Delineation of riparian vegetation from Landsat multi‐temporal imagery using PCA

A deficiency in crucial digital data, such as vegetation cover, in remote regions is a challenging issue for water management and planning, especially for areas undergoing rapid development, such as mining in the Pilbara, Western Australia. This is particularly relevant to riparian vegetation, which provides important ecological services and, as such, requires regional protection. The objective of this research was to develop an approach to riparian vegetation mapping at a regional scale using remotely sensed data. The proposed method was based on principal component analysis applied to multi‐temporal Normalized Difference Vegetation Index datasets derived from Landsat TM 5 imagery. To delimit the spatial extent of riparian vegetation, a thresholding method was required and various thresholding algorithms were tested. The accuracy of results was estimated for various Normalized Difference Vegetation Index multi‐temporal datasets using available ground‐truth data. The combination of a 14‐dry‐date dataset and Kittler's thresholding method provided the most accurate delineation of riparian vegetation.     

Inter‐annual changes of alpine inland lake water storage on the Tibetan Plateau: Detection and analysis by integrating satellite altimetry and optical imagery

The effects of climate change have a substantial influence on the extremely vulnerable hydrologic environment of the Tibetan Plateau. The estimation of alpine inland lake water storage variations is essential to modeling the alpine hydrologic process and evaluating water resources. Due to a lack of historical hydrologic observations in this remote and inaccessible region, such estimations also fill a gap in studies on the continuous inter‐annual and seasonal changes in the inland lake water budget. Using Lake Siling Co as a case study, we derived a time‐series of lake surface extents from MODIS imagery, and scarce lake water level data from the satellite altimetry of two sensors (ICESat/GLAS and ENVISAT RA‐2) between 2001 and 2011. Then, based on the fact that the rise in lake water levels is tightly dependent on the expansion of the lake extent, we established an empirical model to simulate a continuous lake water level dataset corresponding to the lake area data during the lake's unfreezing period. Consequently, from three dimensions, the lake surface area, water level and water storage variations consistently revealed that Lake Siling Co exhibited a dramatic trend to expand, particularly from 2001 to 2006. Based on the statistical model and lake area measurements from Landsat images since 1972, the extrapolated lake water level and water storage indicate that the lake has maintained a continual expansion process and that the cumulative water storage variations during 1999–2011 account for 66.84% of the total lake water budget (26.87 km³) from 1972 to 2011. Copyright © 2013 John Wiley & Sons, Ltd.     

Removing sun glint from optical remote sensing images of shallow rivers

Sun glint is the specular reflection of light from the water surface, which often causes unusually bright pixel values that can dominate fluvial remote sensing imagery and obscure the water‐leaving radiance signal of interest for mapping bathymetry, bottom type, or water column optical characteristics. Although sun glint is ubiquitous in fluvial remote sensing imagery, river‐specific methods for removing sun glint are not yet available. We show that existing sun glint‐removal methods developed for multispectral images of marine shallow water environments over‐correct shallow portions of fluvial remote sensing imagery resulting in regions of unreliable data along channel margins. We build on existing marine glint‐removal methods to develop a river‐specific technique that removes sun glint from shallow areas of the channel without over‐correction by accounting for non‐negligible water‐leaving near‐infrared radiance. This new sun glint‐removal method can improve the accuracy of spectrally‐based depth retrieval in cases where sun glint dominates the at‐sensor radiance. For an example image of the gravel‐bed Snake River, Wyoming, USA, observed‐versus‐predicted R² values for depth retrieval improved from 0.66 to 0.76 following sun glint removal. The methodology presented here is straightforward to implement and could be incorporated into image processing workflows for multispectral images that include a near‐infrared band. Copyright © 2016 John Wiley & Sons, Ltd.     

