共查询到18条相似文献，搜索用时 296 毫秒
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《热带海洋学报》2017,(2)
高分一号卫星作为我国首颗对地观测高分辨率卫星,充分挖掘其在海洋领域的应用潜力具有重要意义。以西沙群岛晋卿岛周边浅海水域为研究区域,应用国产高分一号卫星多光谱数据,在开展图像几何校正、大气校正和耀斑校正预处理的基础上,应用常用的双波段线性和对数比值模型开展晋卿岛周边浅海水深反演,并利用实测水深数据开展精度评价,对比分析不同模型反演结果,探讨影响岛礁浅海水深反演精度的可能因素。研究表明,双波段线性模型的反演精度要明显优于对数比值模型,更适合应用于晋卿岛周边浅海水深反演,其20m以浅水深反演均方根误差为1.8m,在5m以浅区域的均方根误差为1.14m,达到了目前浅海水深卫星遥感反演的精度水平。 相似文献
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利用卫星高光谱数据反演南海岛礁区浅海地形无疑具有重要意义,它不依赖于常规水深测量数据,可获得较高反演精度,同时可获得海底反射率和海水光学参数。本文利用美国NASA EO-1卫星装载的高光谱成像仪Hyperion数据,以及Z P Lee提出的半分析模型和高光谱优化算法HOPE,反演南沙岛礁海域的浅海水深、海底反射率和固有光学参数。收集了覆盖南沙海域12个岛礁区9幅2007—2011年Hyperion L1数据,以及有关的水深现场测量资料。反演结果以中洲礁为例,0~15m水深范围,平均百分误差为14%,均方根误差为1.53,相关系数为0.96,0~25m水深范围,平均百分误差为15%,均方根误差为2.68,相关系数为0.93。中洲礁,中业岛,信义礁和双黄沙洲4个岛礁区浅海水深反演的平均百分误差为14%。研究结果证明,半分析模型和HOPE算法用于南中国海岛礁区浅海水深及光学参数测量效果良好,并可推广应用于在轨运行的中国HJ-1A卫星HSI高光谱数据及其他将投入运行的卫星高光谱数据。 相似文献
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根据遥感水深反演原理,利用海南岛龙湾港的WorldView-2多光谱卫星数据和海图水深资料,通过对水深进行0~2,2~5,5~10,10~15和15~20 m的分区处理、潮汐改正和海图水深数据与相应图像波段反射率值的相关性分析及回归分析,建立了浅海水深线性回归反演模型,开展了浅海水深的实际计算与精度分析。结果表明:对不同水深范围分别建立线性回归模型反演的水深精度要高于未分区建立的模型;分区模型中,多波段模型在0~5 m的反演精度最高,而双波段比值模型在5~20 m的反演精度最高,但是反演水深在最浅处的精度还有待提高。本文方法提取的水深与海图水深数据变化趋势基本相似,可以满足海洋科学研究对大范围浅水水下地形探测的要求。 相似文献
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本文基于海浪波折射现象和浅水波理论,提出了一种基于单景高分辨率光学遥感影像的浅海地形提取方法。首先,基于浅水波理论推导出适用于浅海区域的水深与海浪波长、频率的定量关系,针对近岸光学遥感图像复杂的海浪特征,讨论了两种海浪波长提取方法,即FFT方法和剖面线法。然后提出了基于长距离波长波动分析的海浪频率计算方法,解决了单景遥感影像的波浪频率计算难题。最后,利用单景QuickBird高分辨率光学遥感影像,以海南岛三亚湾为研究区域进行了应用实验,结果表明,对12m以浅的浅海区域,在不需要任何辅助参数的情况下,反演获得了浅海地形(DEM),经与1:25000比例尺海图的水深对比验证,地形趋势吻合良好,反演水深的均方根误差为1.07m,相对水深误差为16.2%,表明该方法适合于浅海水下地形的提取,且具有无需实测水深数据和环境参数的支持的优点。 相似文献
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利用多光谱卫星遥感影像反演浅海水深是水深测量的一种重要方式。提出一种基于主成分分析的地理加权回归模型(PCA-GWR),采用WorldView-2多光谱卫星遥感影像数据,对经过数学变换后的波段反射率数据先进行主成分分析,将得到第一主成分量进行地理加权回归分析,并与双波段比值模型、多波段线性模型和地理加权回归模型(GWR)的水深反演结果进行比较。结果显示,各个反演模型反演水深值与实测水深值的相关系数r均大于0.75,其中PCA-GWR模型水深反演结果最好,r为0.96、RMSE为1.56 m、MAE为1.06 m。研究表明,PCA-GWR模型可有效去除数据变换后的冗余信息,降低数据空间非平稳性,具有较高的反演精度与可靠性,适用于浅海水深反演。 相似文献
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在多光谱遥感浅海水深反演过程中,考虑到水体和底质影响,水深值和海水表面辐射亮度之间的线性关系不成立。本文以甘泉岛南部0～25m范围的沙质区域为研究区域,利用GeoEye-1多光谱遥感影像和多波束实测水深数据构建XGBoost非线性水深反演模型,研究了XGBoost算法用于水深反演的性能。以决定系数(R~2),均方误差(MSE)和平均绝对误差(MAE)作为评价指标,并与3种传统线性回归模型进行了对比分析。结果表明, XGBoost非线性水深反演模型的R~2、MSE和MAE分别为0.991、0.33m和0.44m,拟合程度最好,精度优于线性回归模型。为进一步探究各模型在不同水深的反演精度,将水深范围分成3段(0～8 m, 8～15 m, 15～25 m)分别进行精度验证和误差分析。结果表明, XGBoost模型在各分段的精度均优于线性回归模型, MSE依次为0.56 m, 0.14 m和0.43 m。可见,在单一底质区域下XGBoost模型的水深反演精度更高,且反演效果更稳定。 相似文献
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Shallow water depth retrieval from space-borne SAR imagery 总被引：1，自引：1，他引：0
