Atmospheric correction of ocean color imagery over turbid coastal waters using active and passive remote sensing

This paper demonstrates an atmospheric correction method to process MODIS/Aqua (Moderate-resolution Imaging Spectroradiometer) ocean color imagery over turbid coastal waters with the aid of concurrent CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) aerosol data, assuming that there exists "nonturbid" water in the study area where MODIS aerosol optical properties can be retrieved accurately. Aerosol properties from CALIOP measurements were obtained and related to those from MODIS. This relationship, combined with CALIOP aerosol data, was extended to turbid water to derive MODIS aerosol properties, where atmospheric correction using MODIS data alone often fails. By combining MODIS and CALIOP data, aerosol signals were separated from the total signals at the satellite level, and water-leaving radiances in turbid waters were subsequently derived. This method was tested on several MODIS/Aqua ocean color images over South China turbid waters. Comparison with field data shows that this method was effective in reducing the errors in the retrieved water-leaving radiance values to some extent. In the Zhujiang (Pearl) River Estuary, this method did not overestimate the aerosol effects as severely, and provided far fewer negative water-leaving radiance values than the NASA (National Aeronautics and Space Administration) default methods that used MODIS data alone.     

地表温度的多源遥感数据反演算法对比分析

 多源遥感数据的综合应用是提高地表温度反演精度的有效途径.MODIS数据和Landsat TM数据在我国同一地区获取的时间相差不大,可以获取近似同步的MODIS数据和TM数据.本文将基于MODIS数据反演的大气参数应用于TM影像的地表温度反演,分别对单窗口算法和普适性单通道算法进行了实验研究,应用气象站实测的地表温度数据对反演结果进行了检验,并对比分析了不同土地覆盖条件下两种算法的精度差异.结果表明:两种算法反演精度均较高,单窗口算法反演精度为0.76K,普适性单通道算法反演精度为1.23K;在不同的土地覆盖条件下,两种算法表现出明显的差异性,水体区反演结果差异最小,均值差异仅为0.02K,植被区差异最大,均值差异为0.62K.     

复杂地形山区Landsat TM影像C校正策略与实验

采用分坡度、分NDVI（归一化差异植被指数）和分地类的C校正策略,对复杂地形山区Landsat TM影像进行地形校正,并运用视觉检验、回归分析和遥感分类精度将3种C校正策略的结果与传统的整体C校正进行对比,以探寻适合复杂地形山区的C校正策略。在此基础上,进一步探讨了地形校正对影像重采样尺度的响应。研究结果表明：与传统的整体C校正相比,采用分坡度、分NDVI和分地类的C校正策略能更好地消除原影像的凹凸感,减弱地形效应,且背阳面影像的过校正现象减少;各种C校正策略和整体C校正对Landsat TM影像不同波段的校正效果不一,其中,分地类的C校正策略对波段1、2、3和波段7的校正效果最好,分坡度的C校正策略对波段5的校正效果更佳,而整体C校正则对波段4的校正效果最好;虽然所有C校正均能有效地消除影像中的地形效应,但并未能提高影像分类精度;从不同重采样尺度C校正结果对比看,随着采样尺度增加,地形效应逐渐减弱,但并未完全消除,因此,中、低空间分辨率遥感影像的地形效应也不容忽视。     

TM热波段图像的地表温度反演算法与实验分析

目前利用LandsatTM热波段数据反演地表温度有3种算法:辐射传导方程法、单窗算法和单通道算法。辐射传导方程法由于计算过程复杂且需要实时大气剖面数据,因而实际应用较为困难。单窗算法和单通道算法对Landsat热波段反演地表温度能获得较高精度。单窗算法所需的大气参数包括近地表气温和大气水分含量,单通道算法所需的大气参数仅为大气水分含量。地表辐射率为这两种算法共有的关键参数。本文以福建省福州市为研究区,使用1989年6月15日LandsatTM数据,利用单窗算法和单通道算法对研究区进行地表温度反演,并将这两种算法的反演结果与研究区反演的亮度温度进行了比较,结果表明:(1)两种算法反演的结果总体趋势比较接近,但单窗算法的结果相对于单通道算法较低,二者相差约2.45℃;(2)两种算法的结果与亮度温度相比,单窗算法要高出约2.84℃,而单通道算法则要高出约5.28℃。     

