ASSESSING THE ACCURACY OF SHALLOW WATER DEPTH ESTIMATION BY USING MULTISPECTRAL SATELLITE IMAGES

IF 0.7 Q4 GEOGRAPHY, PHYSICAL

Geographia Technica Pub Date : 2021-10-18 DOI:10.21163/gt_2021.163.14

R. S. Dewi, A. Rizaldy, P. Hartanto, Suprajaka Suprajaka

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引用次数: 1

Abstract

: Timely and accurate bathymetry information is needed to support an effective policy on utilization and management of coastal natural resources. Satellite derived bathymetry (SDB) has been widely considered as an advanced and low-cost method for shallow water depth estimation. This is due to the availability of multi-temporal and multi-resolution satellite data. This study focuses on evaluating the accuracy of satellite derived bathymetry derived from multispectral images recorded by various sensors with various spatial resolution. The study area is located in a small island nearby Morotai Island, Indonesia. Four SDB models were compared. The implementation of the SDB model was carried out by combining echo-sounding measurements and the reflectance of blue, green, red, and near infrared bands of three satellite images (World View 2, Sentinel 2A and Landsat 8). Our findings reveal that all three satellite images performed well in assessing SDB at various spatial and spectral resolution, however, the use of high-resolution imagery did not always improve accuracy, for example when using SVM (Support Vector Machine). When using RF (Random Forest), Sentinel 2A produced the best accuracy and when using GAM (Generalized Additive Model), the most feasible result was generated only by using WorldView 2 image. In all cases, RF performed well and provided the most accurate SDB prediction.

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利用多光谱卫星图像评估浅水深度估计的准确性

：需要及时和准确的测深信息，以支持制定有效的沿海自然资源利用和管理政策。卫星测深法（SDB）被广泛认为是一种先进且低成本的浅水深度估计方法。这是由于可以获得多时相和多分辨率的卫星数据。这项研究的重点是评估从各种空间分辨率的传感器记录的多光谱图像中获得的卫星测深的准确性。研究区域位于印度尼西亚莫罗泰岛附近的一个小岛上。比较了四种SDB模型。SDB模型的实施是通过结合回声探测测量和三个卫星图像（世界视图2号、哨兵2A号和陆地卫星8号）的蓝色、绿色、红色和近红外波段的反射率进行的。我们的研究结果表明，所有三个卫星图像在不同的空间和光谱分辨率下都能很好地评估SDB，然而，高分辨率图像的使用并不总是能提高准确性，例如，当使用SVM（支持向量机）时。当使用RF（随机森林）时，Sentinel 2A产生了最好的精度，而当使用GAM（广义相加模型）时，只有使用WorldView 2图像才能产生最可行的结果。在所有情况下，RF表现良好，并提供了最准确的SDB预测。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Geographia Technica GEOGRAPHY, PHYSICAL-

CiteScore

2.30

自引率

14.30%

发文量

期刊介绍： Geographia Technica is a journal devoted to the publication of all papers on all aspects of the use of technical and quantitative methods in geographical research. It aims at presenting its readers with the latest developments in G.I.S technology, mathematical methods applicable to any field of geography, territorial micro-scalar and laboratory experiments, and the latest developments induced by the measurement techniques to the geographical research. Geographia Technica is dedicated to all those who understand that nowadays every field of geography can only be described by specific numerical values, variables both oftime and space which require the sort of numerical analysis only possible with the aid of technical and quantitative methods offered by powerful computers and dedicated software. Our understanding of Geographia Technica expands the concept of technical methods applied to geography to its broadest sense and for that, papers of different interests such as: G.l.S, Spatial Analysis, Remote Sensing, Cartography or Geostatistics as well as papers which, by promoting the above mentioned directions bring a technical approach in the fields of hydrology, climatology, geomorphology, human geography territorial planning are more than welcomed provided they are of sufficient wide interest and relevance.