Feature based image processing methods applied to bathymetric measurements from airborne remote sensing in fluvial environments

Bathymetric maps produced from remotely sensed imagery are increasingly common. However, when this method is applied to fluvial environments, changing scenes and illumination variations severely hinder the application of well established empirical calibration methods used to obtain predictive depth–colour relationships. In this paper, illumination variations are corrected with feature based image processing, which is used to identify areas in an image with a near‐zero water depth. This information can then be included in the depth–colour calibration process, which results in an improved prediction quality. The end product is an automated bathymetric mapping method capable of a 4 m² spatial resolution with a precision of ±15 cm, which allows for a more widespread application of bathymetric mapping. Copyright © 2006 John Wiley & Sons, Ltd.     

Spectrally based remote sensing of river bathymetry

This paper evaluates the potential for remote mapping of river bathymetry by (1) examining the theoretical basis of a simple, ratio‐based technique for retrieving depth information from passive optical image data; (2) performing radiative transfer simulations to quantify the effects of suspended sediment concentration, bottom reflectance, and water surface state; (3) assessing the accuracy of spectrally based depth retrieval under field conditions via ground‐based reflectance measurements; and (4) producing bathymetric maps for a pair of gravel‐bed rivers from hyperspectral image data. Consideration of the relative magnitudes of various radiance components allowed us to define the range of conditions under which spectrally based depth retrieval is appropriate: the remotely sensed signal must be dominated by bottom‐reflected radiance. We developed a simple algorithm, called optimal band ratio analysis (OBRA), for identifying pairs of wavelengths for which this critical assumption is valid and which yield strong, linear relationships between an image‐derived quantity X and flow depth d. OBRA of simulated spectra indicated that water column optical properties were accounted for by a shorter‐wavelength numerator band sensitive to scattering by suspended sediment while depth information was provided by a longer‐wavelength denominator band subject to strong absorption by pure water. Field spectra suggested that bottom reflectance was fairly homogeneous, isolating the effect of depth, and that radiance measured above the water surface was primarily reflected from the bottom, not the water column. OBRA of these data, 28% of which were collected during a period of high turbidity, yielded strong X versus d relations (R² from 0·792 to 0·976), demonstrating that accurate depth retrieval is feasible under field conditions. Moreover, application of OBRA to hyperspectral image data resulted in spatially coherent, hydraulically reasonable bathymetric maps, though negative depth estimates occurred along channel margins where pixels were mixed. This study indicates that passive optical remote sensing could become a viable tool for measuring river bathymetry. Copyright © 2009 John Wiley & Sons, Ltd.     

Remote measurement of river morphology via fusion of LiDAR topography and spectrally based bathymetry

This study developed and evaluated a hybrid approach to remote measurement of river morphology that combines LiDAR topography with spectrally based bathymetry. Comparison of filtered LiDAR point clouds with surveyed cross‐sections indicated that subtle features on low‐relief floodplains were accurately resolved by LiDAR but that submerged areas could not be detected due to strong absorption of near‐infrared laser pulses by water. The reduced number of returns made the active channel evident in a LiDAR point density map. A second dataset suggested that pulse intensity also could be used to discriminate land from water via a threshold‐based masking procedure. Fusion of LiDAR and optical data required accurate co‐registration of images to the LiDAR, and we developed an object‐oriented procedure for achieving this alignment. Information on flow depths was derived by correlating pixel values with field measurements of depth. Highly turbid conditions dictated a positive relation between green band radiance and flow depth and contributed to under‐prediction of pool depths. Water surface elevations extracted from the LiDAR along the water's edge were used to produce a continuous water surface that preserved along‐channel variations in slope. Subtracting local flow depths from this surface yielded estimates of the bed elevation that were then combined with LiDAR topography for exposed areas to create a composite representation of the riverine terrain. The accuracy of this terrain model was assessed via comparison with detailed field surveys. A map of elevation residuals showed that the greatest errors were associated with underestimation of pool depths and failure to capture cross‐stream differences in water surface elevation. Nevertheless, fusion of LiDAR and passive optical image data provided an efficient means of characterizing river morphology that would not have been possible if either dataset had been used in isolation. Copyright © 2011 John Wiley & Sons, Ltd.     

