基于MODIS的大气因素对蓝藻水华信息提取的影响

本文利用MODIS提供的两种影像产品和代表大气条件的气溶胶产品,运用单波段(NIR)和比值植被指数(NIR/G)两种方法分别提取太湖蓝藻信息.在阐述气溶胶的光学厚度对遥感影像影响的基础上,定量分析了气溶胶光学厚度对两种方法提取蓝藻水华面积的净变化值和选取阈值的影响程度.研究结果表明,运用单波段和比值植被指数两种方法提取太湖蓝藻水华面积差异与气溶胶光学厚度的相关性,固定阈值情况下的相关性高于自选阈值中的对应值.两种指数中大气校正前的阈值与气溶胶光学厚度的相关性都要高于大气校正后两者的相关性.这说明大气会对阈值的设定产生一定的影响,进而影响蓝藻信息提取精度.因此,定量分析气溶胶光学厚度对监测蓝藻是至关重要的.     

退牧还草工程项目遥感分析与效益评价——以四川省阿坝县为例

根据对卫星遥感影像的判读解译,探讨了利用3S技术（遥感（RS）、全球定位系统（GPS）、地理信息系统（GIS）技术）监测四川省阿坝县的退牧还草工程现状。通过陆地卫星TM遥感影像数据和同期野外调查数据,分析了植被指数与草地植被生物量之间的相关关系,建立了不同植被指数与草地生物量之间的一元线性回归模型和非线性回归模型。结果表明,利用遥感卫星的植被指数可以较好反映牧草植被群落变化和不同草原类型的牧草产草量差异。在全年放牧草地中,地上总生物量、植被总覆盖度、植被平均高度等指标均低于围栏内的草地。因此,利用“3S”技术可以对全县草原地上生物量进行遥感估测并对草原基况做出评价,客观反映退牧还草工程实施后效果。同时,为推动高空间分辨率卫星影像在我国草业和生态环境建设中的应用打下了坚实基础。     

HJ-1A/B卫星CCD影像大气订正

大气订正是遥感信息定量化研究中必不可少的一步,目前已有一些成熟的方法,但由于HJ-1A/B卫星CCD相机波段设置特点,常规的大气订正方法基本不适合于HJ-1A/BCCD影像.本文在大量分析HJ-1A/BCCD影像中不同地物的多种指数基础上,提出了改进暗目标法实现HJ-1A/BCCD影像的大气订正,该方法采用比值植被指数(RVI)、土壤调整植被指数(SAVI)和归一化水体指数(NDWI)的综合分析法确定暗像元自动提取,使之适用于环境减灾卫星CCD影像数据.为了客观地验证该方法的精度,本文选取地表平坦均一的敦煌校正场作为实验区,通过多次测量卫星过境时的地表反射率进行分析验证.     

卫星影像大气校正中气溶胶模型的影响分析-以天津地区为例

基于大气校正中常用的大气辐射传输模拟软件6S模型,探讨了不同气溶胶模型对卫星影像大气校正的影响及其适用性问题。选取我国环境小卫星星座HJ\|1的CCD传感器数据,以天津地区大气污染和较清洁条件下的卫星影像为例,基于6S进行大气校正,定量估算了气溶胶模型选取对大气校正精度的影响。与此同时,通过地面太阳-天空辐射计实测,获得研究区域整层大气气溶胶参数进行大气校正,并与基于气溶胶模型的校正结果进行对比,得到以下结论:①6S气溶胶模型中,大陆型与海洋型的校正结果比较接近,而城市型气溶胶模型由于含有较高的煤烟成分比例,其校正结果与前两种相差较大;②天津地区在大气污染情况下,适合应用大陆型气溶胶模型进行大气校正,而在大气较清洁的情况下可选择海洋型气溶胶模型。
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HJ-1A/B星地表反照率生成算法与检验

提出了适合环境与灾害监测预报小卫星-A、B星(简称HJ-1A/B星)CCD相机的大气订正算法,并基于不同地表特性和大气条件下的辐射传输模拟数据,建立HJ-1A/B星的窄波段向宽波段反照率转换的模型.利用多级灰阶靶标实测数据、敦煌检验场实测数据验证了大气订正算法以及转换模型的可靠性和精度,并将HJ-1A/B星影像数据计算的反照率产品与同时相的MODIS反照率产品进行对比分析.结果表明:文章提出的HJ-1A/B星CCD相机大气订正算法可有效校正大气影响;窄波段向宽波段反照率转换模型反演的反照率精度可靠;基于研究成果生成的HJ-1A/B星地表反照率与MODIS反照率产品一致性较好,满足后续遥感数据定量化模型研究的精度需要.     