基于Landsat-8 TIRS的大气参数快速估算方法

Landsat-8卫星设计有2个热红外波段,但由于第11波段存在定标问题,无法用于定量研究,所以基于Landsat-8的地表温度反演算法目前仍以单通道为主。单通道算法反演地表温度需先已知地表比辐射率并完成大气校正的工作。在大气校正方面,现有的算法主要以传统方法为主,即通过大气辐射传输模型或经验-半经验公式的方式获取大气参数。但是,传统的经验-半经验的方法并不建立在物理机制上,其自身存在一定局限性;而大气辐射传输模型的方法虽然精度更高,但执行效率较低,不适用于业务化的产品生产。本文针对现有大气估算方法的不足,提出了一种基于Landsat-8单通道地表温度反演的大气参数快速估算方法。在水汽范围0~6 g/cm²内,大气参数快速估算方法的精度与MODTRAN精度相当,大气透过率RMSE为0.003;大气上行辐亮度RMSE为0.0004;大气下行辐亮度RMSE为0.0004。相较于传统的大气参数估算方法,本文提出的大气参数快速估算方法,不仅可以脱离大气辐射传输模型使用,而且具有与其相当的估算精度,执行效率更高,适用性更广。     

洪涝灾情快速反应的星载SAR与TM数据的融合处理

本文以1998年鄱阳湖地区发生洪涝灾害为研究实例,应用灾中的Radarsat-SAR和灾前的TM数据,以不规则三角网(TIN)方法实现了高精度几何配准。然后,通过波段相关性和信息熵值分析,选取最佳波段。最后,对不同融合模型得出的图像进行对比,得出结论:以灾中的SAR和灾前TM的一个近红外(TM5或TM7)以及一个可见光波段(TM3最佳),分别赋RGB色合成的图像效果很好,既能识别区分洪涝淹没的绝产区、土壤滞水减产区和未受灾区,并且操作简便,能满足洪涝灾情快速反应要求。     

AN ASSESSMENT OF LAND USE CHANGES IN FUQING COUNTY OF CHINA USING REMOTE SENSING TECHNOLOGY

Fuqing County of southeast Chian has witnessed significant land use changes during the last decade.Re-mote sensing technology using multitemporal Landsat TM images was used to characterize land use types and to monitor land use changes in the county.Two TM scenes from 1991and 1996 were used to cover the county and a five-year time period.Digital image processing was carried out for the remotely sensed data to produce classified images.The images were further processed using GIS software to generate GIS databases so that the data could be further spatially analyzed taking the advantages of the software.Land use change areas were determined by using the change detection technique.The comparison of the two classified TM images using the above technologies reveals that during the five study years,a large area of arable lands in the county has been lost and deforestation has taken place largely because of the dramatic in-crease in built-up land and orchard.The conclusive statistical information is useful to understand the processes,causes and impacts of the land use changes in the county.The major driving force to the land use changes in the county ap-peared to be the rapid economic development.The decision makers of the county have to pay more attention to the land use changes for the county‘s sustainable development.     

Estimation of vegetative surface albedo in the Kushiro Mire with Landsat TM data

A method has been developed for estimating the filtered narrow band surface albedo with Landsat/TM data. In this method, the surface albedo from filtered range of Landsat/TM is converted to the surface albedo with unfiltered spectral range. The atmospheric effects on each channel are systematically different, because of the different spectral behavior of atmospheric parameters. As a result, in this study, atmospheric correction has been done respectively in different parameters for visible and infrared channels. The surface albedos of the Kushiro Mire gotten with this method were compared with the observed data there. The results show that the satellite inferred albedos have a good agreement to the diurnal mean of ground observed albedos with 3% systematic error. There is a seasonal variation of albedo in high and low mires, the albedo decreased gradually from April to July and reached its minimum in July, further it rose gradually from August to October. It is also clear that there is a characteristic pattern of surface distribution according to the vegetation types of this area. The average surface albedos of each type of community are 0.164 for Sphagnum, 0.175 for Carex, 0.179 for Pragmites and 0.166 for Alnus. In the other words, the albedo in high mire (mainly covered by Sphagnum) is lower than that in low mire (mainly covered by Phragmites and Carex).     

