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。     

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.     

突发水污染事件中遥感瓦片大数据存储系统

突发水污染事件频发,利用GIS平台、遥感技术及水质模型对突发水污染事件进行模拟研究逐渐成为一种发展趋势.针对目前海量、异构、动态遥感数据难以快速处置和高效存储的问题,基于HBase设计和实现了突发水污染事件的遥感瓦片大数据存储系统.该系统以数字地球平台为支撑,结合遥感瓦片金字塔模型和MapReduce框架,考虑实时、动态观察事件发展态势引起的瓦片数据频繁加载特点,对遥感瓦片数据的线性四叉树编码索引进行了改进,将其同水污染数据一并存储到HBase数据库中,并通过增加缓存区来提升遥感瓦片数据的访问效率.将此系统应用于渭河陕西段突发水污染事件中,实验结果表明:改进后的索引可在200个毫秒时间内提取到水污染区域的遥感数据,引入的缓存机制使得水污染区域遥感数据的加载时间节省了近2/3.因此,该存储系统访问效率高,能够满足突发水污染事件快速应急模拟的需求.     

Predicting algal bloom in the Techi reservoir using Landsat TM data

The application of statistical models in a remote sensing field is an indispensable tool. The main purpose of this study was to develop an empirical model to detect algal blooms phenomenon in the Techi reservoir, Taiwan. We used ratios of logarithm transformed radiance values from Landsat Thematic Mapper (TM) data to establish statistical relationships to dinoflagellate densities. The procedure used a forward selection method to develop multiple linear regression models. The selected independent variables matched the dinoflagellate algal cell densities to build the bloom prediction model. The result showed that the bloom prediction model can predict the algal bloom phenomenon with 74% accuracy in this study. The major limits were the spectral sensitivity and spatial resolution of the scanning device. If we can acquire greater spectral sensitivity and spatial resolution in the remote sensing data, we can attain higher model accuracy.     

多源遥感影像融合在太湖蓝藻监测中的应用

基于空间分辨率分别为1 100 m和500 m的NOAA/AVHRR和EOS/MODIS遥感数据,考虑遥感影像区域内各像素之间的区域特征,设计了基于小波分析的区域能量融合方法(REFS_wt),低频小波系数采用平均值而高频系数采用区域能量法,并与基于像素灰度值的区域能量法(REFS_pl)进行融合性能比较,结果表明REFS_wt法的融合性能明显优于REFS_pl。将此方法应用于太湖蓝藻监测,将空间分辨率较低的AVHRR影像蓝藻水华信息与较高分辨率的MODIS影像融合,得到较高分辨率的太湖蓝藻水华遥感监测图,融合图像信息量和清晰度都有所提高。     

赤潮卫星遥感监测与应用研究进展

赤潮监测是海洋遥感应用的一个重要组成部分。近30 a来,国内外学者发展了许多基于卫星平台的赤潮遥感监测算法。通过回顾赤潮卫星遥感监测的发展历史,总结了各种传感器的赤潮卫星遥感监测算法,分析了各种算法的性能与适用范围。最后,对目前赤潮卫星遥感监测面临的问题进行了讨论,并对未来赤潮遥感监测的发展提出展望。     

水源保护区划界的遥感与GIS技术研究

科学合理地划定水源地的保护范围是一项技术含量较高的工作。以厦门市饮用水源中的北溪引水渠(管道)和坂头水库为例,根据饮用水源保护区划分原则,研究基于数字化的地形图建立数字高程模型并自动生成汇水区盆地和流域范围的GIS技术、获取相关自然环境专题信息的遥感技术、以及综合利用社会和自然等多种数据源进行保护区范围界定的方法。重点探讨数字高程模型的建立以及汇水区盆地和流域边界自动生成的GIS方法。     

湖泊藻类水华神经网络预测研究

在分析湖库藻类水华形成机理特征基础上,确定湖库水华形成关键影响因素,即总氮、总磷、化学需氧量、温度与叶绿素a等,结合关注区域的遥感监测信息,构建基于神经网络的藻类水华预测模型,实现对湖库藻类水华的有效预测,通过仿真验证该方法的有效性,为湖库藻类水华预测提供一种有效途径。     

Quantitative monitoring of inland water using remote sensing of the upper reaches of the Huangpu River,China