Estimation of water clarity in Taihu Lake and surrounding rivers using Landsat imagery

In China, the increase in exogenous-source pollutants from rivers is one of the most important causes of lake eutrophication. The application of remote sensing technology to water quality monitoring of rivers connected to these lakes has special significance for lake management at regional scales. Many research studies have estimated water clarity using Landsat imagery. However, most of this work focused on lakes or reservoirs, for which abundant water-only pixels (i.e., pure pixels of water, PPW) were available. Few of these studies have addressed rivers, especially rivers with an average width less than 100 m. In our study, we sought to determine whether water clarity in the rivers connected to Taihu Lake could be estimated using Landsat imagery. We obtained 18 Enhanced Thematic Mapper Plus (ETM+) images from 2009 for 13 rivers ranging from an average of 37.3 to 173.6 m wide. Three field campaigns conducted in May 2009, September 2009, and January 2010 were used to obtain field measurements of Secchi disk depth (SDD). Our results suggested that the widely used model, a(TM1/TM3) + b(TM1) + c, was suitable for the estimation of SDD for Taihu Lake. The brightness of the panchromatic band of ETM+ showed significant correlations with TM1, TM3 and TM1/TM3 (p < 0.001). As a result, SDD in the lake could also be estimated using the Landsat panchromatic band. The multispectral image of ETM+ did not provide adequate PPW for estimation of water clarity in rivers. However, PPW derived from the panchromatic image captured about 93% of the variation in SDD, on average, for the every worst-case scenario in the 13 rivers. Using the PPW in rivers, a significant correlation was found between the brightness of the panchromatic image and SDD (R² = 0.64, p < 0.001). Our results demonstrate that the panchromatic image of Landsat, but not the multispectral image, can be used to estimate water clarity in rivers with an average width greater than 40 m in the Taihu basin.     

1994-2018年松嫩平原西部月亮泡水淹区生态变化及其对水淹频次的响应

半干旱内陆地区的湖泊湿地是一种特殊的生态系统,季节和年际时间尺度上的湖泊水文变化对湖泊湿地生态结构和功能有着重要影响.近20年来,月亮泡湖泊湿地经历了自然和人为因素共同作用下的水文波动过程.为了实现大尺度地表生态年内/年际变化检测,更好地了解湖泊年际水淹范围及其水淹频次对内陆湖滨湿地生态的影响,基于1994—2018年Landsat TM/OLI影像数据(30 m),首先,计算提取月亮泡的年际水体信息和水淹频次,进而获取湖泊年际淹没范围.其次,采用综合生态指数变化检测法提取生态信息,选取3个标准观测年(1995、2006、2016年),从年内变化和年际变化视角分级评价了研究区生态变化,并分析了水淹频次与湿地生态变化的关系.最终,现有研究表明:湖泊年际水淹区主要分布在月亮泡的北侧与西侧尾闾,月亮泡湖泊湿地北侧的年际水淹频次更为显著.湖泊面积的扩展与自然湿地的减少是月亮泡水淹区域的主要变化类型.在这种变化情况下,研究区水体指数累积量的增加与植被指数累积量的衰减成为显著的生态变化特点.月亮泡湖泊年际水淹频次在一定时间和空间上影响着水淹区域的植被生产能力,水淹的低频波动是研究区植被累积量增加的关键因子.因此,在湿地生态恢复与管理过程中,维持合理的水文波动,恢复月亮泡北侧与西侧沼泽湿地是该区域内生态保护的核心措施.     

考虑采砂影响的鄱阳湖丰水期悬浮泥沙浓度模拟

针对受采砂活动影响显著的鄱阳湖高浑浊水体,结合数值模拟和遥感技术,利用已有的鄱阳湖采砂区遥感监测结果,在构建的鄱阳湖水动力-悬浮泥沙输移模型中添加泥沙点源,对2011年7月1-31日采砂影响下的鄱阳湖丰水期悬浮泥沙浓度进行数值模拟.利用悬浮泥沙浓度实测数据和MODIS影像反演结果对模拟结果的有效验证表明,考虑采砂影响后,悬浮泥沙浓度模拟值与实测值具有强相关关系,确定性系数为0.831,均方根误差为15.5 mg/L,悬浮泥沙浓度空间分布趋势与遥感反演结果基本一致.模拟结果显示,采砂活动对鄱阳湖南部主湖区、河流入湖口影响较小,其主要影响由南向北,经棠荫以西和松门山岛以北航道、入江水道延伸到湖口区域,是鄱阳湖北湖区高浑浊水体形成的重要原因.     

