基于卫星影像的太湖蓝藻水华遥感强度指数和等级划分算法设计

对太湖地区近10余年来共32景Landsat TM/ETM遥感影像进行大气校正处理,获得地表反射率影像,在这些影像上采集了分布在不同片区、不同发生季节、不同集聚程度的蓝藻水华样区,提取了不同蓝藻水华的可见一近红外波段反射率数据.统计表明蓝藻水华在TM 4波段的反射率有较宽的动态范围,能定量反映蓝藻集聚程度,TM 2也是...     

基于欧洲航天局“哨兵-2A”卫星的太湖蓝藻遥感监测

欧洲航天局(ESA)2015年6月23日成功发射"哨兵-2A"卫星,该卫星搭载的多光谱成像仪(MSI)在可见光(VIS)至短波红外(SWIR)波长区间配置了多种光谱波段/地面分辨率组合,可以获取大范围、较短重访周期、较高空间分辨率(10 m)的遥感影像。以太湖2016年6月13日MSI数据为例,在完成大气校正的基础上,分析了太湖典型地物类型光谱特征,采用归一化植被指数(NDVI)结合叶绿素反射峰强度(ρchl)构建的综合阈值法对贡湖湾的蓝藻水华信息进行了提取实验。结果表明:"哨兵-2A"卫星MSI影像质量清晰,可精细地反映植被、蓝藻、水体等典型地物类型的光谱特征;ρchl指数对中-高蓝藻聚集区与水生植被、轻度蓝藻聚集区与混合水体具有较好的分离能力;利用综合阈值法提取贡湖湾中-高蓝藻聚集区面积为60.37 km2,主要分布在贡湖北部沿岸、湖心和南部沿岸。"藻-水"混悬体面积为79.49 km2,贡湖湾东部蓝藻水华相对较轻。     

基于“哨兵-3A”OLCI影像的太湖蓝藻水华荧光基线高度指数信号特征分析

利用新型遥感数据"哨兵-3A"卫星OLCI影像数据,基于其665,681和708 nm波段构建的"荧光基线高度"指数算法,采用SNAP 6.0遥感专业软件,计算了2017年不同季节4个典型日期太湖FLH的全湖分布及蓝藻水华区信号强度特征。以完成了瑞利散射及气体吸收订正的3个波段的遥感反射率数据计算FLH图像,结果表明,FLH数值的"负偏"程度与蓝藻水华强度有很好的对应关系,FLH值"负偏"越大,蓝藻水华越严重,可以作为比较不同季节水华强度的有效遥感指标;富营养化较严重、较为浑浊、以蓝藻为优势种的内陆水体与大洋清洁、非蓝藻优势浮游植物水体的FLH"正偏"信号特征迥异。     

"哨兵-3"卫星OLCI影像MPH算法反演太湖叶绿素a及藻草区分的研究

利用"哨兵-3"卫星OLCI影像数据,基于其619,665,681,709,753和885 nm中心波长对应的6个波段构建的最大特征峰高度(MPH)算法,采用SNAP 7. 0遥感专业软件,计算了典型日期太湖MPH算法得到的叶绿素a浓度、浮藻区、藻水混悬区、水草区的分布。结果表明:(1) MPH算法能够精确地识别太湖水草和蓝藻;(2) MPH算法能够提取稠密铺集水表层的"浮藻区",并区分出藻密度较小、水华现象轻微～轻度、蓝藻主要浸没在水面以下的"藻水混悬区"。与MODIS、VIIRS等常用的蓝藻水华遥感传感器相比,OLCI展现了更出色、更精细化的水生态遥感监测能力,可提高蓝藻水华预警预报水平。     

巢湖蓝藻水华遥感监测初探

以巢湖为研究区,从2008年4月到11月,对巢湖水体的24个点位进行了连续的水体光谱测量,通过对蓝藻水华爆发程度与其光谱反射率之间关系的研究,确定遥感识别水华爆发级别的阈值,对四类不同爆发程度蓝藻水华光谱特征进行遥感识别,绘制巢湖蓝藻水华特征等级图。     

巢湖富营养化遥感监测

以巢湖为研究区,通过对蓝藻水华暴发程度与其光谱反射率之间关系的研究,确定MOD IS遥感影像识别水华暴发级别的阈值,对4类不同暴发程度蓝藻水华光谱特征进行遥感识别;进而确立巢湖水体富营养化评价方法,建立巢湖富营养化遥感反演模型,为实时监控巢湖水质,预警蓝藻水华暴发提供技术支持。     

