Proceedings of International Forum for Green Asia 2019
5th International Exchange and Innovation Conference on Engineering & Sciences (IEICES 2019)

GA04 / P16
Spatio-temporal analysis of coastal and marine environments based on
local remote sensing and photogrammetry
Yukun WANG
IGISES, Kyushu University
Email: ou@esst.kyushu-u.ac.jp,
Abstract: In coastal and marine environments, physical and chemical quantities such as flow, wave, temperature, andsubstance are closely related to biological ones, but the integration of these data is still insufficient at present. As apowerful method for acquiring environmental information, local remote sensing technology is attracting attention now.
In that method, it is necessary to develop highly accurate and efficient methods for image processing. The purpose ofthis study is to examine the photogrammetry method on the basis of observation data obtained from local remote sensing
by ship and UAV. We adopted the Shape from Shading (SFS) algorithm to build 3D/4D wave surface models, and theStructure from Motion (SFM) algorithm was also used to make a 3D beach topography model. Such attempts areimportant for integrated evaluation of local remote sensing with spatio-temporal environmental information.
Keywords: Local remote sensing; 3D/4D model; Shape from Shading (SFS); Structure from Motion (SFM);
Coastal and marine environments
1. INTRODUCTION
The change of land use and the increase of energy
consumption in urban areas, and serious environmental
deterioration in living areas have been caused inassociation with the rapid development of society. In
addition, though highly accurate observation data serveas the basis for advanced use of environmental
information, such data are relatively difficult to acquire.
Figure 1 shows a map of the concept in this study. In
recent years, as important technologies working incollaboration with GPS and Internet, UAV (UnmannedAir Vehicles) [1] and IoT (Internet of Things) have beendeveloped accordingly. These technologies also give
great impacts on the fields of coastal and marine
environments, and they will become increasingly
important in the future so as to visualize and utilize
environmental information for sustainable development
in coastal regions.
In addition to numerical simulation, the local remotesensing technology which is capable of monitoring
relatively large areas with high resolution is expected toprogress in the fields of coastal and marine environments.
Hence, observation technique by UAV like drone to
extract environmental information from image data has
been become important, and information science such asimage processing, machine learning, and deep learning
will be integrated with the local remote sensing
technologies. Therefore, the importance of a newresearch field to be called Environmental
Hydroinformatics[2], which treat the environment andinformation integrally, will increase greatly in the future.
Our research group have made a collaborative researchwith Fukuoka Prefecture's Fisheries Agency to obtainwave properties from digital camera image data on thesea surface. Moreover, we received image data of beach
topography by using UAV. In this study, we used
observation data of coastal and marine environments
such as wave properties and beach topography. Figure 2
shows the ship used for taking wave images and the UAV
we used in this study.

Fig. 1. Map of research concept

Fig. 2. Observation tools for local remote sensing(a) Camera on ship (b) Ship: TSUKUSHI(c) UAV: Phantom4-7-Fig. 3. Conceptual diagram of “SFX” measurements(a)Fig. 4. 3D beach topography modeling by SFM

(b)

(c)

Fig. 5. 3D/4D wave modeling by SFS(a) Original image data(b) 3D wave model(c) Wave height distribution

Fig. 6. Marine Geographic Information System
improve its accuracy, we will carry out laboratory wave
experiments to get the quantitative relation between thewave model and the wave height distribution. As
research targets for integrated evaluation of local remotesensing with spatio-temporal environmental information,
image data of sea surface acquired by drone and offshore
facilities will be utilized. And as Fig. 6 shows that wewill also consider the extraction of environmental
information through machine learning and deep learning,
and integration technology based on MGIS[5].

2. RESEARCH METHODSWith the continuous developments of computer visionand virtual reality, the three-dimensional reconstructionof image gradually becomes one of the significant research
topics of computer science, and it plays an increasingly
important role and function in many fields. At present,
multiple reconstruction technologies have formed that are
abled by a joint name – “Shape/Structure from X”
technology and the X could be the sports, texture, profile,
shadow and so on. In this study, we adopted the Shapefrom Shading (SFS) algorithm to build 3D/4D wave
surface models[3], and the Structure from Motion (SFM) [4]algorithm was used to make a 3D beach topographymodel. Figure 3 displays the conceptual diagram of “SFX”
measurements. In accordance with the light and shadevariation of the object surface in the image, SFS algorithm
recovers the relative heights of all points on the objectsurface which means to recover the object height in linewith the grey information of the image surface to build the3D model.

REFERENCES[1] Nex, Francesco, and Fabio Remondino. "UAV for 3D
mapping applications: a review." Applied geomatics
6.1 (2014): 1-15.
[2] Pinho, J. L. S., JM Pereira Vieira, and JS Antunes Do
Carmo. "Hydroinformatic environment for coastal
waters hydrodynamics and water quality modelling."
Advances in Engineering Software35.3-4 (2004):
205-222.
[3] Remondino, F., Barazzetti, L., Nex, F., Scaioni, M.,& Sarazzi, D. (2011). UAV photogrammetry formapping and 3d modeling–current status and future
perspectives. International Archives of thePhotogrammetry, Remote Sensing and Spatial
Information Sciences, 38(1), C22.
[4] Xiao, Jianxiong, Andrew Owens, and Antonio
Torralba. "Sun3d: A database of big spaces
reconstructed using sfm and object labels."
Proceedings of the IEEE International Conference on
Computer Vision. 2013.
[5] Carpenter, K. E., & Springer, V. G. The center of thecenter of marine shore fish biodiversity: the Philippine
Islands. Environmental biology of fishes, (2005). 72(4),467-480.

3. RESULTS AND DISCUSSION
The 3D beach model reconstructed in this study isshown in Fig. 4. In addition, Fig. 5 shows the 3D wave
surface model and wave height distribution, but at thisstage, the calibration of the wave height in the wave
model has not been made. In the future research process,a new calibration method will be provided to quantify thewave height information in the model. The GNSS will
be used to improve the accuracy of 3D topographic modelof coastal beach environment.
Stated above, we have already made the modeling of
the 3D/4D wave and the coastal beach topography. Inorder to make the calibration of 3D wave model and-8-