基于色度角的岱海水体营养状态遥感评估

湖泊富营养化已经成为水资源领域的研究焦点,是水环境领域面临的长期严峻挑战.为探明干旱半干旱区域湖泊营养状态,以典型岱海水体为例,利用2019—2020年6次野外实测数据为基础,针对Sentinel_2A和Landsat_8 OLI遥感数据,基于营养状态指数TSI_SDD与色度角之间的相关关系,建立了岱海水体营养状态评估模型,并利用1986—2020年遥感影像数据,得到了长时间序列的水体营养状态.结果表明:(1)本文建立的营养状态评估模型,根据精度检验结果显示模型精度较好,决定系数(R²)为0.74,均方根误差(RMSE)为3.66,平均绝对百分比误差(MAPE)为4.84%.(2)将算法应用到时间序列MSI、TM、ETM+和OLI数据,得到了岱海水体1986—2020年的营养状态动态特征.结果表明,岱海水体面积逐年减少,且多数时间处在轻度富营养化状态.水体富营养化现象大体上从边缘逐渐向湖中心趋于缓和,离岸边越近富营养化现象越严重,通常趋向湖中心以中营养为主,整体上贫营养化现象极少.(3)岱海营养状态时空变化与气温、风速和降水量等气候因子的相关性并不显著,对其解释率为13%.气候因子对营养状态的月变化影响显著,对其解释率为93%.     

Retrieval of suspended sediment concentrations in large turbid rivers using Landsat ETM+: an example from the Yangtze River,China

Suspended sediment concentration (SSC) is a critical parameter in the study of river sediment transport and water quality variation, but traditional measurement methods are costly and time‐consuming. This paper is focused on presenting a methodology that may be useful in estimating SSC which is of key importance in process geomorphology and hydrology. In previous studies, remote sensing has been applied to estimate the SSC of sea waters as well as low turbid inland waters like lakes, reservoirs and short river reaches visible within a single Landsat satellite image coverage. Rivers, especially highly turbid large rivers, have largely been ignored. The dataset used in this paper includes measured SSC and multi‐temporal Landsat ETM+ images covering most part of the Yangtze River. Using an effective easy‐to‐use atmospheric correction method that does not require in situ atmospheric conditions, retrieved water reflectance of Band 4 was found to be a good SSC indicator within the large SSC range 22–2610 mg l^–1. The newly developed regression relation between SSC and water reflectance of Band 4 appears to be able to provide a relatively accurate SSC estimate directly from Landsat ETM+ images for the Yangtze River from the upper, the middle to the lower reaches. With the relation it is possible to estimate or map out SSC dynamics of large rivers which lack SSC data due to constraints of conventional measurements. Copyright © 2009 John Wiley & Sons, Ltd.     

环境一号卫星高光谱遥感数据的内陆水质监测适宜性——以巢湖为例

环境一号星座的A星(HJ-1A)上搭载了超光谱成像仪(HSI),它是具有高光谱分辨率的全新国产遥感数据源,为水质遥感特别是内陆水质遥感提供了新的高光谱数据.但HSI影像的处理方法尚不完善,在广泛应用于水质遥感前对其进行质量研究和评价非常必要.本文针对HSI数据在巢湖水质监测应用方面的适宜性,对信噪比和数据真实性、倾斜条...     

基于Landsat 8 OLI影像反演的湖北大冶湖水体光学衰减特性

水体光学衰减特性直接影响湖泊的清澈程度和沉水植被的生存,利用遥感技术获取湖泊光学衰减分布特性能极大提高效率.基于2017-2019年的原位调查数据,利用Landsat 8 OLI影像开发了大冶湖水体光学衰减系数(Kd)的遥感反演模型,并分析大冶湖水体Kd的多年时空分布特性与驱动机制,以期为大冶湖流域的修复与管理提供参考...     