Remote sensing based estimation system for winter wheat yield in North China Plain

1IN~IOXChinaisabigagriculturalcountrywithaverylargePOPulation.ChinesegovernmentattacheSgreatimportancetomdproduction.Anobviousapplicationofsatelliteremotesensing,withitsregularsynOPticcoverage,istOmonitoragriculturalpefforrnance.CropyieldestimationhaSbeenoneofthemainapplicationsofspaceremotesensingtechnologysincethelaunchingofhighrefutionsatellite-Landsat.Forgaininginformationofcropsproductionintime,StatePlanning~ssionsetupanationalkeyprojectduringtheeighthfiveyearplanPened(1991--1995)c…     

太湖水质参数MODIS的遥感定量提取方法

本文利用MODIS数据的可见光、近红外波段和准实时的地面采样数据,分别利用线性回归模型和神经网络模型反演了太湖的叶绿素a和悬浮物浓度.结果表明,利用MODIS数据的波段组合(M2/M8)和(M2/M9)可估算太湖的叶绿素a浓度;而MODIS数据的波段组合(M12/M17)、(M13/M17)及MODIS(M4)波段能定量估算太湖的悬浮物浓度,但估算精度仍不能满足实际需要.因此,构建了一个以MODIS可见光及近红外波段为输入,以太湖水质参数为输出的2层BP神经网络模型反演太湖的水质参数,大大提高了反演精度.     

ESTIMATION OF VEGETATIVE SURFACE ALBEDO IN THE KUSHIRO MIRE WITH LANDSAT TM DATA──A New Approach to Atmospheric and Spectral Corrections

I.I~crIOXNOwadays,theremotesensingtechniqueshavebeenappliedinmeteorology,oceanography,hydrologyandsomeotherscientificfields,andbecomeauSefulmethodformonitoricsavastregion.Monitoringwithsatelliteremotesensinghas~advantageSincollectingdatacontinuously,regularlyandrepeatedlyinalargearea,inparticularinavastwetlandwherethefieldinvestigationisverydifficult.Therefore,remotesensingwithsatellitedataisthemostsuitablemethodforthesurveyinthiskindofregion.Untilthecoddleofthe20thcentury,wetlandhassometim…     

遥感数据的高斯金字塔尺度上推方法研究

尺度转换是遥感信息科学领域的研究热点,其传统研究方法大多局限于统计模型,对数据的空间结构信息考虑较少,很难满足遥感数据的多尺度表达要求。基于此,针对遥感数据的尺度不一致问题,本文提出了一种利用高斯金字塔的图像模糊特性进行遥感数据尺度上推的方法,在对金字塔每一层的数据高斯模糊的基础上,通过多次连续的降采样,得到一系列不同尺度的数据,从而满足实际应用的空间分辨率要求。为了验证本文所提方法的有效性,本文选择Landsat7 ETM影像和ASTER GDEM为研究数据进行尺度上推,并与传统的最邻近、双线性以及立方卷积等方法进行了实验对比,采用均值、方差、均方根误差、平均绝对误差等评价指标,以及相同分辨率的ASTER GDEM和SRTM DEM的等高线套合结果来衡量高斯金字塔方法的性能。实验结果表明,本文使用的高斯金字塔尺度上推方法能够有效地实现连续遥感数据的尺度转换,在保持遥感数据局部细节特征的基础上,较好地保持了原始遥感数据的信息量以及空间结构特征。     

Chlorophyll fluorescence extraction from water-leaving radiance of algae-containing water through polarization

