黄浦江上游水域的多光谱遥感水质监测与反演模型

运用遥感、GPS定位技术对黄浦江上游淀山湖及支干流水环境质量中的水质污染进行了监测,探讨了以实际监测数据与遥感多光谱特征数据建立溶解氧和透明度两种水质参数的遥感反演数学模型。结果表明,利用遥感技术和数据能有效地监测水质污染状况与分布情况,是一种较为快速、可行的监测手段。     

基于无人机多光谱影像的滏阳河水质遥感反演

滏阳河是邯郸市的重要河流,在工业用水、农业灌溉、生态用水等方面发挥着重要作用。近年来,由于废水、污水等违规排放,滏阳河水体的污染状况明显加重。为深入系统地了解滏阳河水体污染情况,分析污染规律,本文采用水质采样和无人机航飞监测方式,对滏阳河重点区域进行了水体污染数据调查,对水质样本进行了实验室检测,并与无人机航拍获取的44种光谱参数进行相关性分析,建立了浊度(TUB)、悬浮物浓度(TSS)、化学需氧量(COD)、总磷(TP)、总氮(TN)、氨氮(NH₃-N)6种水质参数的多元回归模型。研究结果表明：滏阳河在邯郸市主城区域内呈由南到北、由两岸到中心河流水质参数浓度逐渐增高的分布特征。     

基于遥感技术的湖泊水质参数反演研究综述

湖泊水体污染和营养化问题是当前湖泊研究的重点之一,遥感反演技术由于具有快速、宏观、低成本、周期性的特点,已成为当前水质监测评价的重要技术手段。本文阐述了水质反演方法、反演参数和反演基于的遥感数据源三方面的发展过程,讨论了目前反演过程中存在的主要问题,并对未来遥感反演的研究重点进行了展望。     

水质关键因素光谱遥感监测技术分析

针对传统水体水质分析方法过度依赖于实地测量和实验室化学分析,需要耗费大量人力物力且效率不高的问题,从水质遥感监测数据获取手段、典型反演监测模型、不同水体光谱遥感监测应用状况、水质遥感监测技术应用及前景等方面分析归纳了使用遥感技术监测水质的新方法。从可用数据类型、数据特征等方面对水质遥感监测数据获取的3种主要手段进行了比较;从复杂程度、使用场景、优缺点等方面对4种典型的反演模型进行了归纳;对遥感数据和模型在Ⅰ类和Ⅱ类水体应用中的常用组合方式进行了分析总结。     

植被生物物理参数的光学遥感反演方法综述

传感器技术的迅速发展为植被生物物理参数反演提供了大量可用的光学遥感数据,处理这些海量数据需要稳健高效的反演技术支持。本文总结了利用光学遥感影像定量获取植被生物物理参数的反演方法,将这些方法分为参数回归、非参数回归、基于物理模型和混合方法。首先,回顾了这些方法的理论基础,并分析了它们各自的优缺点。然后,介绍了已发表的应用案例,展示了这些方法在植被生物物理参数反演处理中的实际运用。最后,对这些方法在未来的发展和应用前景进行了展望。     

遥感模型多参数反演相互影响机理的研究

遥感数据具有覆盖范围广、时间与空间分辨率高的特点,被广泛应用于提取区域范围内的一些重要的生物物理参数.为提高参数的提取精度,需要制定正确的反演策略.了解影响参数提取精度的因素、反演过程中各反演参数之间如何相互作用是制定合理反演策略的关键.本文通过数学推导与物理机理的分析,证明了影响参数反演精度的因素不但有冠层反射率数据的质量,还有反演过程中参与反演的未知参数的个数、参与反演的每个参数的敏感性及各个参数敏感性之间的相关性.最后通过对反演不同参数个数、不同数据质量进行了叶面积指数反演的精度分析,验证影响参数反演精度的各个因素.     

基于遗传算法的东湖水质参数反演方法探讨

引入了叶绿素浓度的对数和浊度的对数作为变量,建立了前向光学模型和遗传算法的目标函数,实现了较高的反演精度。     

模拟AMSR-E数据的地表多参数反演

为了提供更适用的地表参数反演方案,对Njoku等模拟AMSRE-E数据的多参数反演工作重新进行正向模拟和算法改进,算法用MATLAB开发实现.反演结果表明,改进后的反演方法不仅在精度上略高于原方法,而且还能反演裸露地表可实际测量的粗糙度参数,并在更大的植被含水量范围内达到较高的反演精度.     

