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1.
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2.
Soil surface roughness (SSR) is an important factor in controlling sediment and runoff generation, influencing directly a wide spectrum of erosion parameters. SSR is highly variable in time and space under natural conditions, and characterizing SSR to improve the parameterization of hydrological and erosion models has proved challenging. Our study uses recent technological and algorithmic developments in capturing and processing close aerial sensing data to evaluate how high-resolution imagery can assist the temporally and spatially explicit monitoring of SSR. We evaluated the evolution of SSR under natural rainfall and growing vegetation conditions on two arable fields in Denmark. Unmanned aerial vehicle (UAV) photogrammetry was used to monitor small field plots over 7 months after seeding of winter wheat following conventional and reduced tillage treatments. Field campaigns were conducted at least once a month from October until April, resulting in nine time steps of data acquisition. Structure from motion photogrammetry was used to derive high-resolution point clouds with an average ground sampling distance of 2.7 mm and a mean ground control point accuracy of 1.8 mm. A comprehensive workflow was developed to process the point clouds, including the detection of vegetation and the removal of vegetation-induced point cloud noise. Rasterized and filtered point clouds were then used to determine SSR geostatistically as the standard deviation of height, applying different kernel sizes and using semivariograms. The results showed an influence of kernel size on roughness, with a value range of 0.2–1 cm of average height deviation during the monitoring period. Semivariograms showed a measurable decrease in sill variance and an increase in range over time. This research demonstrated multiple challenges to measuring SSR with UAV under natural conditions with increasing vegetation cover. The proposed workflow represents a step forward in tackling those challenges and provides a knowledge base for future research. © 2020 John Wiley & Sons, Ltd.  相似文献   

3.
Stream biophysical processes are commonly studied using multi-dimensional numerical modelling that quantifies flow hydraulics from which parameters such as habitat suitability, stream carrying capacity, and bed mobility are derived. These analyses would benefit from accurate high-resolution stream bathymetries spanning tens of kilometres of channel, especially in small streams or where navigation is difficult. Traditional ground-based survey methods are limited by survey time, dense vegetation and stream access, and are usually only feasible for short reaches. Conversely, airborne topobathymetric LiDAR surveys may overcome these limitations, although limited research is available on how errors in LiDAR-derived digital elevation models (DEMs) might propagate through flow models. This study investigated the performance of LiDAR-derived topobathymetry in support of multi-dimensional flow modelling and ecohydraulics calculations in two gravel-bedded reaches (approximately 200 m long), one morphologically complex and one morphologically simple, and at the segment scale (32 km-long stream segment) along a 15 m-wide river in central Idaho, USA. We compared metre and sub-metre-resolution DEMs generated from RTK-GPS ground and Experimental Advanced Airborne Research LiDAR-B (EAARL-B) surveys and water depths, velocities, shear stresses, habitat suitability, and bed mobility modelled with two-dimensional (2D) hydraulic models supported by LiDAR and ground-surveyed DEMs. Residual statistics, bias (B), and standard deviation (SD) of the residuals between depth and velocity predicted from the model supported by LiDAR and ground-survey topobathymetries were up to −0.04 (B) and 0.09 m (SD) for depth and −0.09 (B) and 0.20 m s−1 (SD) for velocity. The accuracy (B = 0.05 m), precision (SD = 0.09 m), and point density (1 point m−2) of the LiDAR topobathymetric survey (regardless of reach complexity) were sufficient to support 2D hydrodynamic modelling and derivative stream habitat and process analyses, because these statistics were comparable to those of model calibration with B = 0 m and SD = 0.04 m for water surface elevation and B = 0.05 m s−1 and SD = 0.22 m s−1 for velocity in our investigation. © 2020 John Wiley & Sons, Ltd.  相似文献   