Optical remote mapping of rivers at sub‐meter resolutions and watershed extents

At watershed extents, our understanding of river form, process and function is largely based on locally intensive mapping of river reaches, or on spatially extensive but low density data scattered throughout a watershed (e.g. cross sections). The net effect has been to characterize streams as discontinuous systems. Recent advances in optical remote sensing of rivers indicate that it should now be possible to generate accurate and continuous maps of in‐stream habitats, depths, algae, wood, stream power and other features at sub‐meter resolutions across entire watersheds so long as the water is clear and the aerial view is unobstructed. Such maps would transform river science and management by providing improved data, better models and explanation, and enhanced applications. Obstacles to achieving this vision include variations in optics associated with shadows, water clarity, variable substrates and target–sun angle geometry. Logistical obstacles are primarily due to the reliance of existing ground validation procedures on time‐of‐flight field measurements, which are impossible to accomplish at watershed extents, particularly in large and difficult to access river basins. Philosophical issues must also be addressed that relate to the expectations around accuracy assessment, the need for and utility of physically based models to evaluate remote sensing results and the ethics of revealing information about river resources at fine spatial resolutions. Despite these obstacles and issues, catchment extent remote river mapping is now feasible, as is demonstrated by a proof‐of‐concept example for the Nueces River, Texas, and examples of how different image types (radar, lidar, thermal) could be merged with optical imagery. The greatest obstacle to development and implementation of more remote sensing, catchment scale ‘river observatories’ is the absence of broadly based funding initiatives to support collaborative research by multiple investigators in different river settings. Copyright © 2007 John Wiley & Sons, Ltd.     

High resolution,basin extent observations and implications for understanding river form and process

Fifty years of fluvial studies have posited a variety of conceptual frameworks for characterizing river forms and processes throughout entire basins, including hydraulic geometry, the river continuum concept, self‐organized criticality, and sediment links. This article uses basin‐extent, high resolution observations of fluvial forms in the Nueces River basin, Texas, and Yellowstone National Park to evaluate the ability of these frameworks to characterize system behavior across a multitude of scales. The Nueces data were collected with remote sensing methods and the Yellowstone data were collected through extensive field surveys. The data resolution, spatial extent, and quality of these data sets allow direct comparison between the two areas. The ‘hyperscale’ comparison supports using of each these frameworks at specific scales, but also indicates an irreducible amount of variation in both datasets across many different scales that is not captured by the conceptual frameworks. Moreover, the scales and locations where one framework, such as hydraulic geometry, works well are often not the same scales and locations where another framework, such as the river continuum concept, works well. Because the conceptual frameworks appear to operate at scales and locations distinct from one another, the measurement approaches necessary to observe them must also be at different scales and locations. For example, ‘seeing’ self‐organized criticality in a river system is difficult without an extensive survey through space, whereas the recognition of sediment links requires quite intense sampling in specific river regions. We suggest that these separations between measurement scales represent an incommensurability issue in river studies, making it very difficult to both communicate among and test between two or more competing theories. Making simultaneous hyperscale observations of the river is one approach to minimizing the theory‐ladeness of observation, as deviations from different predictions can be plotted at every scale. Copyright © 2010 John Wiley & Sons, Ltd.     