When measuring reflectance spectra, it is very important to accurately extract chlorophyll fluorescence from elastic- scattering light in water-leaving radiance. The elastic scattering of light by water particles produces partially polarized light. In contrast, chlorophyll fluorescence in planktonic algae yields completely unpolarized light. These properties can be used to separate fluorescent signals from the water-leaving radiance and thus to determine chlorophyll concentration. The algal species Aureococcus anophagefferens was used to conduct a laboratory polarization experiment. For the tests, we used a field spectroradiometer and a polarizer; measurements were collected using two different observation modes. The chlorophyll fluorescence curve extracted through polarization shows an excellent match with the results obtained using the fluorospectro photometer for both measurement modes, suggesting that polarization-based chlorophyll fluorescence extraction may be feasible. The extracted fluorescence is more reliable at incident zenith angles ranging from 30° to 60°. For algae-containing water, the results improve with increasing chlorophyll concentration. This method could help improve chlorophyll concentration measurement and the remote-sensing detection of resulting harmful algae blooms.     

基于SVG的分布式遥感图像特征提取方法

在遥感图像网络化分布式特征分析与表达过程中,有很多需要栅格数据与矢量数据的混合模型的网络化表达与传输问题,而矢量数据的网络化表达、传输与显示问题则是影响遥感图像分布式处理效率的关键性因素之一。本文首先对SVG技术及其对矢量数据的表达特点作了简介,在介绍遥感图像分布式特征提取系统的运行流程的基础上,对其在遥感图像分布式处理中相关的网络化数据表达与显示问题给出了相应的解决思路,并给出了相应的实例与效果分析。     

机载多光谱影像语义分割模型在农田防护林提取中的应用

农田防护林是农田生态系统的屏障,其健康状况的监测与评估在我国北方农田林网管理中尤为重要。本文以新疆生产建设兵团第三师51团为研究区,使用复合翼无人机CW-20搭载Micro MCA12 Snap多光谱相机获取农田防护林的多光谱影像,经辐射校正、裁剪等预处理,通过优选有效特征和模型比较,提出农田防护林提取的有效方法。首先,基于原始12波段,依据相关性系数矩阵和最佳指数因子（Optimum Index Factor,OIF）选取最优3波段和植被指数特征进行组合,构建8种农田防护林提取方案;然后,通过建立语义分割Deeplabv3+模型进行精度评价,得到最优3波段组合6（波长710 nm）、8（波长800 nm）、 11（波长900 nm）波段为最佳特征组合;最后,以最优3波段为基础,将Deeplabv3+模型与U-Net、ENVINet5模型进行对比分析。结果表明：Deeplabv3+模型能够更深层次的挖掘光谱中潜在的信息,相比其他模型,能够较好地处理正负样本不均衡问题,获得最高MIoU值85.54%,比U-Net、ENVINet5的MIoU值则分别高出21.21%、27.19%。该研究结果可为基于多光谱遥感影像的语义分割在农田防护林提取及健康状况监测的应用提供借鉴和参考。     

从增强型水体指数分析遥感水体指数的创建

本文对新近提出的增强型水体指数(EWI)进行了分析和讨论,分别用经过大气校正和未经大气校正的两种影像来对该指数作了验证,并与改进的归一化差值水体指数(MNDWI)进行比较。结果表明该指数在经过大气校正的影像中对水体的增强和提取效果不理想,许多水体影像特征不但未能得到增强,反而受到抑制而被漏提。显然,该指数在创建时忽略了大气因素的影响。另外,该指数在构建上重复选择近红外和中红外波段也是造成提取效果不理想的原因之一。因此,为了创建正确的水体指数,避免水体增强和提取结果的偶然性和不确定性,水体指数的创建必须用经过大气校正的影像进行验证,而构建指数的波段也要避免不合理的重复选择,这样才能使所创建的指数具有更广的适应性。     