Kaiguo Fan Weigen Huang Hui Lin Jiayi Pan Bin Fu Yanzhen Gu 《Journal of Oceanography》2011,67(4):405-413
Based on shallow water bathymetry synthetic aperture radar (SAR) imaging mechanism and the microwave scattering imaging model
for oceanic surface features, we developed a new method for shallow water depth retrieval from space-borne SAR images. The
first guess of surface currents and winds are estimated from the normalized radar crossing section (NRCS) profile of shallow
water bathymetry SAR imagery, according to the linear theory and geophysical model function. The NRCS profile is then simulated
by the microwave scattering imaging model. Both the surface currents and winds are adjusted by using the dichotomy method
step by step to make the M4S-simulated NRCS profiles approach those observed by SAR. Then, the surface currents and the wind
speeds are retrieved when a best fit between simulated signals and the SAR image appears. Finally, water depths are derived
using the Navier–Stokes equation and finite difference method with the best estimated currents and the surface winds. The
method is tested on two SAR images of the Taiwan Shoal. Results show that the simulated shallow water NRCS profile is in good
agreement with those measured by SAR with the correlation coefficient as high as 85%. In addition, when water depths retrieved
from the SAR image are compared with in situ measurements, both the root mean square and relative error are less than 3.0 m
and 6.5%, respectively, indicating that SAR images are useful for shallow water depth retrieval and suggesting that the proposed
method in this paper is convergent and applicable. 相似文献
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基于多光谱影像的水深反演方法是获取近岸水深信息的高效手段,然而反演精度低一直是制约其广泛应用的瓶颈。本文聚焦于实测水深与多光谱数据自身的空间自相关特性,提出在机器学习框架下将学习样本的空间自相关特征与统计互相关特征相结合,以提高水深反演精度。西沙北岛海域的实验结果表明:在实测数据量较小的情况下,相比传统机器学习,顾及自相关特征的新方法可获得18%的精度提升;而当实测数据量充足时,精度提升可达到27%。结果表明,将数据源的空间自相关特征融入机器学习算法中,可显著提升多光谱水深反演结果的精确性,进而为浅海海洋研究提供有效数据支撑。 相似文献
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Regular surveys of coastal zone seabed deliver important information about geomorphologic processes such as silting of waterways. The recent introduction of the Sentinel series of sensors has allowed for the use of satellite sensing for shallow bathymetry morphology monitoring. In this context, this article presents a dedicated Geographic Information System for Baltic Sea shallow water depth monitoring on the basis of Sentinel-2 imagery. The system employs Geovisual Analytics for differential analysis of bathymetry changes as well as monitoring the visibility of known wrecks in the coastal waters of Southern Baltic Sea. Results are verified with regard to known changes in shallow water bathymetry between 28 June 2015 and 3 March 2017. 相似文献
