CLASSIFICATION OF THE SURFACE SEDIMENTARY FACIES BASED ON MULTI-SENSOR REMOTELY SENSED DATA IN HWANG-DO TIDAL FLAT

Title
CLASSIFICATION OF THE SURFACE SEDIMENTARY FACIES BASED ON MULTI-SENSOR REMOTELY SENSED DATA IN HWANG-DO TIDAL FLAT
Author(s)
김계림; 유주형; 이윤경; 김범준; 이승국
KIOST Author(s)
Kim, Kye Lim(김계림)Ryu, Joo Hyung(유주형)
Publication Year
2016-04-21
Abstract
The research to classify intertidal surface sedimentary facies with remote sensing data has been performed. The earlier studies have some limitation (e.g., single-sensor data and interstitial moisture influence) that the classification map is not detailed to analysis depositional environment. Therefore, the purpose of this study was minutely to mapping the surface sedimentary facies by analysing the tidal channel, topography with multi-sensor remotely sensed data and in-situ data(sheer strength, surface remnant water, grain-size). The classification methodology is based on hierarchical decision tree. First, the water segmentation is pre-processed by water index and the shellfish beds are separated by using the spectral response and textural featuers with Kompsat-3 and TanDEM-X. Second, the separated area is divided into 3-types sedimentary facies (sand/mixed/mud) with a thresholding technique applied to tidal channel including fractal dimension and density. Finally, second result is further subdivided by DEM and wetness with Landsat 7 and UAV (DEM) related to surface remnant water. The fractal dimension was more than 1.6 in the mud flat, 1.3 - 1.6 in the mixed and less than 1.3 in the sand flat. The elevation was more than 3.9m in the mud flat, 3.1m - 3.9m in the mixed and less than 3.1 m in the sand flat. Each type was subdivided into classes by DEM and wetness related to surface remnant water. The mud flat was clasis not detailed to analysis depositional environment. Therefore, the purpose of this study was minutely to mapping the surface sedimentary facies by analysing the tidal channel, topography with multi-sensor remotely sensed data and in-situ data(sheer strength, surface remnant water, grain-size). The classification methodology is based on hierarchical decision tree. First, the water segmentation is pre-processed by water index and the shellfish beds are separated by using the spectral response and textural featuers with Kompsat-3 and TanDEM-X. Second, the separated area is divided into 3-types sedimentary facies (sand/mixed/mud) with a thresholding technique applied to tidal channel including fractal dimension and density. Finally, second result is further subdivided by DEM and wetness with Landsat 7 and UAV (DEM) related to surface remnant water. The fractal dimension was more than 1.6 in the mud flat, 1.3 - 1.6 in the mixed and less than 1.3 in the sand flat. The elevation was more than 3.9m in the mud flat, 3.1m - 3.9m in the mixed and less than 3.1 m in the sand flat. Each type was subdivided into classes by DEM and wetness related to surface remnant water. The mud flat was clas
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/24875
Bibliographic Citation
International Symposium of Remote Sensing 2016, pp.1, 2016
Publisher
ISRS
Type
Conference
Language
English
Publisher
ISRS
Related Researcher
Research Interests

Coastal Remote Sensing,RS based Marine Surveillance System,GOCI Series Operation,연안 원격탐사,원격탐사기반 해양감시,천리안해양관측위성 운영

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