Derived Bathymetry(衍生测深)研究综述
Derived Bathymetry 衍生测深 - The method is combining satellite-derived bathymetry (SDB) with the regression kriging analysis, which shows a better depth water prediction compared to the SDB alone or the ordinary kriging method. [1] The extraction of satellite data for bathymetry mapping or SDB (Satellite-Derived Bathymetry) has emerged as an effective method to obtain information in terms of cost and time. [2] Satellite-derived bathymetry (SDB) emerging as a cost-effective that provides high-resolution mapping over a wide area. [3] Satellite-derived bathymetry (SDB) can support this activity, particularly when using data from a platform, like the Sentinel-2A/B twin mission of the Copernicus programme, which provides routine and repetitive image acquisition at 10 m spatial resolution. [4] While satellite-derived bathymetry (SDB) solutions have been available for approximately 25 years, the technology has matured appreciably over the past decade, and improvements will only increase further with the advent of cube satellites, which significantly increase persistence and reduce costs of satellite imagery. [5] Satellite-Derived Bathymetry (SDB) is an alternative for obtaining shallow water depth data. [6] Bathymetry retrievals from 2D, multispectral imagery, referred to as Satellite‐Derived Bathymetry (SDB), afford the potential to obtain global, nearshore bathymetric data in optically clear waters. [7] The available technologies were: remotely operated underwater vehicle (ROV), unmanned aerial vehicle (UAV), light detection and ranging (LIDAR), autonomous underwater vehicle (AUV), satellite-derived bathymetry (SDB), and multibeam echosounder (MBES), and they are applied as a case study of Kaštela Bay. [8] Derivation of bathymetry from high-resolution multispectral satellite imagery (Satellite-Derived Bathymetry: SDB) can redress this in shallow (. [9] This study intends to produce Satellite-Derived Bathymetry (SDB) from Landsat 8 images at Pantai Tok Jembal, Terengganu, Malaysia. [10] The comparison of the datasets indicates that the seismic-derived bathymetry has a vertical accuracy better than 1 m + 2 % of the absolute water depths, while the satellite-derived bathymetry has a depth accuracy better than 1 m + 5 % of the absolute water depths. [11] Seabed topography deduced from satellite-derived bathymetry and bathymetric investigations has revealed the tide-dominated Gulf (> 6 m high) has ~50 m maximum depth along the axial part. [12] The experiment’s results also show that accuracy of the derived bathymetry can be improved if the fitting parameters are adjusted according to the water depths. [13] Following a brief overview and timeline of civilian Earth observations from space, satellite-derived shorelines (SDS) and satellite-derived bathymetry (SDB) are used to introduce and demonstrate some of the present real-world capabilities of satellite optical imagery most relevant to coastal professionals and