Quantifying large‐scale historical formation of accommodation in the Mississippi Delta

Large volumes of new accommodation have formed within the Mississippi Delta plain since the mid‐1950s in association with rapid conversion of coastal wetlands to open water. The three‐dimensional aspects and processes responsible for accommodation formation were quantified by comparing surface elevations, water depths, and vertical displacements of stratigraphic contacts that were correlated between short sediment cores. Integration of data from remotely sensed images, sediment cores, and water‐depth surveys at 10 geologically diverse areas in the delta plain provided a basis for estimating the total volume of accommodation formed by interior‐wetland subsidence and subsequent erosion. Results indicate that at most of the study areas subsidence was a greater contributor than erosion to the formation of accommodation associated with wetland loss. Tens of millions of cubic meters of accommodation formed rapidly at each of the large open‐water bodies that were formerly continuous interior delta‐plain marsh. Together the individual study areas account for more than 440 × 10⁶ × m³ of new accommodation that formed as holes in the Mississippi River delta‐plain fabric between 1956 and 2004. This large volume provides an estimate of the new sediment that would be needed just at the study areas to restore the delta‐plain wetlands to their pre‐1956 areal extent and elevations. Published 2010. This article is a US Government work and is in the public domain in the USA.     

Recent geomorphological evolution of the deltas of the rivers Seman and Vjosa,Albania

Rising in the Neogene hills of the Mallakaster, the rivers Seman and Vjosa have built up two large joint deltas on the Albanian Adriatic shore. This shoreline is characterized by a low sandy coast with bars and spits. Changes in the river courses and migration of the mouths of the deltas were rapid and numerous from the Holocene period until the beginning of drainage works in the 1950s. The drainage basins of the two rivers are developed in soft clastic rocks (flysch and molasse) in the proportion of 71·4 per cent for the Seman and 44·8 per cent for the Vjosa. Both rivers carry abundant sediment loads, amounting to 6·7 × 10⁶ tonnes per year for the Vjosa and 13·2 × 10⁶ tonnes per year for the Seman. This is the reason why the alluvial deposits of the Seman have built up two‐thirds of the alluvial plain. The use of a SPOT image dated 25 May 1995 (HRV 3 081‐268) enabled us to view the effects of coastal and fluvial dynamics, the role of neotectonics as well as the predominance of the plume of suspended sediment of the Seman river. Using this image, a geomorphological map was drawn, which identifies the palaeochannels of the Seman and the Vjosa. In order to date those palaeochannels we have made an archaeological inventory from oral and written published information. The location of the sites we studied was checked systematically in the field. The mediaeval and Ottoman archives kept in Tirana also provided substantial information, as well as the reconstitution of the evolution of the shoreline between 1870 and 1990, carried out using an inventory of topographic maps. This work allowed us to reconstitute the progression of the deltas of the Seman and the Vjosa since antiquity. We may then infer that from antiquity up to the Middle Ages, the deltas of the Seman and the Vjosa both progressed very moderately and in a comparable way. However, at the end of the 15th century the Seman underwent a major change in its course, through a southward migration of the river. The natural processes of alluviation and changes in the river courses seem to have been accelerated as agricultural exploitation of the Neogene hills that form most of the drainage basin of the Seman increased. This exploitation is linked with the massive exportation of cereal from the port of Skela e Pirgut, which started in the 14th century. It appears that the 20th century has been the period of the largest progression of the deltas during historical times. The speed of progression increased as early as the beginning of the century, as a result of the rapid growth of the rural population densities. Soil erosion from arable fields increased catchment sediment yields to promote rapid changes in the river courses. This resulted in abandonment of deltaic mouths, a phenomenon leading to a straightening of the coast. Thus to the south of the present mouth of the Seman the coast receded by 7 to 30 m per year between 1968 and 1990 as a result of the abandonment of a mouth. Copyright © 2001 John Wiley & Sons, Ltd.     