In this paper, a quantitative framework using common and readily available remote sensing data, including ground hyperspectral data, multispectral remote sensing images and a regular in situ water quality monitoring programme, is proposed to monitor inland water quality. The entire framework has three steps: (1) collecting and processing basic data, including remote sensing data and water quality data; (2) examining the relationships between water quality parameters and water reflectance from both remote sensing images and in situ measurement data. According to their relationships with ground hyperspectral reflectance, the water quality parameters are classified into three categories, and the corresponding monitoring models using remote sensing data are presented for these three categories; and (3) analysing the spatial distribution by using water quality concentration maps generated with the monitoring models. The upper reaches of the Huangpu River were chosen as our study area to test this framework. The results show that the concentration maps inverted by the proposed models are in accordance with the actual situation. Therefore, we can conclude that the proposed framework for quantifying water quality based on multisource remote sensing data and regular in situ measurement data is an effective and economic tool for the rapid detection of changes in inland water quality and subsequent management.     

基于遥感技术的海岸带资源环境管理

海岸带是人口密集、资源丰富、开发程度较高,但生态环境又往往相对脆弱的地区。随着我国沿海地区经济高速发展,海岸带区域的环境状况发生了显著变化。这些变化信息依靠常规的调查手段难以及时获取,而卫星遥感技术则能够为监测海岸带及毗连海域资源环境变化提供有效手段。如何利用多源、多通道、多时相、主被动融合的星载遥感数据获取海岸带及毗连海域资源环境信息是我们亟需了解的问题。分别从海洋渔业资源调查、珊瑚礁及红树林等海岸生物资源的遥感、海洋水质监测、赤潮的监测与预警、溢油和海冰的监测等方面论述了遥感技术的特点与优势。并对遥感技术在海岸带资源环境管理中的应用做了展望。     

基于地球大数据的“美丽湖泊”SDG 6.3.2综合评价体系构建

湖泊等水体水质状况直接关系到人类社会的可持续发展。传统的水环境质量评价体系大都基于统计数据和原位测量数据,存在周期过长和时效性差等问题,难以实现大范围、连续地湖泊水环境质量评价。遥感技术的发展为高时空分辨率的湖泊水环境质量评价提供了可能。在总结现有湖泊水环境质量评价体系的基础上,以联合国可持续发展目标(Sustainable Development Goals,SDGs)中指标SDG 6.3.2(环境水质良好的水体比例)为导向,结合统计数据、野外实测数据和卫星遥感数据等地球大数据构建了"美丽湖泊"综合评价体系,以期在联合国可持续发展目标框架下,推进我国湖泊水环境质量综合评价,为美丽中国评价提供技术参考。     

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。     

基于多源遥感数据协同反演森林地表土壤水分研究

土壤水分在土壤监测中是一项重要的指标,对于农业生产、生态环境以及水资源管理有着重要的影响.随着遥感建模与反演理论的不断成熟,其逐渐成为分析土壤指标的重要技术与手段.因此,利用光学影像与雷达影像数据,以大兴安岭地区漠河市为研究区域,分别建立以Landsat 8为数据源的土壤水分反演模型和由Landsat 8影像数据与GF...     

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。     

富营养化水体环境中COD浓度遥感监测系统设计

对富营养化水体环境中COD浓度进行遥感监测,可以预防富营养化水体环境中COD浓度增加,提高水体水质,增加水循环次数,减少水体中有机物的污染;当前富营养化水体环境中COD浓度遥感监测系统设计方法,以Modis遥感影像数据为原理,依据富营养化水体环境中COD浓度的特征提取结果,对富营养化水体环境中COD浓度进行遥感监测,没有具体对遥感监测系统进行详细地设计,无法获取富营养化水体环境中COD浓度高精度的遥感监测信息,存在遥感监测结果偏差大的问题;提出了一种基于Zigbee的富营养化水体环境中COD浓度遥感监测系统设计方法;该方法先对Zigbee的富营养化水体环境中COD浓度遥感监测系统进行硬件设计,采用IMF对富营养化水体环境中COD浓度进行特征提取,以特征提取结果为基础,依据COD浓度指数时间序列实现富营养化水体环境中COD浓度遥感监测,最后利用Retinex法对COD浓度遥感监测的图像进行处理,完成对富营养化水体环境中COD浓度的遥感监测;仿真实验结果证明,所提系统设计方法可以精确地对富营养化水体环境中COD浓度进行安全快速的遥感监测。     

Construction of “Beautiful Lakes” Comprehensive Assessment System based on Big Earth Data and SDG 6.3.2