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卫星遥感反演水深（Satellite Derived Bathymetry, SDB）是获取浅海水深信息的有效手段。然而，其有效范围只限于光学浅水区域，在深水区域呈现“伪浅海”的失真现象。因此，如何准确识别SDB数据的有效范围对其广泛应用至关重要。本文基于高空间分辨率多光谱卫星影像，在深入分析深/浅水辐射亮度统计分布特征差异的基础上，提出一种数据驱动的水深反演有效性评价方法。该方法以卫星影像辐亮度信息的局域标准差作为特征，基于K-S检验方法对光学深水区域统计特征进行模型优选，并使用假设检验方法对深水无效区域对应的SDB进行识别。甘泉岛水域实验结果表明，该方法通过统计分布划分光学浅水与深水区域边界，可以有效识别光学深水区域产生的无效水深反演数据。在剔除无效区域数据后，光学浅水有效区域内水深反演平均绝对误差（MAE）为1.01，均方根误差（RMSE）为1.52。实验结果表明，本文提出的方法可准确识别SDB结果的有效区域，进而为浅海地形解译提供方法支撑。 相似文献
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Abstract Studies of coastal bathymetry are important where littoral drift has implications on the planning of fishing and dredging operations. Also, there is a possibility of finding hitherto unknown bottom features in relatively less explored regions of the shallow seas around the globe. High resolution satellite imagery over oceans provides us with quantitative methods for estimating depth in shallow parts of the seas. One of the methods is the analysis of the refraction of coastal gravity waves observed on satellite imagery. A panchromatic image acquired by SPOT with 10 m resolution on March 22, 1986, over Bay of Bengal near Madras Coast, was used for this analysis. The image was enhanced to clearly bring out the wave structure seen on the sea surface. The image was then superimposed with a 1 km × 1 km grid. For each grid cell, 64 × 64 pixels at the center were considered for getting a Fast Fourier Transform to determine the wave spectrum and the dominant wavelength present there. The classical theory of gravity waves was used to relate the shallow water wavelengths obtained as above with the corresponding wavelengths in the deep water. The deep‐water wavelength was estimated to be 110 m using the known chart depths at a set of control points. The resulting depth estimates, when compared with standard bathymetric charts, were found, in general, to be well in agreement up to a depth of 30 m in the sea, with an r.m.s. error of 2.6 meters. The method seems to be very useful for remotely sensed bathymetric work. However, further research is required to reduce the error margin and operationalize the method. 相似文献
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大气校正是水体定量遥感的基础与前提。本文从大气校正模型、大气校正模型参数、水体组分差异以及水深反演波段组合方式4个维度探讨大气校正模型对水深反演的影响。研究采用6S、FLAASH、ACOLITE与QUAC 4种大气校正模型,选取大陆型、海洋型与城市型气溶胶模式,以瓦胡岛西北侧与谢米亚岛周边浅水作为清洁水体研究区,以辽东浅滩与槟城海峡作为浑浊水体研究区,基于Landsat-8多光谱影像开展大气校正,并采用8种波段组合方式进行水深遥感反演。研究结果表明:（1）4种大气校正模型均可在一定程度上削弱大气对水体信号的影响;因参数选取以及研究区水体组分的不同,不同模型的校正结果存在一定差异;两类水体反射率峰值分别出现在蓝波段与绿波段;（2）6S大气校正模型鲁棒性较强,该模型因研究区水体组分发生变化导致对应的水深反演结果与其余模型相比波动较小;FLAASH模型在海洋型和城市型两种气溶胶模式水深反演结果在浑浊水体存在较为明显的差异,辽东浅滩浅水区平均相对误差相差7.9%;ACOLITE模型受水体类型影响显著且对浑浊水体具有优越性与稳定性,平均相对误差较FLAASH降低5.6%;（3）多波段水深反演精度普遍优于单波段,但反演精度与波段数目之间无显著的相关性;水深反演波段组合方式对不同研究区敏感性不同,清洁水体三波段模型的反演精度较好,浑浊水体中四波段模型的反演精度最优,平均相对误差较三波段模型降低达5.6%。 相似文献