基于波谱匹配的Hyperion数据大气校正方法对比研究

遥感影像数据的大气校正是高光谱遥感地空对比、信息提取的前提和关键,如何根据不同数据、不同研究区、不同研究目的选择合适的大气校正方法是高光谱遥感应用研究的重点和难点。针对EO\|1卫星Hyperion高光谱遥感数据特点和研究区地形环境特征,分别选择线性回归经验模型、基于MODTRAN4模型的FLAASH和基于DEM数据的ACORN\|3模型不同大气校正方法对研究区Hyperion数据进行大气校正。从波谱匹配、识别的目的出发,通过计算不同方法校正后影像像元的波谱曲线与实测地面波谱曲线的匹配程度分析不同大气校正方法的校正效果。     

山丹县草地地上生物量遥感估算模型

选择黑河流域草地植被的典型区域-山丹县作为研究区, 利用2003 年8 月野外实测50 个样方的草地地上生物量数据和同期的陆地卫星TM 影像数据, 分析了植被指数与草地地上生物量的相关关系, 进而建立基于遥感植被指数DV I 的草地地上生物量估算模型。结果表明: 在草地地上生物量和TM 影像植被指数之间关系微弱、直接利用TM 影像数据建立估算模型不可行的情况下,用地面实测的草地植被反射光谱数据对遥感影像数据进行校正, 能够弥补传统的“点-面”建模方法的不足, 获得比较理想的估算模型; 植被指数DVI 与草地地上生物量之间存在较好的相关性, 其估算模型为Y = 2477X - 77. 598 (R 2= 0. 7589) , 经实测数据验证, 总体精度达到80% 以上, 基本上能够满足中尺度的草地地上生物量估算。     

NOAA卫星轨道漂移的影响初探

选取一个NOAA轨道周期的来列资料，在对影像的太阳高度角、大气状况及地表物理特性作同化处理的基础上，分析了地面卫星视角的变化对NOAA五个原始通道数据及反射率、温度的影响，同时比较了不同植被指数组合对卫星视角变化的响应情况，均得出有一定规律性的结果。     

TM遥感影像的地形辐射校正研究

从地面所接收到的太阳直接辐射、天空散射辐射和临近地形反射附加的辐射三个方面分析计算地面每个像元的太阳总辐射,并在此基础上建立地表真实反射率恢复模型,实现对地形的辐射校正。在算法实现上,采用交互式数据语言（Interactive Data Language,IDL）,结合6S大气校正模型和数字高程模型（DEM）进行编程实现。利用北京山区的TM遥感影像所做的实验表明该方法能有效地消除卫星影像中地形的影响,为影像的后续处理提供更真实的信息。     

规模化土地利用变化动态监测的辐射校正技术研究

在土地利用变化动态监测中,辐射校正是非常重要的一项预处理过程,它能够提高土地利用分类及土地利用变化检测的精度。本文通过一系列试验,对比分析了辐射校正中的地形效应校正算法,太阳高度角校正算法,基于传输模型的大气校正算法和相对辐射校正算法。最后得出了一套适用于规模化土地利用监测的辐射校正处理技术流程。     

基于IDL语言的太湖蓝藻水华遥感监测信息系统设计

以MODIS L1B数据为数据源,采用IDL语言,运用系统配置与插件技术实现系统架构,设计中间件解决系统框架和IDLDrawWidget控件通信接口的衔接问题,设计模型对象管理器组织模型对象,设计IDL数据显示的组织结构实现图像显示及其与矢量数据的叠加显示,使用相对图像坐标系显示叠加的矢量数据,并运用影像匹配技术和仿射变换技术分别实现了MODIS L1B影像"双眼皮"消除及其几何校正,在此基础上运用蓝藻水华遥感监测模型,实现蓝藻水华空间分布信息自动化提取。     