Modelling the bulk flow of a bedrock‐constrained,multi‐channel reach of the Mekong River,Siphandone, southern Laos

The general nature of bulk flow within bedrock single‐channel reaches has been considered by several studies recently. However, the flow structure of a bedrock‐constrained, large river with a multiple channel network has not been investigated previously. The multiple channel network of the Siphandone wetlands in Laos, a section of the Mekong River, was modelled using a steady one‐dimensional hydraulic model. The river network is characterized by a spatially‐varying channel‐form leading to significant changes in the bulk flow properties between and along the channels. The challenge to model the bulk flow in such a remote region was the lack of ideal boundary conditions. The flow models considered both low flow, high inbank and overbank flows and were calibrated using SPOT satellite sensor imagery and limited field data concerning water levels. The application of the model highlighted flow characteristics of a large multi‐channel network and also further indicated the field data that would be required to properly characterize the flow field empirically. Important results included the observation that adjacent channels within the network had different water surface slopes for the same moments in time; thus calibration data for modelling similar systems needs to account for these significant local differences. Further, the in‐channel hydraulic roughness coefficient strongly varied from one cross‐section to the next (Manning's ‘n’ range: 0·01 to 0·10). These differences were amplified during low flow but persisted in muted form during high discharges. Copyright © 2012 John Wiley & Sons, Ltd.     

基于长时间序列(1975—2020年)生态耗水的岱海动态生态需水分析

生态需水是湖泊生态系统的重要指标,维持着湖泊生态系统的良性循环.以内蒙古中部半干旱湖泊岱海为研究对象,对湖泊动态生态需水进行分析.本研究在遥感和气象数据的基础上,获得1975-2020年长时间序列高精度水文要素数据,分析岱海水文要素时空演变规律;通过天然生态水深分析法、水深经验频率分析法和湖泊形态分析法分析岱海的水深随面积变化的关键水深;构建基于生态耗水规律的湖泊生态需水模型,计算自然状态下岱海生态需水动态变化范围.研究结果如下:岱海地区6-9月为丰水期,10月至次年5月为枯水期;45 a以来岱海水面面积呈显著下降趋势,近年来下降速率减缓;枯水期岱海适宜生态水深为8.72~9.92 m,丰水期为9.40~10.69 m,适宜生态需水量为5.62亿~7.71亿m³,适宜湖面面积为70.92~84.77 km².本文构建了长时间序列气候水文数据库,确定岱海动态生态需水范围可以实现对湖泊生态健康的实时监测,为相关规划与管理提供科学依据及可操作性指导,从而为岱海湖泊治理提供理论参考.     

Development and application of a remote sensing-based salinity prediction model for a large estuarine lake in the US Gulf of Mexico coast

Salinity in estuaries is highly variable due to river discharge, tidal motion, and winds. Information on the spatial and temporal changes in salinity can provide important ecological indications, but accurate monitoring of the space–time variability for a large estuary is often costly and time-consuming. This study applied remote sensing techniques to develop a salinity prediction model for Lake Pontchartrain, a large estuarine lake located in the Northern Gulf of Mexico, USA. “Ground truth” salinity was measured along two transects across the lake and near the shoreline. Water-leaving reflectance from the measurement locations was extracted from Landsat Thematic Mapper (TM) images pre-processed through “banding” noise reduction and radiometrical correction approaches. Ordinary least square and ridge regression methods were performed to identify model parameters and to determine relationships between salinity and reflectance. Salinity in the lake on eight dates was predicted with the developed model. Difference in salinity level and patterns, and impacts of Hurricanes Katrina and Rita on salinity were assessed with ANOVA and Fuzzy Similarity methods. The results showed that the model achieved a high power in prediction of the lake salinity (R² = 0.89 and RMSE of validation = 0.27). Reflectance from TM bands 1, 2, and 4 was positively correlated to salinity levels and explained 1.9%, 20.3%, and 10.2% variance in salinity levels. Reflectance from bands 3 and 5 was negatively correlated to salinity and explained 34.1% and 31.2% variance. Under normal circumstances without the impacts of hurricanes, the lake salinity presented two patterns with average salinity level of 5.5 ppt. After Katrina’s landfall, the average was significantly increased by 1.1 ppt and the spatial patterns were altered. The pattern on 30 August 2005 was the most dissimilar one as compared to the two normal patterns, and then followed by the patterns on 9 and 25 October, and 7 September 2005. This study demonstrated that satellite remote sensing techniques can be applied to monitor salinity in coastal environments, and that freshwater discharge not only affects salinity levels and patterns under normal conditions but also is crucial for the return of salinity patterns to normal conditions after hurricane disturbance.     