researchers. [14] One of the availabilities of remote sensing satellite imagery can be used as a provider of shallow sea depth information using the Satellite-Derived Bathymetry (SDB) technique. [15] Using green LIDAR-derived bathymetry and hydraulic modelling, we tested how mesoscale depth and velocity were related to fish counts of adult European grayling (Thymallus thymallus L. [16] Satellite-Derived Bathymetry (SDB) has been used in many applications related to coastal management. [17] Satellite-Derived Bathymetry (SDB) modeling is used to derive bathymetric data needed for enriching several applications including nautical charting. [18] Hence, BIG is exploring remote sensing techniques to help with the improvement of Indonesia’s bathymetric maps including Satellite-Derived Bathymetry (SDB). [19] This is particularly challenging with Satellite-Derived Bathymetry (SDB) where minimal in situ data may be present for validation. [20] The results presented here confirm the applicability of satellite-derived bathymetry for mapping shallow seabed complying to the category zone of confidence C as of the International Hydrographic Organization standard. [21] Nowadays Multi-Beam Echo-Sounder (MBES) derived bathymetry is used for a large range of applications. [22] This paper reports on the remote measurement of river currents and derived bathymetry from airborne time-series imagery. [23] The current study is the first that examines the suitability of them for the calculation of the Satellite-derived Bathymetry. [24] Our results demonstrate that the satellite-derived bathymetry is efficient for retrieving depths up to 10 m for coastal regions and up to 30 m for the lake environment. [25] The set of images was used to establish a bathymetric estimation that merges the derived bathymetry of each image. [26] This study combined species counts and microhabitat observations from SCUBA surveys with satellite-derived bathymetry and habitat data to create predictive species distribution maps of lionfish in a 58 km2 region along the southern edge of the island of Eleuthera in the Bahamas. [27] Satellite-Derived Bathymetry (SDB) has Median Absolute Error (MedAE) of 0. [28] 59 m; while enhancements of the derived bathymetry can be achieved by clustering water depths with different assigned GA equations. [29]该方法将卫星测深（SDB）与回归克里金分析相结合，与单独使用SDB或普通克里金方法相比，该方法显示出更好的深度水预测。 [1] 提取用于测深测绘或 SDB（卫星衍生测深）的卫星数据已成为一种在成本和时间方面获取信息的有效方法。 [2] 卫星测深 (SDB) 正在成为一种具有成本效益的方法，可在大范围内提供高分辨率测绘。 [3] 卫星测深 (SDB) 可以支持这项活动，特别是在使用来自平台的数据时，例如哥白尼计划的 Sentinel-2A/B 双胞胎任务，它以 10m 的空间分辨率提供常规和重复的图像采集。 [4] 虽然卫星测深 (SDB) 解决方案已经推出了大约 25 年，但该技术在过去十年中已经明显成熟，随着立方体卫星的出现，改进只会进一步增加，这将显着提高持久性并降低卫星图像的成本. [5] 卫星测深 (SDB) 是获取浅水深度数据的替代方法。 [6] 从 2D、多光谱图像中检索水深，称为卫星测深 (SDB)，有可能在光学清澈的海水中获得全球近岸水深数据。 [7] 可用的技术有：遥控水下航行器（ROV）、无人驾驶飞行器（UAV）、光探测和测距（LIDAR）、自主水下航行器（AUV）、卫星测深（SDB）和多波束回声测深仪（MBES），它们被用作 Kaštela Bay 的案例研究。 [8] 从高分辨率多光谱卫星图像推导水深（卫星推导水深：SDB）可以在浅层（. [9] 本研究旨在利用马来西亚登嘉楼 Pantai Tok Jembal 的 Landsat 8 图像生成卫星测深 (SDB)。 [10] 数据集对比表明，地震测深的垂直精度优于绝对水深的1 m + 2 %，而卫星测深的深度精度优于绝对水深的1 m + 5 %深度。 [11] 从卫星测深和测深调查推断的海底地形表明，潮汐主导的海湾（> 6 m 高）沿轴向部分具有 ~50 m 的最大深度。 [12] 实验结果还表明，根据水深调整拟合参数，可以提高推导测深的准确性。 [13] 在对从太空进行的民用地球观测的简要概述和时间表之后，使用卫星衍生海岸线 (SDS) 和卫星衍生测深 (SDB) 来介绍和展示与沿海最相关的卫星光学图像的一些当前现实世界能力专业人士和研究人员。 [14] 遥感卫星图像的可用性之一可用作使用卫星衍生测深 (SDB) 技术的浅海深度信息的提供者。 [15] 使用绿色激光雷达衍生的水深测量和水力模型，我们测试了中尺度深度和速度与成年欧洲河豚 (Thymallus thymallus L. [16] 卫星测深 (SDB) 已用于与海岸管理相关的许多应用中。 [17] 卫星测深 (SDB) 建模用于获得丰富包括海图在内的多种应用所需的测深数据。 [18] 因此，BIG 正在探索遥感技术，以帮助改进印度尼西亚的测深地图，包括卫星测深 (SDB)。 [19] 这对于卫星测深 (SDB) 尤其具有挑战性，因为其中可能存在用于验证的极少原位数据。 [20] 此处提供的结果证实了卫星测深法在绘制符合国际水文组织标准的置信区 C 类别的浅海床时的适用性。 [21] 如今，多波束回声测深仪 (MBES) 衍生的水深测量被用于广泛的应用。 [22] 本文报道了河流的远程测量和从机载时间序列图像中推导出的水深测量。 [23] 目前的研究是第一次检查它们是否适合计算卫星衍生的水深测量。 [24] 我们的研究结果表明，卫星测深法可有效地检索沿海地区高达 10 m 的深度和湖泊环境高达 30 m 的深度。 [25] 该组图像用于建立一个测深估计，该估计合并了每个图像的派生测深。 [26] 这项研究将 SCUBA 调查中的物种计数和微生境观察结果与卫星测深和栖息地数据相结合，在巴哈马伊柳塞拉岛南部边缘 58 平方公里的地区创建了狮子鱼的预测物种分布图。 [27] 卫星测深 (SDB) 的中值绝对误差 (MedAE) 为 0。 [28] 59米；而可以通过使用不同的分配 GA 方程对水深进行聚类来增强推导的水深测量。 [29]
Satellite Derived Bathymetry 卫星测深
Heterogeneous underwater environments such as complex bottom types represent the main factor affecting accuracy of satellite derived bathymetry. [1] The optical satellite data have capabilities to offer alternate solution in near-shore region, which has been researched for past 50 years, using evolving algorithms to estimate Satellite Derived Bathymetry (SDB). [2] Untuk mencegah insiden serupa, perolehan data batimetri menggunakan metode Satellite Derived Bathymetry (SDB) ini dianggap efektif dan efisien dalam mendapatkan informasi kedalaman di perairan dangkal, guna percepatan dalam pembuatan Electronic Navigational Chart (ENC) di perairan Raja Ampat. [3] This work supports applying Satellite Derived Bathymetry (SDB) with the available low-cost multispectral satellite imagery applications, instruments and readily accessible data for different areas with only their benthic parameters, water characteristics and atmospheric conditions. [4] However, recent advancements in satellite remote sensing, including the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) offer new tools for generating satellite derived bathymetry (SDB). [5] My comments below are mainly focused on the satellite derived bathymetry component of the work. [6] To fill this gap, over recent years, the Satellite Derived Bathymetry (SDB) techniques have been developed. [7] Therefore, many satellite derived bathymetry products use both active/passive spaceborne data to achieve spatial coverage as well as absolute depth measurements. [8] Seiring dengan perkembangan teknologi yang begitu pesat, peran teknologi penginderaan jauh saat ini adalah solusi yang diharapkan dapat menyajian data dan informasi yang di butuhkan untuk pelaksanaan kegiatan survei dengan jangka waktu yang relative pendek dan biaya murah serta hasil yang optimal guna memperbaharui peta laut tersebut, Maka metode ravid survei merupakan suatu parameter yang dapat dilaksanakan dengan menggunakan