一种基于FY3D/MERSI2的AOD遥感反演方法

针对目前国产卫星对气溶胶遥感监测应用较少的情况,本研究综合暗象元和SARA算法优势,基于FY-3D MERSI2数据构建了一套气溶胶光学厚度(Aerial Optical Depth, AOD)快速遥感反演方法。首先,引入了传统暗象元算法中的地表反射率经验关系,然后利用AERONET长时间序列的地基观测数据,构建了红波段和蓝波段气溶胶光学厚度、不对称因子和单次散射率之间的关系,最后利用MOD04和AERONET的AOD产品对研究反演结果进行了验证和评估分析。结果发现：① 本研究反演的AOD不仅保持了与MODIS的气溶胶产品空间分布的一致性,而且合理地呈现了AOD的高值分布,改进了MOD04气溶胶产品在云和亮目标方面反演缺失问题;② 利用AERONET地基观测结果对本研究获取的MERSI2的AOD反演结果进行了对比分析,发现二者具有较高的线性相关性,蓝波段AOD线性相关系数超过0.85;③ 利用MERSI2数据完整地捕捉到了2018年3月9—14日京津冀及周边区域的一次重污染过程中气溶胶时空分布变化情况,这也说明了FY3D卫星具备良好的气溶胶遥感监测能力,为我国灰霾监测和预警提供参考依据。本研究对大力发展国产卫星在大气环境遥感的应用有重要参考意义。     

Evaluation of the retrieval of total suspended matter concentration in Taihu Lake,China from CBERS-02B CCD

Remote sensing techniques is used to quantify the total suspended matter concentration (C _TSM). In this study, we used remotely sensed data to retrieve the C _TSM for the Taihu Lake, China, and developed an atmospheric correction algorithm especially for CBERS-02B CCD data. We simulated the remote sensing reflectance (R _rs) of CCD bands using in-situ observations made in a cruise over the Taihu Lake in autumn 2004, from which a retrieval model is established with simulated R _rs(830) and measured C _TSM. In addition, we applied the atmospheric correction algorithm and retrieval model to process the CCD data over the lake in 2008 and to retrieve the C _TSM. The RMS relative error between the C _TSM retrieved from MODIS and from the CCD images is about 42.9%, indicating that algorithms described in this paper can be used for the application of CCD data in monitoring the C _TSM distribution in the Taihu Lake.     

Object-oriented Urban Dynamic Monitoring——A Case Study of Haidian District of Beijing

It is crucial to conduct the land use/cover research to obtain the global change information.Urban area is one of the most sensitive areas in land use/cover change.Therefore land use/cover change in urban areas is very im-portant in global change.It is vital to incorporate the information of urban land use/cover change into the process of decision-making about urban area development.In this paper,a new urban change detection approach,urban dynamic monitoring based on objects,is introduced.This approach includes four steps:1)producing multi-scale objects from multi-temporal remotely sensed images with spectrum,texture and context information;2)extracting possible changed objects adopting object-oriented classification;3)obtaining shared objects as the basic units for urban change detection;4)determining the threshold to segment the changed objects from the possible changed objects using Otsu method.In this paper,the object-based approach was applied to detecting the urban expansion in Haidian District,Beijing,China with two Landsat Thematic Mapper(TM)data in 1997 and 2004.The results indicated that the overall accuracy was about 84.83%,and Kappa about 0.785.Compared with other conventional approaches,the object-based approach was advantageous in reducing the error accumulation of image classification of each datum and in independence to the radiometric correction and image registration accuracy.     

基于Cubist模型树的城市不透水面百分比遥感估算模型

不透水面是城市区域中一种典型的土地覆盖类型,是衡量城市环境质量和城市化水平的重要标志之一。与传统基于像元级的遥感研究方法相比,不透水面百分比（Impervious Surface Percent,ISP）的估算可以进入像元内部,获得更准确的城市信息。本文应用Cubist模型树,对Landsat TM的原始波段变量（除热红外波段）,建立ISP估算的基础模型（Base Cubist-ISP）。通过基于模型树的集成学习优化算法和加入相邻时相影像的波段变量中值,以削弱噪声的影响。然后,优选热红外波段和各种衍生变量,并进行属性精简,继而应用集成学习算法得到的参数和精简后的变量建立ISP估算的优化模型（Optimal Cubist-ISP）。对广东省广州市海珠区的实验结果表明,Optimal Cubist-ISP模型估算不透水面的整体均方根误差（RMSE）为12.98%,决定系数（R²）为0.90,精度明显优于Base Cubist-ISP模型,RMSE降低约5.03%,ISP在透水面区域被高估和高密度不透水面区域被低估的现象得到改善。本文提出的基于Cubist模型树建立ISP遥感估算的模型及优化方法可以适用于城市区ISP的提取。