太湖湖泛现象的卫星遥感监测

2010年8月20日太湖地区Landsat ETM影像显示,太湖西部沿岸带存在湖泛黑水团现象,对该景遥感影像进行了大气校正,提取了湖泛样区、其他水体样区的ETM各波段光谱反射率数据统计特征。结果表明,湖泛样区在可见光波长的ETM波段1、2、3具有很低的反射率,水色暗黑,与人眼观察一致,而在反射红外波长的ETM波段4则有比波段3高的反射率,差异植被指数DVI>0,其原因为湖泛黑水团中,虽然大量蓝藻死亡分解,然而水中还残留有一定数量的活体蓝藻,残余叶绿素及细胞造成了虽然较弱、但仍较为稳定的反射红外波长处的光谱反射能力。提出了识别湖泛现象的遥感判据为ρ0.485<0.05 andρ0.56<0.08 andρ0.66<0.065 and(ρ0.83-ρ0.66)>0 andρ0.83<0.1。     

太湖蓝藻水华时空分布与预警监测响应的分析

选择2007和2008年200幅EOS/MODIS太湖蓝藻监测遥感影像,统计分析了梅梁湾、竺山湾宜兴段、贡湖湾、东太湖胥口湾和湖州方向湖体蓝藻水华爆发的空间和时间分布规律。并在得出全太湖蓝藻水华空间和时间分布规律的基础上,从环境监测部门蓝藻预警监测工作的实际出发,将蓝藻水华预警监测的响应划分为常规监测和应急监测,提出了具体的监测要求,为环太湖地区的相关部门更好地开展蓝藻预警监测工作提供了科学依据。     

太湖蓝藻水华预警监测综合系统的构建

近年来随着浅水型湖泊的富营养化进程不断加快,蓝藻水华暴发现象也频繁出现,采用科学、全面的手段对太湖蓝藻暴发进行预警十分必要。根据太湖蓝藻预警监测中使用的现场巡视、卫星遥感、实验室分析、自动监测等监测技术手段,分别建立各自监测系统,结合各监测系统特点和相互关系,对太湖蓝藻水华预警监测综合系统的构建进行了探讨,以期能够更好地开展太湖蓝藻水华预警监测工作,为确保太湖地区饮用水安全,提高环保部门应对太湖蓝藻水华暴发的能力,为政府决策提供技术支持和保障。     

基于哨兵-3A卫星OLCI数据的最大叶绿素指数在太湖蓝藻水华监测中的应用

欧洲航天局于2016年2月16日成功发射哨兵-3A卫星,搭载的水色遥感仪器(OLCI)提供了很好的海洋和内陆水体生态指标观测反演能力。基于OLCI获取的太湖L1b级遥感数据产品,利用OLCI Oa10、Oa11、Oa12波段计算了重要的水色/水生态遥感指标,即最大叶绿素指数(MCI),在此基础上初步分析了MCI在太湖蓝藻水华监测预警中应用效果。研究表明:(1)哨兵-3A卫星OLCI影像质量清晰,构建的MCI能够反映太湖水体叶绿素信号强度;(2)与常用的归一化植被指数相比,在蓝藻没有明显积聚的藻-水混悬水域,MCI与叶绿素浓度有很好的关联,可更灵敏地反映叶绿素浓度的空间分布特征。MCI将在蓝藻监测上具有更好的适用性,可有效提高富营养湖泊蓝藻水华的预警预报精度。     

空间关联随机森林模型结合Sentinel-2影像估算潍北地区裸土期土壤盐分

土壤盐分含量(SSC)是评价土地退化和肥力水平的重要指标，实现SSC状态和空间分异的快速准确监测对区域环境的优化管理极为关键。选取潍北平原为研究区，野外采集233处土壤样品并获取同时相Sentinel-2多光谱影像，进一步将特征光谱波段和构建的最优光谱指数作为输入自变量，测试得到的SSC实测值为因变量，最后将空间关联函数引入到随机森林中去建立基于空间关联随机森林算法的SSC遥感估算模型，完成区域尺度上的SSC反演估算与空间制图。结果表明：影像的B3、B8和B11是SSC的特征波段，通过波段比值变换能够增强卫星光谱信号对SSC的吸收响应，筛选得到的最优光谱指数分别为RI₃₄(波段3和波段4的反射率比值)、RI₇₁₁(波段7和波段11的反射率比值)、ND₆₁₁(波段6和波段11的反射率归一化值)和D₄₅(波段4和波段5的反射率差值);仅用特征波段或最优光谱指数来构建模型不能取得满意的SSC估算精度，空间关联随机森林模型的SSC估算精度要高于随机森林模型；在将上述特征波段和最优光谱指数共同输入空间关联随机...     

Comparison of remote sensing change detection techniques for assessing hurricane damage to forests

