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A change in the elevation of bare tidal flats outside a mangrove area is an indispensable factor for the sustainable development of mangroves. Waterline extraction, as an effective and economical tool used in reconstructing the terrain of an intertidal zone, has been widely applied to open-coast tidal flats by constructing a digital elevation model (DEM). However, mangrove wetlands are usually located in wave-sheltered sites, such as estuaries and bays that have narrow tidal channels flanked by tidal flats. Changes in water level are affected by the dry-wet processes of complex landforms caused by tides. This article takes as a study case the area of Yingluo Bay, which covers the core region of the Zhanjiang and Shankou National Mangrove National Nature Reserve in southwestern China. Waterline extraction based on seventeen multisource and multispectral satellite images obtained from December 2014 to April 2015, combining the finite-volume coastal ocean model (FVCOM) hydrodynamic model in an iterative process, was used to generate a topographical map of the bare tidal flat outside the mangrove area in Yingluo Bay. The quality of the iterative DEMs was evaluated via six transects of a ground-based survey using Real - time kinematic (RKT) GPS in May 2015. The mean absolute error (MAE) and root mean square error (RMSE) of the DEM decreased with an increase in the number of iterations. In this study, the DEM in the third iteration was used as the final output because the difference from the previous iterative DEM satisfied an inversion-stopping criterion. The MAE and RMSE of the final DEM with the measured data were 0.072 and 0.09?m, respectively, without considering small tidal creeks. The method used in this study can be an effective and highly precise approach for detecting and reconstructing the historical terrain of a bare tidal flat outside a mangrove area. This work also has great importance regarding intertidal resource management and the sustainable development of mangroves facing the vulnerable coastal ecological environment. 相似文献
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Bahram Saghafian 《International Journal of Applied Earth Observation and Geoinformation》2009,11(5):317-323
River low flow (LF) is an important hydrological characteristic used in management of the quantity and quality of water resources. A common way to transpose at-station low flow quantiles to ungaged locations involves development of regional multivariate regression models. In site selection studies of water control facilities, need arises to automate the mapping of LF characteristics onto the stream network in a continuous manner. This would allow estimation of LF at any desired ungaged location. A mapping algorithm is introduced that determines the value of regression model's independent variables (input components) over the drainage area of each stream pixel and calculates the flow (output). The mapping algorithm relies mainly on the digital elevation model (DEM) and its derivatives, such as flow direction and flow accumulation. Furthermore, the contribution of each independent variable of the regional model to the total flow may be plotted to represent the flow profiles along the streams. A case study involving LF mapping in rivers of Gilan province, Iran, where LF quantiles are required for issuing water withdrawal permits as well as maintaining water quality standards, is also described in the paper. Overall, the maps and profiles of flow statistics in the region of interest provide convenient visualization and assessment tools for water resource and environmental engineers. The transposition algorithm may also be applied in regional mapping of other flow characteristics such as flood or average flows. 相似文献
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Accuracy assessment of digital elevation models by means of robust statistical methods 总被引:3,自引:0,他引:3
Measures for the accuracy assessment of Digital Elevation Models (DEMs) are discussed and characteristics of DEMs derived from laser scanning and automated photogrammetry are presented. Such DEMs are very dense and relatively accurate in open terrain. Built-up and wooded areas, however, need automated filtering and classification in order to generate terrain (bare earth) data when Digital Terrain Models (DTMs) have to be produced. Automated processing of the raw data is not always successful. Systematic errors and many outliers at both methods (laser scanning and digital photogrammetry) may therefore be present in the data sets. We discuss requirements for the reference data with respect to accuracy and propose robust statistical methods as accuracy measures. Their use is illustrated by application at four practical examples. It is concluded that measures such as median, normalized median absolute deviation, and sample quantiles should be used in the accuracy assessment of such DEMs. Furthermore, the question is discussed how large a sample size is needed in order to obtain sufficiently precise estimates of the new accuracy measures and relevant formulae are presented. 相似文献
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分析了基于DEM数据的自动晕渲地图生成的意义,介绍了将1:5万数据库中等高线文件转换到CartoShading软件中,利用软件本身功能生成晕渲的方法. 相似文献
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