4.
Advances in topobathymetric LiDARs could enable rapid surveys at sub-meter resolution over entire stream networks. This is the first step to improving our knowledge of riverine systems, both their morphology and role in ecosystems. The Experimental Advanced Airborne Research LiDAR B (EAARL-B) system is one such topobathymetric sensor, capable of mapping both terrestrial and aquatic systems. Whereas the original EAARL was developed to survey littoral areas, the new version, EAARL-B, was also designed for riverine systems but has yet to be tested. Thus, we evaluated the ability of EAARL-B to map bathymetry and floodplain topography at sub-meter resolution in a mid-size gravel-bed river. We coupled the EAARL-B survey with highly accurate field surveys (0.03 m vertical accuracy and approximately 0.6 by 0.6 m resolution) of three morphologically distinct reaches, approximately 200 m long 15 m wide, of the Lemhi River (Idaho, USA). Both point-to-point and raster-to-raster comparisons between ground and EAARL-B surveyed elevations show that differences (ground minus EAARL-B surveyed elevations) over the entire submerged topography are small (root mean square error, RMSE, and median absolute error, M, of 0.11 m), and large differences (RMSE, between 0.15 and 0.38 m and similar M) are mainly present in areas with abrupt elevation changes and covered by dense overhanging vegetation. RMSEs are as low as 0.03 m over paved smooth surfaces, 0.07 m in submerged, gradually varying topography, and as large as 0.24 m along banks with and without dense, tall vegetation. EAARL-B performance is chiefly limited by point density in areas with strong elevation gradients and by LiDAR footprint size (0.2 m) in areas with topographic features of similar size as the LiDAR footprint. © 2018 John Wiley & Sons, Ltd.  相似文献   

5.
Vegetation plays a critical role in modifying inundation and flow patterns in salt marshes. In this study, the effects of vegetation are derived and implemented in a high‐resolution, subgrid model recently developed for simulating salt marsh hydrodynamics. Vegetation‐induced drag forces are taken into account as momentum sink terms. The model is then applied to simulate the flooding and draining processes in a meso‐tidal salt marsh, both with and without vegetation effects. Marsh inundation and flow patterns are significantly changed with the presence of vegetation. A smaller area of inundation occurs when vegetation is considered. Tides propagate both on the platform and through the channels when vegetation is absent, whereas flows concentrate mainly in channels when vegetation is present. Local inundation on vegetated platforms is caused mainly by water flux spilled from nearby channels, with a flow direction perpendicular to the channel edges, whereas inundation on bare platforms has contributions from both local spilled‐over water flux and remote advection from adjacent platforms. The flooding characteristics predicted by the model showed a significant difference between higher marsh and lower marsh, which is consistent with the wetlands classification by the National Wetlands Inventory (NWI). The flooding characteristics and spatial distribution of hydroperiod are also highly correlated with the vegetation zonation patterns observed in Google Earth imagery. Regarding the strong interaction between flow, vegetation and geomorphology, the conclusion highlights the importance of including vegetation in the modeling of salt marsh dynamics. Copyright © 2017 John Wiley & Sons, Ltd.  相似文献   

6.
Flood modelling of urban areas is still at an early stage, partly because until recently topographic data of sufficiently high resolution and accuracy have been lacking in urban areas. However, digital surface models (DSMs) generated from airborne scanning laser altimetry (LiDAR) having sub‐metre spatial resolution have now become available, and these are able to represent the complexities of urban topography. This paper describes the development of a LiDAR post‐processor for urban flood modelling based on the fusion of LiDAR and digital map data. The map data are used in conjunction with LiDAR data to identify different object types in urban areas, though pattern recognition techniques are also employed. Post‐processing produces a digital terrain model (DTM) for use as model bathymetry, and also a friction parameter map for use in estimating spatially distributed friction coefficients. In vegetated areas, friction is estimated from LiDAR‐derived vegetation height, and (unlike most vegetation removal software) the method copes with short vegetation less than ～1 m high, which may occupy a substantial fraction of even an urban floodplain. The DTM and friction parameter map may also be used to help to generate an unstructured mesh of a vegetated urban floodplain for use by a two‐dimensional finite element model. The mesh is decomposed to reflect floodplain features having different frictional properties to their surroundings, including urban features (such as buildings and roads) and taller vegetation features (such as trees and hedges). This allows a more accurate estimation of local friction. The method produces a substantial node density due to the small dimensions of many urban features. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

