data was a reasonable approach. Second,the actual dry-bulb temperature in some stations and the corresponding temperatures retrieved from remote sensing data（ at the same time and geographical location） were taken as modeling samples. The SVM prediction model with a strong learning capability and nonlinear processing capability was developed to retrieve dry-bulb temperatures. Finally,the dry-bulb temperature was calculated by using remote sensing brightness temperature and the temperature retrieved from remote sensing data as the input parameters of the SVM model.For the data obtained on May 12 and November 20,2008,the absolute errors of the traditional method（ using Tslinear translation with surface temperature retrieved from remote sensing data） to calculate the dry-bulb temperature are 2. 050112 ℃ and1. 3437564 ℃; the absolute errors of SVM models of brightness temperature are 0. 91915 ℃ and 0. 40294 ℃; and the absolute errors of SVM models of surface temperature are 0. 73802 ℃ and 0. 55002 ℃. The precision of the SVM models is higher than that of traditional methods.The conclusions are as below:（ 1） Actual dry-bulb temperatures,brightness temperatures,and surface temperatures retrieved by remote sensing are well correlated. Using remote sensing data to predict dry-bulb temperatures is a feasible approach. As determinative factors of regional change for dry-bulb temperature are complex,relations among dry-bulb temperatures,brightness temperatures,and surface temperatures are not linear. Using traditional linear methods may result in large biases. The SVM model with nonlinear processing capacity is more suitable than traditional methods for calculating dry-bulb temperature.（ 2） The absolute errors of the SVM model are more reasonable and smaller than those of traditional methods.（ 3） The results of the SVM model,which used brightness temperature and retrieval surface temperature as input parameters,are comparable. The retrieval process for surface temperature is complex; therefore,brightness temperature can be taken as input for SVM directly instead of retrieving surface temperature.（ 4） Given that November is a non-flood season in Guangxi,nonadiabatic heating of heat flux equation is less affected by convection and turbulence. The main factor for dry-bulb temperature is surface thermal radiation; the absolute error for the November data is significantly smaller than that of May even when using the same SVM models.关键词：brightness temperature;dry-bulb temperature;support vector machines;Nanning
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发布时间：2021-06-10 - 摘要：<正>高分辨率对地观测系统利用天基、临近空间和航空平台的多种观测手段,实现对陆地、海洋、大气等各类对地观测信息的获取,其数据广泛应用于农业、林业、水利、国土、气象以及国家安全等众多领域。高分辨率对地观测系统重大专项（以下简称高分专项）是《国家中长期科学和技术发展规划纲要（2006-2020年）》中部署的16个重大专项之一,用于发展我国高分对地观测技术,构建我国高分对地观测体系,掌握高分对地观测信息自主权,促进形成空间信息产业链。高分专项重点发展基于卫星、飞机和平流层飞艇的高分辨率先进观测系统;形成时空协调、
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发布时间：2021-06-10 - 摘要：<正>中巴地球资源系列卫星（CBERS）由中国航天科技集团公司和巴西空间研究院联合研制,是中巴两国在航天科技领域合作的重要体现,被赞誉为"南南合作的典范",主要应用于国土、林业、水利、农情、环境保护等领域的监测,规划和管理。CBERS-04卫星配备有分辨率为5 m的全色、10 m的多光谱相机（PAN）,20 m的多光谱相机（MUX）,40 m/80 m的红外相机（IRS）以及分辨率为67 m的宽视场相机（WFI）,满足了获取持续稳定的中分辨率普查数据的迫切需求。
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发布时间：2021-06-10
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