Daily discharge estimation at ungauged river sites using remote sensing

A methodology is developed to estimate daily river discharge at an ungauged site using remote sensing data. Use is made of ERS‐2 and ENVISAT satellite altimetry to provide a time series of river channel stage levels and longitudinal channel slope and Landsat satellite imagery to provide a range of channel widths over a 50 km reach of river. The data are substituted into the Bjerklie et al. ( 2003 ) equation, which is based on the Manning's resistance equation and has been developed using a global database of channel hydraulic information and discharge measurements. Our methodology has been applied at three locations on the Mekong and Ob Rivers and validated against daily in situ discharge measurements. The results show Nash–Sutcliffe efficiency values of 0.90 at Nakhon Phanom and 0.86 at Vientiane on the Mekong, and 0.86 at Kalpashevo on the Ob. Copyright © 2012 John Wiley & Sons, Ltd.     

基于Landsat TM/ETM+数据提取巢湖悬浮泥沙相对浓度的信息与空间分布变化

悬浮泥沙是重要的水质参数之一.应用遥感技术监测悬浮泥沙,学者们提出了众多的悬浮泥沙遥感的经验模型和推导模型.但在缺乏大气参数或没有足够实测数据的情况下,这些模式的精度和准确性得不到保证.针对这种情况,以巢湖为实验区,对三景的巢湖卫星遥感数据进行了如下的数据处理:(1)利用内部平均相对反射率法进行图像的大气校正,得到的相对反射率与真实反射率具有相似的波谱特征;(2)对图像进行了水体提取、二值化、掩膜处理,并通过湖泊泥沙指数SI=(TM2 TM3)/(TM2/TM3)提取了TM数据下的泥沙信息,得到水体含沙量图;(3)按照本文提出的基于遥感图像的不同浓度等级泥沙的划分依据,在泥沙指数图上进行密度分割处理,得到了巢湖泥沙相对浓度分布图.在上述的处理基础上,利用谱间关系法对巢湖水体进行准确提取;结果表明,与实测资料对比,巢湖泥沙相对浓度分布与验证数据一致,实测数据和SI值相关系数为0.89(置信度水平在0.001),表明泥沙指数方法可以直观和定量地反映悬浮泥沙相对浓度的分布与变化;研究结果显示,1987-2000年间,巢湖高浓度悬浮泥沙范围增大了约1.5倍.通过影像差值图清楚地识别出变化区域,主要位于西湖的中心、河口入湖区和东湖的南岸,这种变化的最主要原因是由于各入湖河流携带的大量悬浮泥沙进入水体,其次是岸坡崩塌物形成的.     

Extreme flood‐driven fluvial bank erosion and sediment loads: direct process measurements using integrated Mobile Laser Scanning (MLS) and hydro‐acoustic techniques