7.
石希  夏军强  周美蓉  辛沛 《湖泊科学》2024,36(2):562-574
植物是大型河流生态系统的重要成分。但受气候变化和人类活动影响,洲滩禾本科植物高度不断发生调整,进而影响洲滩生境和河道防洪安全,故需长期监测。近年来,伴随着星载激光雷达(LiDAR)技术的发展,应用LiDAR卫星数据反演洲滩禾本科植物高度成为一种可能。本文融合新一代星载LiDAR系统GEDI数据与Sentinel-2影像,基于XGBoost算法构建了考虑物候、累积温度与光合有效辐射指标的洲滩典型禾本科植物高度外推模型,同时利用Attention-UNet算法搭建了洪淹区域识别模型。随后以长江中游洲滩为例,探明了星载LiDAR技术在获取洲滩植株高度方面的性能,分析了各指标对模型精度的影响,并初步得出了洲滩典型禾本科植物高度对不同淹没条件的响应模式。主要结论包括:(1)星载LiDAR系统GEDI具有准确探测洲滩植物高度的能力,与无人机航测数据相比RMSE=0.43 m;(2)运用GEDI数据构建禾本科植物高度外推模型时,考虑物候和累积温度等指标可有效提升模型精度,提升幅度为6.8%～10.7%;(3)利用无人机航测数据对模型外推植物高度进行评价,RMSE=0.80m。同时从模型外推结果中可知...  相似文献   

8.
机载激光雷达森林叶面积指数反演研究   总被引：9，自引：0，他引：9       下载免费PDF全文
叶面积指数(LAI)是分析冠层结构最常用的参数之一,它控制着植被的生物物理过程,如光合、呼吸、蒸腾、碳循环和降水截获等,因此快速、可靠和客观地评价LAI非常重要.本文发展了激光穿透指数(LPI)的简化计算方法,首次利用校正后的回波强度计算出LPI,以LPI为变量基于Beer-Lambert定律实现了甘肃大野口研究区森林LAI反演,并且与原始回波强度和回波数反演LAI的精度进行对比,结果发现通过距离和角度校正后的回波强度值能提高LAI反演精度.为了评价模型的可靠性和泛化性能,用留一法交叉验证程序(LOOCV)对最佳反演模型进行了验证,表明该模型没有过度拟合,具有很好的泛化能力.最后,用没有参加建模的16个实测LAI对预测值进行精度验证(R2=0.810,RMSE=0.198),发现校正后的回波强度反演山区森林LAI精度较高.本文还对激光雷达LAI反演结果与传统光学TM影像的反演结果进行了对比分析,结果表明机载激光雷达反演LAI精度(R2=0.825,RMSE=0.165)高于光学TM遥感数据(R2=0.605,RMSE=0.257),因此,可用激光雷达数据实现研究区的高精度LAI反演,为生态环境研究提供可靠的基础数据.  相似文献   

