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.     

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.     

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.     

Evaluating the capabilities of the CASI hyperspectral imaging system and Aquarius bathymetric LiDAR for measuring channel morphology in two distinct river environments

Remote sensing is a powerful tool for examining river morphology. This study used detailed field surveys to assess the capability of the CASI hyperspectral imaging system and Aquarius bathymetric LiDAR to measure bed elevations in rivers with disparate optical characteristics. Field measurements of water column optical properties in the clear Snake River, the more complex Blue and Colorado, and highly turbid Muddy Creek were used to calculate depth retrieval precision and dynamic range. Differences in depth of a few centimeters were detectable via passive optical techniques in the clearest stream, but precision was greatly reduced under turbid conditions. The bathymetric LiDAR evaluated in this study could not detect shallow depths or differences in depth smaller than 11 cm owing to the difficulty of distinguishing water surface and bottom returns in laser waveforms. In clear water and with high radiometric resolution, hyperspectral systems such as CASI could detect depths approaching 10 m, but semi‐empirical analysis of the Aquarius LiDAR indicated that maximum detectable depths were of the order of 2–3 m in the clear‐flowing Snake River, and closer to 1 m in the more turbid streams. Turbidity also constrained spectrally based depth retrieval, and depth estimates from the Blue/Colorado were far less reliable than on the Snake. Both sensors yielded positively biased (0.03 m for CASI, 0.08 m for Aquarius) bed elevations on the Snake, with precisions of 0.16–0.17 m. For the Blue/Colorado, mean errors were of the order of 0.2 m, biased shallow for optical data and biased deep for LiDAR, although no Aquarius laser returns were recorded from the deepest parts of these channels; precisions were reduced to 0.29–0.32 m. Both approaches have advantages and limitations, and prospective users must understand the capabilities and constraints associated with various types of remote sensing to ensure efficient use of these evolving technologies. Copyright © 2015 John Wiley & Sons, Ltd.     

Optical remote sensing of submerged aquatic vegetation: Opportunities for shallow clearwater streams

Remote sensing has rarely been used as a tool to map and monitor submerged aquatic vegetation (SAV) in rivers, due to a combination of insufficient spatial resolution of available image data and strong attenuation of light in water through absorption and scattering. The latter process reduces the possibility to use spectral reflectance information to accurately classify submerged species. However, increasing availability of very high resolution (VHR) image data may enable the use of shape and texture features to help discriminate between species by taking an object based image analysis (OBIA) approach, and overcome some of the present limitations.This study aimed to investigate the possibility of using optical remote sensing for the detection and mapping of SAV. It firstly looked at the possibilities to discriminate submerged macrophyte species based on spectral information only. Reflectance spectra of three macrophyte species were measured in situ across a range of submergence depths. The results showed that water depth will be a limiting factor for the classification of species from remote sensing images. Only Spiked Water Milfoil (Myriophyllum spicatum) was indicated as spectrally distinct through ANOVA analysis, but subsequent Jeffries–Matusita distance analysis did not confirm this. In particular Water Crowfoot (Ranunculus fluitans) and Pondweed (Potamogeton pectinatus) could not be discriminated at 95% significance level. Spectral separability of these two species was also not possible without the effect of an overlying water column.Secondly, the possibility to improve species discrimination, using spatial and textural information was investigated for the same SAV species. VHR image data was acquired with a Near Infrared (NIR) sensitive DSLR camera from four different heights including a telescopic pole and a Helikite UAS. The results show that shape and texture information can improve the detection of the spectrally similar Pondweed and Water Crowfoot from VHR image data. The best performing feature ‘length/width ratio of sub-objects’ was obtained through expert knowledge. All of the shape and texture based features performed better at species differentiation than the spectrally based features.In conclusion this study has shown that there is considerable potential for the combination of VHR data and OBIA to map SAV in shallow stream environments, which can benefit species monitoring and management.     

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.     

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.     