Qualitative and quantitative applications of LiDAR imagery in fluvial geomorphology

The potential for geomorphological mapping and quantitative calculations of light detection and ranging (LiDAR) data within fluvial geomorphology was studied for two river catchments within Belgium (Dijle and Amblève), which differ in physical settings and floodplain morphology. Two commercial, of‐the‐shelf LiDAR datasets with different specifications (horizontal resolution and vertical accuracy) were available for parts of the floodplains of both catchments. Real‐time kinematic (RTK) Global Positioning System (GPS) data were used as ground truth for error calculations. Qualitative analysis of LiDAR data allowed the identification of former channel patterns, levees, colluvial hillslope and fan deposits. These results were confirmed by field data, topographic surveys and historical maps. The pixel resolution proved to be an important factor in the identification of small landforms: only features with a width equal to or larger than LiDAR resolution can be detected. This poses limits on the usability of regionally available LiDAR data, which often have a horizontal resolution of several metres. The LiDAR data were also used in a quantitative analysis of channel dynamics. In the study area, the width of the Dijle River channel increased 3 m on average between 1969 and 2003. A sediment budget of channel processes for the period 1969–2003 indicated a total river bank erosion of 16·1 10³ m³ and a total within channel deposition of 7·1 10³ m³, resulting in a net river erosion of 9·0 10³ m³ or c. 0·4 Mg year^?1 per metre river length. Sequential LiDAR data can in theory be used to calculate vertical sedimentation rates, as long as there is control on the error of the reference levels used. Copyright © 2008 John Wiley and Sons, Ltd.     

基于地面实测光谱的太湖水体富营养化水平估算

富营养化指数是评价水体污染情况的一个重要的综合性指标．通过对高光谱遥感数据和水体富营养化指数的分析,确立了反演水体富营养化水平的高光谱敏感波段,进而用选择的敏感波段和波段组合来建立模型．通过对几个模型的比较,选出了较为理想的估算模型．最后对模型进行精度分析,认为该模型具有一定的可靠性和实用性．从而确定了直接由高光谱遥感数据监测水体富营养化水平的可能性,为实现由高光谱遥感数据开展大范围的水质调查奠定了一定的理论基础．     

Multivariate approach for chlorophyll-a and suspended matter retrievals in Case II type waters using hyperspectral data

Abstract

Remote sensing has become promising in providing temporal and spatial information on biogeodynamics in large and open freshwater bodies. In optically complex environments, such as in the Western Basin of Lake Erie (WBLE), the water contains multiple biogeochemical constituents or colour producing agents (CPAs), such as phytoplankton, suspended matter and dissolved organic carbon; identifying and analysing such in-water constituents is crucial for understanding and assessing many biogeochemical processes. For example, concentrations of chlorophyll-a and total suspended matter can be used as proxies to assess phytoplankton dynamics and particulate loading. However, quantitative estimation of their concentrations from satellite observations is complicated when working with mixed spectral signatures. Hyperspectral remote sensing is fast emerging as a key technology for advanced and improved understanding of optically complex waters. This study estimates concentrations of chlorophyll-a and total suspended matter (TSM) in the WBLE by applying the partial least squares (PLS) method to a full range (400–900 nm) of continuous narrow spectral bands. The PLS method models the covariance between hyperspectral bands and CPAs, and identifies the optimal bands that characterize most of the variance in the CPAs. This method avoids the curse of dimensionality and the effects of multi-collinearity, a challenge that is associated with new-generation hyperspectral satellite sensors. Validation parameters for the PLS-based models produced R² of 0.84 for chlorophyll-a (RMSE = 1.18 μg/L), and R² of 0.90 for TSM (RMSE = 1.26 mg/L), illustrating the potential of the PLS method for isolating and extracting absorption features characterizing the various CPAs in optically complex Case II type waters.