9.
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.  相似文献   

10.
The production of topographic datasets is of increasing interest and application throughout the geomorphic sciences, and river science is no exception. Consequently, a wide range of topographic measurement methods have evolved. Despite the range of available methods, the production of high resolution, high quality digital elevation models (DEMs) requires a significant investment in personnel time, hardware and/or software. However, image‐based methods such as digital photogrammetry have been decreasing in costs. Developed for the purpose of rapid, inexpensive and easy three‐dimensional surveys of buildings or small objects, the ‘structure from motion’ photogrammetric approach (SfM) is an image‐based method which could deliver a methodological leap if transferred to geomorphic applications, requires little training and is extremely inexpensive. Using an online SfM program, we created high‐resolution digital elevation models of a river environment from ordinary photographs produced from a workflow that takes advantage of free and open source software. This process reconstructs real world scenes from SfM algorithms based on the derived positions of the photographs in three‐dimensional space. The basic product of the SfM process is a point cloud of identifiable features present in the input photographs. This point cloud can be georeferenced from a small number of ground control points collected in the field or from measurements of camera positions at the time of image acquisition. The georeferenced point cloud can then be used to create a variety of digital elevation products. We examine the applicability of SfM in the Pedernales River in Texas (USA), where several hundred images taken from a hand‐held helikite are used to produce DEMs of the fluvial topographic environment. This test shows that SfM and low‐altitude platforms can produce point clouds with point densities comparable with airborne LiDAR, with horizontal and vertical precision in the centimeter range, and with very low capital and labor costs and low expertise levels. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

11.
湿地植被地上生物量是衡量湿地生态系统健康状况的重要指标,对于珍稀水禽越冬繁殖、全球碳循环、生态净化具有重要意义,是生态学与遥感解译的研究热点之一.针对于地上生物量的测算,卫星遥感数据覆盖范围广但其空间分辨率较低,无人机遥感数据空间分辨率高但采集范围小,同时受湿地面积、观测系统及外界环境等条件的影响,使得遥感影像地上生物量反演更加复杂和困难.本研究基于无人机和高分一号数据对升金湖草滩植被地上生物量反演进行研究,结合升金湖保护区4个样区无人机可见光影像与相应样区实测样本数据,建立地上生物量与可见光波段、多种可见光植被指数的线性、幂函数、多项式、对数回归模型,并通过可决系数（R2）、平均绝对误差（MAE）和均方根误差（RMSE）对模型进行精度评价,选择最优模型对无人机影像进行地上生物量反演;通过可见光波段反演得到的生物量,与高分一号WFV归一化差分植被指数（Normalized Difference Vegetation Index,NDVI）影像相结合进行回归建模,获取整个升金湖草滩植被地上生物量分布.结果表明,利用无人机红光波段建立的多项式方程对地上生物量反演有着最高模拟精度,R2=0.86、预测精度MAE=111.33 g/m2、RMSE=145.42 g/m2,且红光波段生物量反演方法得到的结果与实际生物量分布一致性较高,高分一号WFV NDVI与无人机反演生物量构建的多项式模型为最优模型,R2为0.91.本研究利用无人机和高分一号数据进行生物量反演研究,整合多源遥感数据优点,以获取更加丰富和准确的信息,进而提高地上生物量反演精度,为湿地监测和湿地恢复管理提供数据和技术支撑,具有重要研究意义和应用价值.  相似文献   

12.
Sea level rise (SLR) is threatening coastal marshes, leading to large-scale marsh loss in several micro-tidal systems. Early recognition of marsh vulnerability to SLR is critical in these systems to aid managers to take appropriate restoration or mitigation measures. However, it is not clear if current marsh vulnerability indicators correctly assess long-term stability of the marsh system. In this study, two indicators of marsh stress were studied: (i) the skewness of the marsh elevation distribution, and (ii) the abundance of codominant species in mixtures. We combined high-precision elevation measurements (GPS), LiDAR imagery, vegetation surveys and water level measurements to study these indicators in an organogenic micro-tidal system (Blackwater River, Maryland, USA), where large-scale historical conversion from marshes to shallow ponds resulted in a gradient of increasing marsh loss. The two indicators reveal increasingly stressed marshes along the marsh loss gradient, but suggest that the field site with the most marsh loss seems to experience less stress. For the latter site, previous research indicates that wind waves generated on interior marsh ponds contribute to lateral erosion of surrounding marsh edges and hence marsh loss. The eroded marsh sediment might temporarily provide the remaining marshes with the necessary sediment to keep up with relative SLR. However, this is only a short-term alleviation, as lateral marsh edge erosion and sediment export lead to severe marsh loss in the long term. Our findings indicate that marsh elevation skewness and the abundance of codominant species in mixtures can be used to supplement existing marsh stress indicators, but that additional indices such as fetch length and the sediment budget should be included to account for lateral marsh erosion and sediment export and to correctly assess long-term stability of micro-tidal marshes. © 2020 John Wiley & Sons, Ltd.  相似文献   