This methods paper details the first attempt at monitoring bank erosion, flow and suspended sediment at a site during flooding on the Mekong River induced by the passage of tropical cyclones. We deployed integrated mobile laser scanning (MLS) and multibeam echo sounding (MBES), alongside acoustic Doppler current profiling (aDcp), to directly measure changes in river bank and bed at high (~0.05 m) spatial resolution, in conjunction with measurements of flow and suspended sediment dynamics. We outline the methodological steps used to collect and process this complex point cloud data, and detail the procedures used to process and calibrate the aDcp flow and sediment flux data. A comparison with conventional remote sensing methods of estimating bank erosion, using aerial images and Landsat imagery, reveals that traditional techniques are error prone at the high temporal resolutions required to quantify the patterns and volumes of bank erosion induced by the passage of individual flood events. Our analysis reveals the importance of cyclone‐driven flood events in causing high rates of erosion and suspended sediment transport, with a c. twofold increase in bank erosion volumes and a fourfold increase in suspended sediment volumes in the cyclone‐affected wet season. Copyright © 2016 John Wiley & Sons, Ltd.     

A review of low‐cost space‐borne data for flood modelling: topography,flood extent and water level

During the last two decades, remote sensing data have led to tremendous progress in advancing flood inundation modelling. In particular, low‐cost space‐borne data can be invaluable for large‐scale flood studies in data‐scarce areas. Various satellite products yield valuable information such as land surface elevation, flood extent and water level, which could potentially contribute to various flood studies. An increasing number of research studies have been dedicated to exploring those low‐cost data towards building, calibration and evaluation, and remote‐sensed information assimilation into hydraulic models. This paper aims at reviewing these recent scientific efforts on the integration of low‐cost space‐borne remote sensing data with flood modelling. Potentials and limitations of those data in flood modelling are discussed. This paper also introduces the future satellite missions and anticipates their likely impacts in flood modelling. Copyright © 2015 John Wiley & Sons, Ltd.     

2000-2010年东北地区湖泊动态变化及驱动力分析

以2000、2005和2010年的Landsat TM和ETM遥感影像为主要数据源,利用面向对象的分类方法,提取3期东北地区湖泊数据;在GIS技术的支持下,分析了过去10年东北地区湖泊的时空变化特征,并对导致湖泊面积变化的自然和人文驱动因素进行分析.结果表明:2000-2010年间,东北地区湖泊面积由12234.02 km²减少至11307.58 km²,其中,2005-2010年间湖泊萎缩剧烈程度大于2000-2005年;湖泊数量先增加后减少,10年间共减少了4092个;10年间天然湖泊面积大幅减少,人工湖泊面积略增加;研究区内西北方向湖泊萎缩程度小于东南方向,质心向西北偏移;湖泊变化受自然因素和人类活动的共同影响,人类活动叠加在自然因素之上,对湖泊变化产生了放大作用.     

近40年来南四湖湿地NDVI变化特征及其控制因子分析

利用Landsat系列卫星的MSS、TM和ETM+遥感数据,计算了研究区的归一化植被指数(NDVI),并以此为湿地植被活动的指标,研究1973 2011年间该湿地植被变化特征及年内季节变化特征,揭示植被活动在年内和年际变化的控制因子以及湿地植被对于气候变化、人类活动和极端干旱事件的响应特征.结果表明:(1)近40年来南四湖湿地植被各个季节的变化特征不尽相同.春季NDVI呈现先降低后增加的特征,主要先后受到研究区围垦、渔业养殖等人为活动和气候变化(增温)的影响;夏季和冬季的NDVI呈现显著降低趋势,主要受到围垦、渔业养殖等人类活动的影响;秋季NDVI的变化不显著.(2)年内季节变化方面,湿地植被面积和NDVI都呈现单峰的变化特征,从春季开始增加,在夏季末(全年的第202和205 d)达到最大值,然后开始下降,到冬季降至最低.植被的年内季节变化特征主要受到月均温度的控制.(3)干旱在一定程度上不是湖泊湿地NDVI增加的限制因子.干旱导致湖泊水位下降,滨湖滩地及湖底露出,可能会促进湿地植被生长和植被面积的扩大,使得湿地NDVI增加.     

太湖藻类的卫星遥感监测

利用卫星遥感监测和计算机图像处理技术,调查了太湖梅染湖区灌空间分布和影响范围,并根据提取的遥感信息对藻华现象的气象成因作为实步分析。