metode Satellite Derived Bathymetry (SDB). [9] Although many studies have been conducted on satellite derived bathymetry (SDB), previously used methods basically require supervised data for analysis, and cannot be used to analyze areas that are unreachable by boat or airplane. [10] In this study, a satellite derived bathymetry (SDB) map, considered suitable for shallow water, was created using random forests (RF) and multi-temporal satellite images from Google Earth Engine. [11] The results demonstrate that the satellite derived bathymetry is efficient for retrieving depths up to 10 m for coastal regions and up to 30 m for lake environment. [12] Untuk menyelesaikan masalah tersebut, Satellite Derived Bathymetry, sebuah teknologi pemetaan yang memperoleh data bathimetri dari citra satelit multispektral resolusi tinggi diterapkan. [13] Satellite derived bathymetry (SDB) enables rapid mapping of large coastal areas through measurement of optical penetration of the water column. [14] Satellite Derived Bathymetry (SDB) method uses satellite or other remote multispectral imagery for depth determination in very shallow coastal areas with clear waters. [15]复杂海底类型等异质水下环境是影响卫星测深精度的主要因素。 [1] 光学卫星数据具有在近岸地区提供替代解决方案的能力，该解决方案已经研究了 50 年，使用不断发展的算法来估计卫星衍生测深 (SDB)。 [2] 为了防止类似事件的发生，使用卫星测深 (SDB) 方法获取水深数据被认为在获取浅水深度信息方面是有效和高效的，以加速在拉贾安帕水域创建电子导航图 (ENC)。 [3] </p><p>这项工作支持将卫星测深 (SDB) 与可用的低成本多光谱卫星图像应用程序、仪器和易于获取的不同区域的数据相结合，仅具有其底栖参数、水特征和大气条件。 [4] 然而，卫星遥感方面的最新进展，包括冰、云和陆地高程卫星 2 (ICESat-2)，为生成卫星测深 (SDB) 提供了新工具。 [5] 我在下面的评论主要集中在这项工作的卫星测深部分。 [6] 为了填补这一空白，近年来，卫星衍生测深（SDB）技术得到了发展。 [7] 因此，许多卫星测深产品使用主动/被动星载数据来实现空间覆盖以及绝对深度测量。 [8] 随着技术的飞速发展，今天遥感技术的作用是一种解决方案，期望能够以相对较短的时间、低成本和最优的结果呈现实施调查活动所需的数据和信息。为了更新海洋地图，ravid 测量方法是可以使用卫星衍生测深 (SDB) 方法实现的参数。 [9] 尽管已经对卫星衍生测深（SDB）进行了许多研究，但以前使用的方法基本上需要有监督的数据进行分析，不能用于分析船只或飞机无法到达的区域。 [10] 在这项研究中，使用随机森林 (RF) 和来自 Google 地球引擎的多时相卫星图像创建了一张被认为适用于浅水区的卫星衍生测深 (SDB) 地图。 [11] 结果表明，卫星测深法可有效地检索沿海地区高达 10 m 的深度和湖泊环境高达 30 m 的深度。 [12] 为了解决这个问题，应用了卫星衍生测深，这是一种从高分辨率多光谱卫星图像中获取测深数据的测绘技术。 [13] 卫星测深 (SDB) 可以通过测量水柱的光学穿透力来快速绘制大片沿海地区的地图。 [14] 卫星测深 (SDB) 方法使用卫星或其他远程多光谱图像来确定具有清澈海水的非常浅的沿海地区的深度。 [15]
Spectrally Derived Bathymetry 光谱推导测深
Besides airborne laser bathymetry and multimedia photogrammetry, spectrally derived bathymetry provides a third optical method for deriving water depths. [1] For area-wide, high-resolution mapping of bathymetry, Sonar (Sound Navigation And Ranging), LiDAR (Light Detection And Ranging), multimedia stereo-photogrammetry, and spectrally derived bathymetry (SDB) have proved most suitable. [2]除了机载激光测深和多媒体摄影测量之外，光谱衍生测深提供了第三种光学方法来推导水深。 [1] 对于大面积的高分辨率测深测绘，Sonar（声音导航和测距）、LiDAR（光探测和测距）、多媒体立体摄影测量和光谱衍生测深 (SDB) 已被证明是最合适的。 [2]
derived bathymetry model
The results demonstrate both imageries derived bathymetry models convey promising results which can be ultilised for bathymetric mapping application. [1] Satellite-derived bathymetry model in the Arctic waters based on support vector regression. [2]结果表明，两种图像派生的水深模型都传达了可用于水深测绘应用的有希望的结果。 [1] 基于支持向量回归的北极水域卫星测深模型。 [2]