13.
The boat‐based, mobile mapping system (BoMMS) with a laser scanner allows the derivation of detailed riverine topographical data for fluvial applications. Combined with data acquisition from static terrestrial LiDAR (light detection and range) or mobile terrestrial LiDAR on the ground, boat‐based laser scanning enables a totally new field mapping approach for fluvial studies. The BoMMS approach is an extremely rapid methodology for surveying riverine topography, taking only 85 min to survey a reach approximately 6 km in length. The BoMMS approach also allowed an effective survey angle for deep river banks, which is difficult to achieve with aerial or static terrestrial LiDAR. Further, this paper demonstrates the three‐dimensional mapping of a point‐bar and its detailed morphology. Compared with the BoMMS surface, approximately, 80% and 96% of the terrestrial LiDAR points showed a height deviation of less than 2 cm and 5 cm, respectively, with an overall standard deviation of ± 2·7 cm. This level of accuracy and rapidity of data capture enables the mapping of post‐flood deposition directly after a flood event without an extensive time lag. Additionally, the improved object characterisation may allow for better 3D mapping of the point bar and other riverrine features. However, the shadow effect of the BoMMS survey in point bar mapping should be removed by additional LiDAR data to acquire entire riverine topography. The approach demonstrated allowed a large reach to be surveyed compared with static terrestrial LiDAR and increased the spatial limit of survey towards aerial LiDAR, but it maintains the same or even better temporal resolution as static terrestrial LiDAR. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

14.
The availability of high‐resolution, multi‐temporal, remotely sensed topographic data is revolutionizing geomorphic analysis. Three‐dimensional topographic point measurements acquired from structure‐from‐motion (SfM) photogrammetry have been shown to be highly accurate and cost‐effective compared to laser‐based alternatives in some environments. Use of consumer‐grade digital cameras to generate terrain models and derivatives is becoming prevalent within the geomorphic community despite the details of these instruments being largely overlooked in current SfM literature. A practical discussion of camera system selection, configuration, and image acquisition is presented. The hypothesis that optimizing source imagery can increase digital terrain model (DTM) accuracy is tested by evaluating accuracies of four SfM datasets conducted over multiple years of a gravel bed river floodplain using independent ground check points with the purpose of comparing morphological sediment budgets computed from SfM‐ and LiDAR‐derived DTMs. Case study results are compared to existing SfM validation studies in an attempt to deconstruct the principle components of an SfM error budget. Greater information capacity of source imagery was found to increase pixel matching quality, which produced eight times greater point density and six times greater accuracy. When propagated through volumetric change analysis, individual DTM accuracy (6–37 cm) was sufficient to detect moderate geomorphic change (order 100 000 m3) on an unvegetated fluvial surface; change detection determined from repeat LiDAR and SfM surveys differed by about 10%. Simple camera selection criteria increased accuracy by 64%; configuration settings or image post‐processing techniques increased point density by 5–25% and decreased processing time by 10–30%. Regression analysis of 67 reviewed datasets revealed that the best explanatory variable to predict accuracy of SfM data is photographic scale. Despite the prevalent use of object distance ratios to describe scale, nominal ground sample distance is shown to be a superior metric, explaining 68% of the variability in mean absolute vertical error. Published 2016. This article is a U.S. Government work and is in the public domain in the USA  相似文献   