向导式遥感震害评估系统研制

依托国家科技支撑计划重点项目子专题,在总结、归纳已有震害评估系统处理方式、流程及优缺点的前提下,研究了符合实际工作状况的遥感震害评估系统.该系统集成了基于ENVI/IDL、ERDAS开发的影像处理模块,可辅助提取高分辨率遥感影像中房屋倒塌、道路损毁、滑坡、泥石流、堰塞湖等震害信息.尤其是面向对象分类模块,对遥感影像各种特征进行了综合处理.基于ArcEngine开发的空间数据管理与分析模块,可处理道路空间位置分布、地震烈度划分、行政区划及属性等信息.并实现了对各模块向导式的流程化调用,有效提高了震后灾害评估工作的效率.该系统已在地震应急工作中发挥了有力的作用.     

The remote sensing observation in experiments of rock failure and the beginning of remote sensing rock mechanics

The remote sensing observational study for infrared radiation of rocks was proceeded during the loading on rocks until failure. The major instruments used in experiments were transient spectrum apparatus, intelligent spectrum apparatus, infrared radiation thermometer, infrared spectrum radiometer, and infrared thermal imaging system. The experiments for 26 kinds of rocks were made. The studies show that infrared radiation temperature of rocks increases along with increasing of stress. The amplitude of infrared radiation spectrum of rocks also increases along with increasing of stress. The observational results of infrared thermal imaging of rocks are consistent with infrared radiation temperature. Before formation of major faults for some rocks, the belt-shape thermal imaging of temperature anomaly displaies in position of future major faults. This study has led the new technology of remote sensing into rock mechanics and tend to establish a new field in rock mechanics — remote sensing rock mechanics (or remote sensing rock physics). The application of remote sensing rock mechanics in prediction of earthquake and rock burst, and in measurement of stress field in rock mass is expected. The Chinese version of this paper appeared in the Chinese edition ofActa Seismologica Sinica,14, Supp., 645–652, 1992. Jin-Shen HAO, Ji-Han LI, Xiao-Hong LIU, Yi-Qiao ZHI, Jin-Kai ZHANG, Yong-Hong Lü, Yi LIU, Yun-Shen YU, He ZHANG, Quan-Quan JI, Xiao-Fan ZHU and Ning CHEN took part in this work. This subject is supported by the Chinese Joint Seismological Science Foundation (91006). Work of Institute of Geophysics, SSB (93A0009).     

Simulating streamflow on regulated rivers using characteristic reservoir storage patterns derived from synthetic remote sensing data

This study presents a method to estimate streamflow in rivers regulated by lakes or reservoirs using synthetic satellite remote sensing data. To illustrate the approach, the new reservoir routing method is integrated into the Hillslope River Routing model, and a case study is presented for the highly regulated river in the Cumberland River basin (46,400 km²). The study period is April–May 2000, which contains a significant flood event that occurred in 1–2 May 2000. The model is shown to capture storage/release characterises in eight reservoirs with a mean normalized root mean square error (NRMSE) of 20% for entire simulation period and 27% for the May flood event. These errors are 69 and 75%, respectively, less than the NRMSE if reservoirs are not included in the model. Given the limitations of satellite missions, the impacts of the revisit cycles and operational periods are quantified. We used 26 observation sets of satellite altimetry over Cumberland River basin that are generated by considering both repeat cycles and satellite operation periods. For the revisit cycles, increasing the interval of repeat cycle leads to a corresponding increase of mean NRMSE from 27 to 59% as a result of sampling fewer flood events and smoothing of the change in storage signal as a result of longer intervals between visits. For the operation periods, the impact of data periods is limited because of the strong seasonal pattern of reservoir operations. Overall, the results suggest that the generalized routing model derived from reservoir stage observations can be used to simulate reservoir operating conditions, which can be used in forecasting hydrologic impacts of land cover or climate change. 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.     

