TY - JOUR
T1 - Assessment of Complementary Medium-Resolution Satellite Imageries for Nearshore Bathymetry Estimation
AU - Misra, Ankita
AU - Ramakrishnan, Balaji
AU - Vojinovic, Zoran
AU - Luijendijk, Arjen
AU - Ranasinghe, Roshanka
PY - 2019/3/7
Y1 - 2019/3/7
N2 - This paper focuses on utilizing Sentinel 2 MSI datasets to generate satellite-derived bathymetry (SDB) maps at a resolution of 10 m for two temporally varying datasets of the study region of Ameland Inlet, located in The Netherlands, by using support vector regression (SVR) technique. The relative performance of Landsat 8 OLI (30 m) datasets with SVR technique is also assessed to demonstrate the complementary nature of these freely available medium-resolution imageries. Further, the root mean square error and mean absolute error between the retrieved and measured bathymetries are estimated and reported to evaluate the capability of SVR in estimating depths. It is evident that the SDBs thus generated using this machine learning approach provide dependable estimations of depths that can further be utilized for various coastal engineering studies.
AB - This paper focuses on utilizing Sentinel 2 MSI datasets to generate satellite-derived bathymetry (SDB) maps at a resolution of 10 m for two temporally varying datasets of the study region of Ameland Inlet, located in The Netherlands, by using support vector regression (SVR) technique. The relative performance of Landsat 8 OLI (30 m) datasets with SVR technique is also assessed to demonstrate the complementary nature of these freely available medium-resolution imageries. Further, the root mean square error and mean absolute error between the retrieved and measured bathymetries are estimated and reported to evaluate the capability of SVR in estimating depths. It is evident that the SDBs thus generated using this machine learning approach provide dependable estimations of depths that can further be utilized for various coastal engineering studies.
KW - Coastal bathymetry
KW - Landsat 8 OLI
KW - Nonlinear
KW - Sentinel 2 MSI
KW - Support vector regression
KW - n/a OA procedure
UR - http://www.scopus.com/inward/record.url?scp=85057610875&partnerID=8YFLogxK
U2 - 10.1007/s12524-018-0920-x
DO - 10.1007/s12524-018-0920-x
M3 - Article
AN - SCOPUS:85057610875
SN - 0255-660X
VL - 47
SP - 537
EP - 540
JO - Journal of the Indian Society of Remote Sensing
JF - Journal of the Indian Society of Remote Sensing
IS - 3
ER -