15.
Soil loss caused by erosion has enormous economic and social impacts. Splash effects of rainfall are an important driver of erosion processes; however, effects of vegetation on splash erosion are still not fully understood. Splash erosion processes under vegetation are investigated by means of throughfall kinetic energy (TKE). Previous studies on TKE utilized a heterogeneous set of plant and canopy parameters to assess vegetation's influence on erosion by rain splash but remained on individual plant- or plot-levels. In the present study we developed a method for the area-wide estimation of the influence of vegetation on TKE using remote sensing methods. In a literature review we identified key vegetation variables influencing splash erosion and developed a conceptual model to describe the interaction of vegetation and raindrops. Our model considers both amplifying and protecting effect of vegetation layers according to their height above the ground and aggregates them into a new indicator: the Vegetation Splash Factor (VSF). It is based on the proportional contribution of drips per layer, which can be calculated via the vegetation cover profile from airborne LiDAR datasets. In a case study, we calculated the VSF using a LiDAR dataset for La Campana National Park in central Chile. The studied catchment comprises a heterogeneous mosaic of vegetation layer combinations and types and is hence well suited to test the approach. We calculated a VSF map showing the relation between vegetation structure and its expected influence on TKE. Mean VSF was 1.42, indicating amplifying overall effect of vegetation on TKE that was present in 81% of the area. Values below 1 indicating a protective effect were calculated for 19% of the area. For future work, we recommend refining the weighting factor by calibration to local conditions using field-reference data and comparing the VSF with TKE field measurements. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd  相似文献   

16.
Airborne scanning laser altimetry (LiDAR) is an important new data source that can provide two‐dimensional river flood models with spatially distributed floodplain topography for model bathymetry, together with vegetation heights for parameterization of model friction. Methods are described for improving such models by decomposing the model's finite‐element mesh to reflect floodplain vegetation features such as hedges and trees having different frictional properties to their surroundings, and significant floodplain topographic features having high height curvatures. The decomposition is achieved using an image segmentation system that converts the LiDAR height image into separate images of surface topography and vegetation height at each point. The vegetation height map is used to estimate a friction factor at each mesh node. The spatially distributed friction model has the advantage that it is physically based, and removes the need for a model calibration exercise in which free parameters specifying friction in the channel and floodplain are adjusted to achieve best fit between modelled and observed flood extents. The scheme was tested in a modelling study of a flood that occurred on the River Severn, UK, in 1998. A satellite synthetic aperture radar image of flood extent was used to validate the model predictions. The simulated hydraulics using the decomposed mesh gave a better representation of the observed flood extent than the more simplistic but computationally efficient approach of sampling topography and vegetation friction factors on to larger floodplain elements in an undecomposed mesh, as well as the traditional approach using no LiDAR‐derived data but simply using a constant floodplain friction factor. Use of the decomposed mesh also allowed velocity variations to be predicted in the neighbourhood of vegetation features such as hedges. These variations could be of use in predicting localized erosion and deposition patterns that might result in the event of a flood. Copyright © 2003 John Wiley & Sons, Ltd.  相似文献   

17.
刘超  雷启云  余思汗  杨顺  王银 《地震学报》2021,43(1):113-123
本文首先介绍了无人机摄影测量技术获取数字高程模型(digital elevation model,缩写为DEM)和地貌数据(正射影像)的作业流程,对比分析了三种不同质量密集点云生成的DEM在水平位置和高程上的差异;然后以1709年中卫南M7?大地震的主体地表破裂带为例,提取其上地震断层的垂直位错量和水平位移量.研究结果...  相似文献   