基于支持向量机的高光谱遥感分类进展

支持向量机作为一种最新的也是最有效的统计学习方法,近年来成为模式识别与机器学习领域一个新的研究热点。支持向量机因其适用高维特征、小样本与不确定性问题的优越性,是一种极具潜力的高光谱遥感分类方法。在分析基于支持向量机的高光谱遥感影像分类进展的基础上,对若干需要进一步研究的问题包括多类分类策略、训练样本与特征空间优化、不确定性控制、核函数选择与优化等进行探讨。     

激光雷达在森林参数反演中的应用

激光雷达是近年来国际上发展十分迅速的主动遥感技术,在森林参数的定量测量和反演上取得了成功的应用。在林业上,高采样密度激光雷达能够获取单株木3维结构特征,采用不同的数据处理方法,可以得到不同精度的单株木参数。利用激光雷达测量森林参数不仅节省了人力,还提高了工作效率,现在已经成为快速获取树木几何参数的一种有效方法。文中主要介绍了LiDAR工作原理、类型及特点、影响LiDAR数据质量的因素、国内外LiDAR的发展状况及应用领域,重点介绍了国内外利用LiDAR数据反演森林参数(树高、郁闭度、冠幅、林分密度、断面积和蓄积量等)的方法和研究进展,同时对今后LiDAR在森林参数反演方面的研究作了展望。     

A filtering approach for estimating lake water quality from remote sensing data

In this paper we consider the estimation of lake water quality constituent distributions from hyperspectral remote sensing data. We present a computational approach that can be used to assimilate information from mathematical evolution models into data processing. The method is based on a reduced order iterated extended Kalman filter, and a convection–diffusion model is used to describe the movement of the water quality constituents. The performance of the technique is evaluated in a simulation study. The results show that the filter approach with an appropriate evolution model yields estimates that have better spatial and temporal resolutions than those obtained with conventional methods. Furthermore, the use of a feasible evolution model may make it possible to obtain information also on the concentrations in the lower parts of the lake.     

基于水体光学分类的二类水体水环境参数遥感监测进展

二类水体主要包括内陆及近岸水体,受浮游植物、悬浮颗粒、有色可溶性有机物等多种因素影响,光学特性复杂多变,难以建立统一的水环境参数遥感定量估算模型.针对水体的光学特征,进行水体光学分类,进而反演水环境参数的方法,不仅能够提高参数估算精度,而且便于模型在同类水体中推广应用.水体光学分类方法主要包括基于固有光学特征的光学分类...     

空-谱角匹配与多指数法相结合的OLI遥感影像水体提取

针对复杂环境条件下水体遥感提取结果不连续且易与植被、建筑物、阴影相混淆的难题,基于Landsat 8 OLI影像,以石家庄市平山县岗南水库和宿迁市骆马湖附近河流为研究区,提出了一种空-谱角匹配与多指数法相结合的水体信息提取方法;并与单波段阈值法、归一化差分水体指数法（NDWI）、光谱角匹配法（SAM）、自动水体提取指数法（AWEI）和一类支持向量机法（OC-SVM）的水体提取结果进行对比分析和精度评定。试验结果表明,本文提出的方法兼顾了多特征之间的互补性优势,引入的空间信息有效地抑制了噪声的干扰,且以像素为基元的提取策略较好地保持了水体的边缘信息,避免了出现平滑掉细节信息的情况;与传统方法相比,本文方法受植被、建筑和阴影的干扰最小,对细小水体也具备较好的识别能力。     

Machine learning approaches to coastal water quality monitoring using GOCI satellite data

Since coastal waters are one of the most vulnerable marine systems to environmental pollution, it is very important to operationally monitor coastal water quality. This study attempts to estimate two major water quality indicators, chlorophyll-a (chl-a) and suspended particulate matter (SPM) concentrations, in coastal environments on the west coast of South Korea using Geostationary Ocean Color Imager (GOCI) satellite data. Three machine learning approaches including random forest, Cubist, and support vector regression (SVR) were evaluated for coastal water quality estimation. In situ measurements (63 samples) collected during four days in 2011 and 2012 were used as reference data. Due to the limited number of samples, leave-one-out cross validation (CV) was used to assess the performance of the water quality estimation models. Results show that SVR outperformed the other two machine learning approaches, yielding calibration R² of 0.91 and CV root-mean-squared-error (RMSE) of 1.74 mg/m³ (40.7%) for chl-a, and calibration R² of 0.98 and CV RMSE of 11.42 g/m³ (63.1%) for SPM when using GOCI-derived radiance data. Relative importance of the predictor variables was examined. When GOCI-derived radiance data were used, the ratio of band 2 to band 4 and bands 6 and 5 were the most influential input variables in predicting chl-a and SPM concentrations, respectively. Hourly available GOCI images were useful to discuss spatiotemporal distributions of the water quality parameters with tidal phases in the west coast of Korea.     