基于海岸带高光谱成像仪影像的太湖蓝藻水华和水草识别

水华与水草的同步监测对于研究湖泊水环境、生态特性以及水循环具有重要意义,相对于传统监测方法如实地调查,利用遥感手段具有大范围、长时间周期、高效率以及低成本等优势。基于海岸带高光谱成像仪HICO(Hyperspectral Imager for the Coastal Ocean)影像,利用叶绿素a光谱指数和藻蓝蛋白基线的水华和水草识别模型,提取太湖水华和水草分布图,经过检验,水华和水草的平均提取精度为93%和95%;通过水华和水草分布图的叠加分析了2010~2014年太湖水华和水草的分布规律,与相关文献的分析结果一致,进一步证实了识别方法的可靠性;将平均阈值与最佳阈值进行对比分析,提取水华与水草面积的精度分别为75.7%和84%,在对精度要求不高但对效率要求较高的情况下,可以利用平均阈值提取水华和水草,便于实现水华和水草的自动化提取及批处理。     

Passive optical remote sensing of cyanobacteria and other intense phytoplankton blooms in coastal and inland waters

Increased frequency and extent of potentially harmful blooms in coastal and inland waters world-wide require the development of methods for operative and reliable monitoring of the blooms over vast coastal areas and a large number of lakes. Remote sensing could provide the tool. An overview of the literature in this field suggests that operative monitoring of the extent of some types of blooms (i.e. cyanobacteria) is relatively straightforward. Operative monitoring of inland waters is currently limited to larger lakes or using airborne and hand-held remote sensing instruments as there are no satellite sensors with sufficient spatial resolution to provide daily coverage. Extremely high spatial and vertical variability in biomass during blooms of some phytoplankton species and the strong effects of this on the remote sensing signal suggest that water sampling techniques and strategies have to be redesigned for highly stratified bloom conditions, especially if the samples are collected for algorithm development and validation of remote sensing data. Comparing spectral signatures of different bloom-forming species with the spectral resolution available in most satellites and taking into account variability in optical properties of different water bodies suggests that developing global algorithms for recognizing and quantitative mapping of (harmful) algal blooms is questionable. On the other hand some authors cited in the present paper have found particular cases where satellites with coarse spectral and spatial resolution can be used to recognize phytoplankton blooms even at species level. Thus, the algorithms and methods to be used depend on the optical complexity of the water to which they will be applied. The aim of this paper is to summarize different methods and algorithms available in an attempt to assist in selecting the most appropriate method for a particular site and problem under investigation.     

Comparison of atmospheric correction algorithms for TM image in inland waters

In order to extract quantitative water‐leaving information from the Thematic Mapper (TM) image accurately in inland waters, atmospheric correction is a necessary step. Based on former researchers' results, the paper presents two atmospheric correction algorithms based on meteorological data (MD) and on Moderate Resolution Imaging Spectroradiometer (MODIS) Vicarious Calibration (MVC) for TM image in inland waters according to the theory of radiative transfer. Studying Taihu lake, China, in this paper we derived water remote sensing reflectance from a TM image of 26 July 2004 by these two atmospheric correction algorithms and we compare the results with that of dark object subtraction (DOS) and 6S code. The results show that the effect of atmospheric correction based on meteorological data and MODIS Vicarious Calibration is much better than that of DOS and 6S code. Although the MD is more accurate, MVC may be an ideal choice for TM images in inland water because TERRA MODIS images can be acquired easily than collecting meteorological data at the time of satellites passing over.     

太湖蓝藻水华遥感监测信息系统设计及其关键技术

快速提取太湖蓝藻水华空间分布信息对于制定相关应急预案有重要意义,构建太湖蓝藻水华遥感监测信息系统可为之提供有力支持。从系统总体结构和系统流程角度介绍系统设计思路,并阐述研发本系统的关键技术。采用系统配置与单体软件模式技术实现菜单驱动的系统架构,并在影像数据自动化预处理基础上,运用蓝藻水华遥感监测模型,实现蓝藻水华空间分布信息自动化提取,使得本系统在太湖蓝藻水华遥感监测的业务化运行中取得明显效果。     

遥感影像地形与大气校正系统设计与实现

遥感影像地形和大气校正是提高定量化遥感数据处理精度的重要因素。目前的数据处理软件系统集成了一些地形和大气校正算法,但在应用中还存在不能获取重要的地形参数(如阴影因子、天空可视因子等),需提供精准DEM和校正方法基于朗伯体地表假设等问题。为应对遥感专业用户需求,设计并实现了遥感影像地形与大气校正软件系统,用以对影像进行地形辐射校正、获取DEM数据和相关地形参数、地形与大气校正等。介绍了系统的功能模块设计并展示了系统的原型版本,并应用系统中的地形和大气校正方法获取了HJ/CCD影像和Landsat/TM影像的反射率。校正结果表明:该系统中的BRDF模型能够有效消除地形影响。系统的实现可以为遥感科学研究和应用提供支撑。     