18.
Stream bathymetry is a critical variable in a number of river science applications. In larger rivers, bathymetry can be measured with instruments such as sonar (single or multi‐beam), bathymetric airborne LiDAR (light detection and ranging), or acoustic Doppler current profilers. However, in smaller streams with depths less than 2 m, bathymetry is one of the more difficult variables to map at high‐resolution. Optical remote sensing techniques offer several potential solutions for collecting high‐resolution bathymetry. In this research, I focus on direct photogrammetric measurements of bathymetry using multi‐view stereo photogrammetry, specifically Structure‐from‐Motion (SfM). The main barrier to accurate bathymetric mapping with any photogrammetric technique is correcting for the refraction of light as it passes between the two different media (air and water), which causes water depths to appear shallower than they are. I propose and test an iterative approach that calculates a series of refraction correction equations for every point/camera combination in a SfM point cloud. This new method is meant to address shortcomings of other correction techniques and works within the current preferred method for SfM data collection, oblique and highly convergent photographs. The multi‐camera refraction correction presented here produces bathymetric datasets with accuracies of ~0.02% of the flying height and precisions of ~0.1% of the flying height. This methodology, like many fluvial remote sensing methods, will only work under ideal conditions (e.g. clear water), but it provides an additional tool for collecting high‐resolution bathymetric datasets for a variety of river, coastal, and estuary systems. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

19.
Evaluation of on-line DEMs for flood inundation modeling   总被引：1，自引：0，他引：1  
Recent and highly accurate topographic data should be used for flood inundation modeling, but this is not always feasible given time and budget constraints so the utility of several on-line digital elevation models (DEMs) is examined with a set of steady and unsteady test problems. DEMs are used to parameterize a 2D hydrodynamic flood simulation algorithm and predictions are compared with published flood maps and observed flood conditions. DEMs based on airborne light detection and ranging (LiDAR) are preferred because of horizontal resolution, vertical accuracy (∼0.1 m) and the ability to separate bare-earth from built structures and vegetation. DEMs based on airborne interferometric synthetic aperture radar (IfSAR) have good horizontal resolution but gridded elevations reflect built structures and vegetation and therefore further processing may be required to permit flood modeling. IfSAR and shuttle radar topography mission (SRTM) DEMs suffer from radar speckle, or noise, so flood plains may appear with non-physical relief and predicted flood zones may include non-physical pools. DEMs based on national elevation data (NED) are remarkably smooth in comparison to IfSAR and SRTM but using NED, flood predictions overestimate flood extent in comparison to all other DEMs including LiDAR, the most accurate. This study highlights utility in SRTM as a global source of terrain data for flood modeling.  相似文献   

20.
Bar colonization by vegetation and subsequent island formation is a key bio-geomorphological process in fluvial landscape evolution. Here we investigate morphological and ecological evolution of river islands over timescales from single floods to decades, focusing on islands initiated by deposited trees that sprout to form vegetated patches. On a braided reach of the high-energy Tagliamento River, Italy, we monitored 30 pioneer islands of 1 to 17 years age in comparison with unvegetated bar surfaces, open areas between islands, and established island surfaces. We integrated morphological, surface sediment and vegetation properties of islands initiated by different flood events, combining evidence from remotely-sensed and ground observations, flow and climate time series. At a decadal timescale, pioneer islands aggrade rapidly to the elevation of the mean annual flood, showing a steady increase in vegetation canopy height, fining of surface sediments from predominantly gravel to silty-sand with a notable clay and organic fraction. The standing vegetation included over 130 species, with the largest number on island surfaces of intermediate elevation and flood disturbance. As islands age, standing vegetation becomes comprised mainly of competitor species with transient seed banks and typical of woodland, scrub, pasture and wetland habitats, whereas the winter seedbank is dominated on all surfaces by ruderal species with persistent seedbanks, mainly associated with aquatic, wetland, pasture, arable and wasteland habitats. At shorter timescales, the biogeomorphological trajectory of pioneer islands is initiated by large flood events that control the elevation of deposited trees, and subsequent flows that control tree survival and establishment. Island morphological evolution depends on the frequency-magnitude of sediment and seed delivery and redistribution by flood and possibly wind events, whereas island ability to retain sediments reflects the degree of vegetation establishment, which in the short-term may vary with seasonal to annual moisture supply, substrate characteristics and climatic growth conditions. © 2018 John Wiley & Sons, Ltd.  相似文献   

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