Editor Z.W. Kundzewicz Associate editor Not assigned     

Assessing aeolian beach‐surface dynamics using a remote sensing approach

A remote sensing technique for assessing beach surface moisture was used to provide insight into beach‐surface evolution during an aeolian event. An experiment was carried out on 21 October 2007 at Greenwich Dunes, Prince Edward Island National Park, Canada, during which cameras were mounted on a mast on the foredune crest at a height of about 14 m above the beach. Maps of beach surface moisture were created based on a calibrated relationship between surface brightness from the photographs and surface moisture content measured in situ at points spaced every 2.5 m along a transect using a Delta‐T moisture probe. A time sequence of maps of surface moisture content captured beach surface evolution through the transport event at a spatial and temporal resolution that would be difficult to achieve with other sampling techniques such as impedance probes. Erosion of the foreshore and berm crest resulted in an increase in surface moisture content in these areas as the wetter underlying sediments were exposed. Flow expansion downwind of the berm crest led to sand deposition and a consequent decrease in surface moisture content. Remote sensing systems such as the one presented here allow observations of the combined evolution of beach surface moisture, shoreline position, and fetch distances during short‐term experiments and hence provide a comprehensive rendering of sediment erosion and transport processes. Copyright © 2012 John Wiley & Sons, Ltd.     

Soil erosion assessment using geomorphological remote sensing techniques: an example from southern Italy

The aim of this study is to assess of the distribution and map the geomorphological effects of soil erosion at the basin scale identifying newly‐formed erosional landsurfaces (NeFELs), by means of an integration of Landsat ETM 7+ remotely sensed data and field‐surveyed geomorphological data. The study was performed on a 228·6 km²‐wide area, located in southern Italy. The study area was first characterized from a lithological, pedological, land‐use and morpho‐topographic point of view and thematic maps were created. Then, the georeferenced Landsat ETM 7+ satellite imagery was processed using the RSI ENVI 4.0 software. The processing consisted of contrast stretching, principal component analysis (PCA), decorrelation stretching and RGB false colour compositing. A field survey was conducted to characterize the features detected on the imagery. Particular attention was given to the NeFELs, which were located using a global positioning system (GPS). We then delimited the Regions of Interest (ROI) on the Landsat ETM 7+ imagery, i.e. polygons representing the ‘ground‐truth’, discriminating the NeFELs from the other features occurring in the imagery. A simple statistical analysis was conducted on the digital number (DN) values of the pixels enclosed in the ROI of the NeFELs, with the aim to determine the spectral response pattern of such landsurfaces. The NeFELs were then classified in the entire image using a maximum likelihood classification algorithm. The results of the classification process were checked in the field. Finally, a spatial analysis was performed by converting the detected landsurfaces into vectorial format and importing them into the ESRI ArcViewGIS 9.0 software. Application of these procedures, together with the results of the field survey, highlighted that some ‘objects’ in the classified imagery, even if displaying the same spectral response of NeFELs, were not landsurfaces subject to intense soil erosion, thus confirming the strategic importance of the field‐checking for the automatically produced data. During the production of the map of the NeFELs, which is the final result of the study, these ‘objects’ were eliminated by means of simple, geomorphologically‐coherent intersection procedures in a geographic information system (GIS) environment. The overall surface of the NeFELs had an area of 22·9 km², which was 10% of the total. The spatial analysis showed that the highest frequency of the NeFELs occurred on both south‐facing and southwest‐facing slopes, cut on clayey‐marly deposits, on which fine‐textured and carbonate‐rich Inceptisols were present and displaying slope angle values ranging from 12° to 20°. The comparison of two satellite imageries of different periods highlighted that the NeFELs were most clearly evident immediately after summer tillage operations and not so evident before them, suggesting that these practices could have played an important role in inducing the erosional processes. Copyright © 2009 John Wiley & Sons, Ltd.     

Using width‐based rating curves from spatially discontinuous satellite imagery to monitor river discharge

Remote estimation of river discharge from river width variations is an intriguing method for gauging rivers without conventional measurements. Entirely cloud‐free imagery of an entire river reach is often rare, but partial coverage is more frequent. Discharge is estimated from spatially discontinuous imagery via construction of multiple width–discharge rating curves within a 62‐km reach of the Tanana River, Alaska. The resulting discharge error is as low as 6.7% root mean squared error. Imagery covering <20% of the study reach can be used. Copyright © 2014 John Wiley & Sons, Ltd.     