Remote sensing analysis of physical complexity of North Pacific Rim rivers to assist wild salmon conservation

Salmon populations are highly variable in both space and time. Accurate forecasting of the productivity of salmon stocks makes effective management and conservation of the resource extremely challenging. Furthermore, widespread and consistent data on the productivity of species‐specific and total salmon stocks in a river are almost nonexistent. Ranking rivers based on physical complexity derived from remote sensing allows rivers to be objectively compared. Our approach considered rivers with great geomorphic complexity (e.g. having expansive, multichanneled floodplains and/or on‐channel lakes) as likely to have greater productivity of salmon than rivers flowing in constrained or canyon‐bound channels. Our objective was to develop a database of landscape metrics that could be used to rank the rivers in relation to potential salmon productivity. We then examined the rankings in relation to existing empirical (monitoring) data describing productivity of salmon stocks. To extract the metrics for each river basin we used a digital elevation model and multispectral satellite imagery. We developed procedures to extract channel networks, floodplains, on‐channel lakes and other catchment features; variables such as catchment area, channel elevation, main channel length, floodplain area, and density of hydrojunctions (nodes) were measured. We processed 1509 catchments in the North Pacific Rim including the Kamchatka Peninsula in Russia and western North America. Overall, catchments were most physically complex in western Kamchatka and western Alaska, and particularly on the Arctic North Slope of Alaska. We could not directly examine coherence between potential and measured productivity except for a few rivers, but the expected relationship generally held. The resulting database and systematic ranking are objective tools that can be used to address questions about landscape structure and biological productivity at regional to continental extents, and provide a way to begin to efficiently prioritize the allocation of funding and resources towards salmon management and conservation. Copyright © 2010 John Wiley & Sons, Ltd.     

城市湖泊时空演变的遥感分析——以武汉市为例

在GIS技术支持下,以多时相Landsat TM/ETM 遥感影像为数据源,利用NDWI指数提取武汉市1991年、1995年、2000年、2002年的湖泊水域面积信息,引入湖泊萎缩强度等测度指标,从时空两方面对主城区湖泊水域变化和26个主要湖泊的发展演化特征进行了系统地分析.结果表明,从1991年到2002年,武汉市主城区湖泊水域面积急剧减少,达38.67km2;主要湖泊水域的面积变化具有时空分异特征,湖泊萎缩变化与湖泊所处地区的城市建设水平、道路交通规划、政策导向等因素密切相关.分析认为,城市湖泊转变为公园后,萎缩现象得到明显遏制,通过立法加强湖泊保护力度并尽早制定城市湖泊的规划管理措施,是保护武汉幸存湖泊的有力手段.     

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.     

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.     

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.     

丽江地区遥感影像线环结构特征与场地稳定性分析

丽江地区活动性构造发育,地震发生频繁。以遥感影像线环结构理论论述了该区主要活动断裂和活动环块的遥感影像特征和地质地貌特征,并分析活动构造与场地稳定性的关系,进而划分出该区内易发震地区与相对稳定的地区。     

金星大气声波传播特性研究以及光学遥感

行星地震能够在大气中激发声波,该波动携带地震信息在大气中上传,可以作为行星地震监测研究的示踪目标.本文研究了不同频率的声波,在金星背景大气条件下的上传特征.通过计算大气密度分布、大气黏滞性和热传导效应引起的声波振幅变化,得到不同频率声波的振幅高度剖面.研究发现低频声波能够上传到较高高度,且振幅出现显著放大.根据振幅的高度分布以及金星光学辐射特征可以得到,通过光学遥感的方式探测金星声波扰动时,所选波段对应的辐射高度应为90 km附近及以上,并据此筛选了探测的可用频段.该研究结果为金星地质活动光学遥感探测的参数选择提供了参考.

     

基于Contourlet变换和ICA的多时相遥感图像变化检测

为了提高多时相遥感图像变化检测的精确度和运算效率,本文提出了一种基于Contourlet变换和独立分量分析(ICA-Independent component analysis)的变化检测算法.利用Contourlet变换多尺度、多方向性和各向异性等性质,对图像数据进行多尺度分解,再对分解后的数据进行独立分量分析,利用改进的基于牛顿迭代的固定点ICA算法分离出互相独立的数据分量,然后将分离后的数据分量转变成图像分量,最终对变化图像分量经阈值分割实现变化检测.实验结果表明,与现有的基于PCA、基于ICA、基于小波变换与ICA三种变化检测算法相比,本文算法能有效地分离出变化信息,减少了计算的复杂性,得到的变化图像具有更高的精确度,且对背景有较强的稳健性.