This study compared performance of four change detection algorithms with six vegetation indices derived from pre- and post-Katrina Landsat Thematic Mapper (TM) imagery and a composite of the TM bands 4, 5, and 3 in order to select an optimal remote sensing technique for identifying forestlands disturbed by Hurricane Katrina. The algorithms included univariate image differencing (UID), selective principal component analysis (PCA), change vector analysis (CVA), and postclassification comparison (PCC). The indices consisted of near-infrared to red ratios, normalized difference vegetation index, Tasseled Cap index of greenness, brightness, and wetness (TCW), and soil-adjusted vegetation index. In addition to the satellite imagery, the “ground truth” data of forest damage were also collected through field investigation and interpretation of post-Katrina aerial photos. Disturbed forests were identified by classifying the composite and the continuous change imagery with the supervised classification method. Results showed that the change detection techniques exerted apparent influence on detection results with an overall accuracy varying between 51% and 86% and a kappa statistics ranging from 0.02 to 0.72. Detected areas of disturbed forestlands were noticeable in two groups: 180,832–264,617 and 85,861–124,205 ha. The landscape of disturbed forests also displayed two unique patterns, depending upon the area group. The PCC algorithm along with the composite image contributed the highest accuracy and lowest error (0.5%) in estimating areas of disturbed forestlands. Both UID and CVA performed similarly, but caution should be taken when using selective PCA in detecting hurricane disturbance to forests. Among the six indices, TCW outperformed the other indices owing to its maximum sensitivity to forest modification. This study suggested that compared with the detection algorithms, proper selection of vegetation indices was more critical for obtaining satisfactory results.     

联合多源光学和雷达遥感的巢湖水华长时序时空变化分析

以巢湖水华爆发现象为研究对象,利用多源光学遥感和全极化SAR遥感作为数据源,对研究区域2008—2017年的水华进行识别提取,定量和定性分析水华面积及区域位置的时空变化。结果表明:在时间上,每年二、三季度巢湖水华面积普遍高于一、四季度,总体上呈现年平均水华面积逐渐减小趋势,前五年的水华面积比后五年高。在空间上,巢湖西北部水华发生频率最高,西部水华比东部水华发生频率高,沿岸比湖中心发生频率高。巢湖水华整体呈现改善趋势。     

Research on the relationship between the fractional coverage of the submerged plant Vallisneria spiralis and observed spectral parameters

The present paper discusses the relationship between the coverage fraction of submerged plants and the observed spectral characteristics. The purpose of this paper is to validate a remote sensing technology to monitor the change in the plant composition of a water body. In the current study, the reflectance spectra of the submerged plant Vallisneria spiralis at different fraction coverages of the wetland in Hangzhou Bay were measured. The relationships between the fraction coverage of V. spiralis and simulated Quickbird normalized difference vegetation index (NDVI), red edge, and other spectral characteristic parameters were established. The results showed that the spectral reflectance characteristics of submerged plant V. spiralis were mainly in the visible light (490–650 nm) and near infrared (700–900 nm). The rate of change of the blue band curve and simulated Quickbird NDVI showed a higher correlation with the V. spiralis coverage, so estimation models of the fraction coverage were constructed using these parameters. The estimated fraction coverage of V. spiralis with different models were validated with ground data, and the accuracy of estimation models was assessed. The most suitable estimated fraction coverage of V. spiralis was obtained using the rate of change of the blue band curve and simulated Quickbird NDVI. The present work demonstrated a method to monitor the distribution and dynamical variation of submerged plants at the large scale.     

Predictions of soil organic carbon using laboratory-based hyperspectral data in the northern Tianshan mountains, China

This paper presents a study dealing with soil organic carbon (SOC) estimation of soil through the combination of soil spectroscopy and multivariate stepwise linear regression. Soil samples were collected in the three sub-regions, dominated by brown calcic soil, in the northern Tianshan Mountains, China. Spectral measurements for all soil samples were performed in a controlled laboratory environment by a portable ASD FieldSpec FR spectrometer (350–2,500 nm). Twelve types of transformations were applied to the soil reflectance to remove the noise and to linearize the correlation between reflectance and SOC content. Based on the spectral reflectance and its derivatives, hyperspectral models can be built using correlation analysis and multivariable statistical methods. The results show that the main response range of soil organic carbon is between 400 and 750 nm. Correlation analysis indicated that SOC has stronger correlation with the second derivative than with the original reflectance and other transformations data. The two models developed with laboratory spectra gave good predictions of SOC, with root mean square error (RMSE) <5.0. The use of the full visible near-infrared spectral range gave better SOC predictions than using visible separately. The multivariate stepwise linear regression of second derivate model (model A) is optimal for estimating SOC content, with a determination coefficient of 0.894 and RMSE of 0.322. The results of this research study indicated that, for the grassland regions, combining soil spectroscopy and mathematical statistical methods does favor accurate prediction of SOC.     

The terrain signatures of administrative units: a tool for environmental assessment

The quantification of knowledge related to the terrain and the landuse/landcover of administrative units in Southern Greece (Peloponnesus) is performed from the CGIAR-CSI SRTM digital elevation model and the CORINE landuse/landcover database. Each administrative unit is parametrically represented by a set of attributes related to its relief. Administrative units are classified on the basis of K-means cluster analysis in an attempt to see how they are organized into groups and cluster derived geometric signatures are defined. Finally each cluster is parametrically represented on the basis of the occurrence of the Corine landuse/landcover classes included and thus, landcover signatures are derived. The geometric and the landuse/landcover signatures revealed a terrain dependent landuse/landcover organization that was used in the assessment of the forest fires impact at moderate resolution scale.