特征维数对支持向量机分类器性能影响的研究——以高光谱遥感影像为例

本文为验证SVM对高维特征的适应性和可靠性,针对不同特征提取方法与特征组合,以国产OMISⅡ传感器获得的北京昌平地区高光谱遥感据为例,对SVM分类器中特征维数对分类准确率的影响进行了试验,通过对主成分分析、最小噪声分离算法、相关系数分组后特征提取、导数光谱等的分析,表明SVM分类器的分类精度随着特征维数波动,其中主成分分析降维后提取的特征具有用于分类能够获得最高的准确率。通过与最大似然法和光谱角制图分类算法的比较,说明在同样的特征输入情况下SVM分类算法分类的准确率高于最大似然法和光谱角制图分类器。     

多源遥感与作物模型同化模拟作物物生长参数时空域连续变化

本文将遥感信息与作物模型同化实现作物生长参数的时空域连续模拟,进而监测生长参数的时空域变化.首先将作物模型WOFOST(World food studies) 与冠层辐射传输模型PROSAIL 耦合构建WOPROSAIL 模型,利用微粒群算法(PSO) 通过最小化从CCD 数据获取的土壤调节植被指数观测值SAVI(soil adjusted vegetation index) 与耦合模型得到的模拟值SAVI’之间差值优化作物模型初始参数.通过MODIS 数据反演实现参数的区域化,并将区域参数作为优化后作物模型输入参数驱动模型逐像元计算生长参数,实现生长参数的时空域连续模拟与监测,最终建立区域尺度遥感-作物模拟同化框架模型RS-WOPROSAIL .结果表明：同化模型解决了作物模型模拟空间域和遥感信息时间域的不连续问题.模型模拟的叶面积指数(LAI) 、穗重(WSO) 、地上总生物量(TAGP) 等生长参数较好地体现了水稻生长状况时空域变化,研究区水稻模拟产量与实际产量的误差为27.4% .     

基于Sentinel-1的长江干流水域面积动态变化遥感监测

本文利用Sentinel-1数据获得了2016-2020年月度长江干流上海-宜宾段水域面积,并分析其年际、年内变化规律。分析结果表明,①月度变化规律为1-5月水面面积变化相对平稳,6-8月水域面积逐步增加,在7月达到峰值;9月稍有回落,10月再次达到峰值后逐步减少至稳定。②季节性变化规律为冬季水域面积最小,夏季水域面积最大,夏季和冬季呈现明显的季节差异。③年际变化规律为2016年后水域面积呈增长趋势,其中2017-2019年水域面积相对稳定且缓慢增长,2020年面积急剧增长。分段而言,水域面积随时间的变化幅度为下游>中游>上游,中上游变化相对平稳,下游较显著。④易发生洪涝的断面主要分布在中下游段,需引起重视并做好监测预警。     

Remote estimation of water quality parameters of Himalayan lake (Kashmir) using Landsat 8 OLI imagery

The overarching aim of this study was to derive simple and accurate algorithms for the retrieval of water quality parameters for the Wular Lake using Landsat 8 OLI satellite data. The water quality parameters include pH, COD, DO, alkalinity, hardness, chloride, TDS, total suspended solids (TSS), turbidity, electric conductivity and phosphate. Regression analysis was performed using atmospherically corrected true reflectance values of original OLI bands, images after applying enhancement techniques (NDVI, principal components) and the values of the water quality parameters at different sample locations to obtain the empirical relationship. Most of the parameters were well correlated with single OLI bands with R² greater than 0.5, whereas phosphate showed a good correlation with NDVI image. The parameters like pH and DO showed a good relation with the principal component I and IV, respectively. The high concentration of pH, COD, turbidity and TSS and low concentration of DO infers the anthropogenic impact on lake.     

Use of multitemporal remote sensing data for mapping the Alfios River network changes from 1977 to 2000

Alfios is the biggest river of the Peloponnese and the ninth longest river in Greece. It drains an area of almost 2575 km² in Western Peloponnese and discharges at Kiparissiakos Gulf. Due to its extent, the Alfios basin presents complex physiography and geomorphology.

During the last 50 years, major direct human activities have had an important impact on the river network shape and on the valley floor morphology. The most important human activities were the channel straightening caused by meander cut-offs in 1950, the construction of two dams: the Ladonas dam in 1955 and the Flokas dam in 1968 and the illegal in-stream gravel extraction that started in the 1960s and continues until today. As a result, the Alfios riverbed has presented very rapid vertical and horizontal (lateral) erosion and significant changes to its network shape. The drainage network follows a straighter course, the number of meanders has been reduced and the seventh order branch is deeply incised. Besides the morphological impacts to the river network shape there are also serious economic damages caused by human activity. During the winter of 1999, the Flokas dam bridge was closed for a long period due to damages at its foundation caused by the heavy rain and illegal gravel extraction. Transportation between the villages in the area became extremely difficult and time consuming and the cost of the repairs was estimated at 500 000 euros. In this study, there is an effort to map the network shape transformation for the period 1977–2000 using multitemporal and multisensor satellite images. One Landsat MSS image, three Landsat TM images, two Landsat ETM images, and one Terra ASTER image have been orthorectified and processed in order to cover the specific period. Principal Component Analysis (PCA) method and Geographical Information System (GIS) techniques have been applied to map the changes in the Alfios River channel. The drainage network straightening and the cut-off of five big meanders were detected and mapped. These changes occurred between 1986 and 2000.