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Determination of the water depths in coastal zones is a common requirement for the majority of coastal engineering and coastal science applications. However, production of high quality bathymetric maps requires expensive field survey, high technology equipment and expert personnel. Remotely sensed images can be conveniently used to reduce the cost and labor needed for bathymetric measurements and to overcome the difficulties in spatial and temporal depth provision. An Artificial Neural Network (ANN) methodology is introduced in this study to derive bathymetric maps in shallow waters via remote sensing images and sample depth measurements. This methodology provides fast and practical solution for depth estimation in shallow waters, coupling temporal and spatial capabilities of remote sensing imagery with modeling flexibility of ANN. Its main advantage in practice is that it enables to directly use image reflectance values in depth estimations, without refining depth-caused scatterings from other environmental factors (e.g. bottom material and vegetation). Its function-free structure allows evaluating nonlinear relationships between multi-band images and in-situ depth measurements, therefore leads more reliable depth estimations than classical regressive approaches. The west coast of the Foca, Izmir/Turkey was used as a test bed. Aster first three band images and Quickbird pan-sharpened images were used to derive ANN based bathymetric maps of this study area. In-situ depth measurements were supplied from the General Command of Mapping, Turkey (HGK). Two models were set, one for Aster and one for Quickbird image inputs. Bathymetric maps relying solely on in-situ depth measurements were used to evaluate resultant derived bathymetric maps. The efficiency of the methodology was discussed at the end of the paper. It is concluded that the proposed methodology could decrease spatial and repetitive depth measurement requirements in bathymetric mapping especially for preliminary engineering application. 相似文献
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在过去的十几年中,海洋可控源电磁法的迅猛发展在油气勘探中起到了重要的作用。在浅海环境中,常见的两种可控源电磁法的数据采集系统采用海底基站式（Sea Bed Logging（SBL））,以及拖缆式（Towed Streamer electromagnetics（TSEM））两种模式。本文的研究目的是研究在不同水深条件下,两种数据采集系统的工作模式以及海水对其的影响。为了更好的比较两种数据采集方式,本文采用了三种不同的分析方法：一维敏感度模型,二维油藏敏感指数,Occam反演。一维敏感度模型能够迅速的给出结果,但是由于结果的信息量有限,不足以给定准确的结论。二维油藏敏感指数可以依据正演的结果快速的给定一个水深和油藏敏感度的关系。Occam反演方法用于对合成数据进行反演计算,估计地下介质电阻率参数。为了更好的评价反演结果,本文引入了横向电阻异常率（ATR）。通过对合成数据的反演结果的分析,本文得出以下结论：在浅水环境中,SBL和TSEM数据采集系统都可以提供较高的分辨率,对高电阻层有很好的敏感度。在深水环境中,SBL数据采集系统具有明显的优势。ATR对于反演的电阻率参数结果具有很好的评价作用。 相似文献