Lake water quality is directly related to the survival and development of human beings and society. Most of the existing assessment systems are based on statistical data and in-situ measurement data. Due to the long cycle and poor timeliness, these assessment systems are hard to achieve large-scale and continuous assessment of lake water environment. The development of remote sensing technology has made it possible to evaluate the quality of lake water environment with high spatial and temporal resolution. Thus, after summarizing the existing lake water environment quality assessment system, a new assessment system called “Beautiful Lakes” comprehensive assessment system was developed. A novel index system based on Big Earth Data (such as statistical data, field measured data and satellite remote sensing data) was first developed and integrates human activities, water quality, biology and hydrology indexes. Then, the threshold of each index was determined and the Percentage Compliance of Water Quality Index (c_wq) was calculated. Following UN water, the threshold 80% of c_wq was used to classify the water quality, which means if a certain water body is with c_wq greater than 80%, the water quality is “good”; otherwise, the water quality is poor. Finally, the Percentage of Water Bodies of Good Quality (WBGQ) was calculated to attain the comprehensive assessment of water quality on a large scale (basin scale or national scale). The new assessment system will promote the comprehensive assessment of lake water environment quality in China under the framework of the UN Sustainable Development Goals and provide a technical reference for the evaluation of beautiful China.     

水质遥感监测的关键要素叶绿素a的反演算法研究进展

叶绿素a浓度是表征水体富营养化程度的重要指标,通过遥感手段反演叶绿素a浓度是实现水体富营养化监测的一个有效途径,已衍生出了一系列叶绿素a浓度反演算法.这些算法各有所长,适用范围也各自有别.由于水体光学特征差异,盲目套用这些算法难以取得预期效果.为了推动水质遥感的进一步发展,从遥感反演的原理和数据源出发,对国内外利用遥感...     

基于物联网技术的太湖蓝藻水华预警平台

针对以往藻类水华预测系统在数据源方面存在的不足,采用物联网技术,实现基于三层网络传输结构的监测体系,保证了数据的时间连续性;并对遥感水质参数定量反演方法、中程无线传感网络技术和藻类水华预测预警模型方面进行了改进。在此基础上,开发了太湖蓝藻预测预警平台,运行结果表明蓝藻水华未来3天的平均预测精度达到了80%以上。     

Two-component modeling of the optical properties of a diatom bloom in the Southern Ocean

Diatom cells have distinctive optical characteristics, originating from their relatively large cell size, fucoxanthin content and silica cell wall. It has been proposed that diatom-dominated phytoplankton blooms can be identified by optical remote sensing and that specifically tuned chlorophyll and primary production algorithms should be applied in regions where these blooms are present. However there have been few studies on how the optical properties of diatom blooms change as they progress from active growth to senescence, and it is unlikely that measurements on laboratory cultures encompass the full range of physiological states found in natural waters. We have therefore examined the inherent optical properties (IOPs) of the waters around the island of South Georgia at the end of the spring diatom bloom. Considerable variability was found in the relationships between the inherent optical properties and analytically determined chlorophyll a concentrations even in the surface layer, which meant that the usual bio-optical assumptions for Case 1 waters did not apply. To account for this variability, phytoplankton absorption and scattering were modeled as a two-component mixture, with the components representing actively growing and senescent material. The specific inherent optical properties of the two components were derived by linear regression of total IOPs against chlorophyll concentration and a fraction of the suspended mineral concentration. These specific IOPs were used to develop radiative transfer models of diatom blooms in varying stages of growth and senescence. Remote sensing reflectances calculated using this technique confirmed the tendency of the standard algorithms employed in SeaWiFS, MODIS and MERIS data processing to under-estimate near-surface chlorophyll concentrations in diatom blooms. However the inclusion of increasing proportions of senescent material had a significant effect on algorithm performance only at chlorophyll concentrations below 10 mg m^− 3. Optical depths predicted by the model around South Georgia were 9 +/− 2 m at 512 nm, indicating that a large fraction of the phytoplankton biomass was located below the depth from which the remote sensing signals originated.     

水质监测与评价中的遥感应用

不同含量和类别的水质参数的水体光谱特征不同,这使得遥感影像能用于水体水质的监测。本文简要介绍了遥感监测水质的原理,监测的几类水质参数,常用的方法和几种典型水质参数的光谱特征及其遥感研究方法和目前研究的进展情况,最后讨论了这一领域目前仍然存在的一些问题。