Monitoring acidic water in a polluted river with hyperspectral remote sensing (HyMap)

Abstract

Sulphide mine waste extensively contaminates the Odiel River (southwest Spain), releasing sulphuric acid into the water body. Acidic water in this river precipitates and dissolves variably hydrated iron sulphate in a complex geological pattern controlled by climate. Local abrupt changes in the water pH in the vicinity of highly contaminated tributaries can be mapped by means of imaging spectroscopy using hyperspectral remote sensing (HyMap) data. Also, increased pH through mixing of acidic river water with marine water can be detected when the river reaches the area influenced by sea tides. Mapping the quality of water with hyperspectral data is confounded by vegetation, either dry or wet, rooted or floating. The spectral features of acidic water measured with a field spectrometer revealed the spectral influence of green vegetation, similar to the influence of the depth and transparency of water. Careful mapping of such parameters with HyMap data must therefore precede any spectral evaluation of water related to acidity in a river course. The spectral features detectable by HyMap data and associated with pH changes caused by contamination in river water by iron sulphide mine waste, and their controls, are described and references established for routine monitoring through hyperspectral image processing.     

应用实测光谱估算千岛湖夏季叶绿素a浓度

依据2010年8月的实测数据构建了千岛湖水体夏季叶绿素a浓度的实测光谱数据估算模型,并进行了验证.利用ASD FieldSpec3野外光谱仪获取高光谱数据,计算水体离水辐亮度和遥感反射率.通过寻找反演水体叶绿素a浓度的高光谱敏感波段,采用单波段相关分析、波段比值、微分光谱、三波段模型、BP人工神经网络等多种算法进行比较分析,结果表明:叶绿素a浓度与单波段光谱反射率的相关性不大;596 nm和489 nm波长处反射率比值、545 nm处光谱一阶微分与叶绿素a浓度均呈较显著相关,估测模型决定系数R2分别为0.782、0.590,RMSE分别为0.89、1.98μg/L;三波段模型的反演结果优于传统的波段比值和一阶微分法,R2为0.838,RMSE为0.71μg/L;神经网络模型大大提高了叶绿素a浓度的反演精度,R2高达0.942,RMSE为0.63μg/L.本研究为今后在千岛湖水域的夏季相邻月份进行叶绿素a浓度大范围遥感反演研究奠定了基础.     

Land cover classification of remote sensing imagery based on interval-valued data fuzzy c-means algorithm

There is a certain degree of ambiguity associated with remote sensing as a means of performing earth observations.Using interval-valued data to describe clustering prototype features may be more suitable for handling the fuzzy nature of remote sensing data,which is caused by the uncertainty and heterogeneity in the surface spectral reflectance of ground objects.After constructing a multi-spectral interval-valued model of source data and defining a distance measure to achieve the maximum dissimilarity between intervals,an interval-valued fuzzy c-means(FCM)clustering algorithm that considers both the functional characteristics of fuzzy clustering algorithms and the interregional features of ground object spectral reflectance was applied in this study.Such a process can significantly improve the clustering effect;specifically,the process can reduce the synonym spectrum phenomenon and the misclassification caused by the overlap of spectral features between classes of clustering results.Clustering analysis experiments aimed at land cover classification using remote sensing imagery from the SPOT-5 satellite sensor for the Pearl River Delta region,China,and the TM sensor for Yushu,Qinghai,China,were conducted,as well as experiments involving the conventional FCM algorithm,the results of which were used for comparative analysis.Next,a supervised classification method was used to validate the clustering results.The final results indicate that the proposed interval-valued FCM clustering is more effective than the conventional FCM clustering method for land cover classification using multi-spectral remote sensing imagery.