Remote sensing of cyanobacteria-dominant algal blooms and water quality parameters in Zeekoevlei, a small hypertrophic lake, using MERIS

Eutrophication and cyanobacterial algal blooms present an increasing threat to the health of freshwater ecosystems and to humans who use these resources for drinking and recreation. Remote sensing is being used increasingly as a tool for monitoring these phenomena in inland and near-coastal waters. This study uses the Medium Resolution Imaging Spectrometer (MERIS) to view Zeekoevlei, a small hypertrophic freshwater lake situated on the Cape Flats in Cape Town, South Africa, dominated by Microcystis cyanobacteria. The lake's small size, highly turbid water, and covariant water constituents present a challenging case for both algorithm development and atmospheric correction. The objectives of the study are to assess the optical properties of the lake, to evaluate various atmospheric correction procedures, and to compare the performance of empirical and semi-analytical algorithms in hypertrophic water. In situ water quality parameter and radiometric measurements were made simultaneous to MERIS overpasses. Upwelling radiance measurements at depth 0.66 m were corrected for instrument self-shading and processed to water-leaving reflectance using downwelling irradiance measurements and estimates of the vertical attenuation coefficient for upward radiance, K_u, generated from a simple bio-optical model estimating the total absorption, a(λ), and backscattering coefficients, b_b(λ). The normalised water-leaving reflectance was used for assessing the accuracy of image-based Dark Object Subtraction and 6S Radiative Transfer Code atmospheric correction procedures applied to MERIS. Empirical algorithms for estimating chlorophyll a (Chl a), Total Suspended Solids (TSS), Secchi Disk depth (z_SD) and absorption by CDOM (a_CDOM) were derived from simultaneously collected in situ and MERIS measurements. The empirical algorithms gave high correlation coefficient values, although they have a limited ability to separate between signals from covariant water constituents. The MERIS Neural Network algorithms utilised in the standard Level 2 Case 2 waters product and Eutrophic Lakes processor were also used to derive water constituent concentrations. However, these failed to produce reasonable comparisons with in situ measurements owing to the failure of atmospheric correction and divergence between the optical properties and ranges used to train the algorithms and those of Zeekoevlei. Maps produced using the empirical algorithms effectively show the spatial and temporal variability of the water quality parameters during April 2008. On the basis of the results it is argued that MERIS is the current optimal sensor for frequent change detection applications in inland waters. This study also demonstrates the considerable potential value for simple TOA algorithms for hypertrophic systems. It is recommended that regional algorithm development be prioritized in southern Africa and that remote sensing be integrated into future operational water quality monitoring systems.     

于桥水库蓝藻水华遥感长时序监测研究

针对水库富营养化给供水安全带来的严重威胁，利用2008~2017年Landsat时间序列卫星数据，基于归一化差值植被指数（NDVI）与实测水质参数的相关分析结果，运用阈值法动态提取了于桥水库的水华分布范围和程度。通过与自然和人为因子的协同分析，认为气温、降水和人类活动等共同驱动引发了水华爆发，其中人为干预的生态修复工程可抑制或减缓水华爆发，并有效改善水质状况。时间分辨率更高的气象因子数据和卫星遥感数据将更有助于对中小型饮用水水面蓝藻水华驱动力的分析，推动准实时遥感监测预警技术应用。     

Remote Sensing Long-term Monitoring of Cyanobacterial Blooms in Yuqiao Reservoir

Reservoir eutrophication leads serious threat to water supply safety. This paper apples Landsat time series satellite data from 2008 to 2017 to extract the distribution and degree of water bloom in Yuqiao Reservoir based on a threshold method to the correlation analysis results between Normalized Difference Vegetation Index (NDVI) and measured water quality parameters. Through the collaborative analysis of both natural and artificial factors, the water bloom was jointly drive by temperature, precipitation, and human activities. Among them, the ecological restoration project with human intervention could inhibit or slow down the blooms and effectively improve the water quality. Meteorological and spaceborne remote sensing data with higher temporal resolution will be more conducive the analyze the driver force of cyanobacteria blooms on small and medium-sized drinking water surfaces. Meanwhile, remote sensing data based monitoring and early warning technology could be promoted.