Shoreline Dynamics in East Java Province, Indonesia, from
2000 to 2019 Using Multi-Sensor Remote Sensing Data
Faculty of Geography, Universitas Gadjah Mada
PDUPT’s Research Team, 2021
Contents
Introduction01
Methodologies02
Results and Discussions03
Conclusions04
Introduction01
Introduction
•Coastal regions are one of the most vulnerable areas to the effects of global warming, The increase in sea
level affects shorelines and generate coastal erosion
•In Indonesia, the coastal areas are still inhabited by people as settlements, and the development of
settlements in the coastal area are still increasing
•Some dense populated big cities, (i.e. Semarang, Jakarta, Surabaya) are prone to the coastal erosion and
Coastal Flooding
•The dynamic of Shoreline is relatively understudied, despite of the abundance of datasets and the
availability of easily accessible cloud computing platforms (i.e Google Earth Engine)
Research Objectives
2
1
Using the cloud computing platform (the Google Earth Engine)
and utilizing remote sensing datasets (i.e., Landsat-5 TM,
Landsat-7 ETM, Landsat-8 OLI, and Sentinel-1) to perform a
regional mapping of the shoreline dynamics in a part of East
Java Province
Monitor the regional shoreline dynamics and the affected land
use in a part of the eastern coastal areas of East Java Province
from 2000 to 2019 at 4- to 5-year intervals
Methodologies02
Study area
•Our study area is a part
of Eastern region of Java
Island (shown by yellow
line)
Datasets
Variables from remote sensing data used for classification for each years (5 and 4 years interval)
Research Flowchart
2
1
•Identifying Shoreline Change in
2000-2005-2005-2015-2019,
•First, using GMO Maxent and
Random Forest algorithm
classifying Land, water, and
Suspended Sediment in
Google Earth Engine
•Identifying Shoreline Change
by using DSAS tools plugin in
ArcGIS
•Identifying Land use land cover in
2000 and 2019, to see the land use
change in eroded and accreted
region
Results and Discussions03
Classification Result
•GMO maxent’s results are used as a basis toconduct shoreline change analysis, because it’s
overall accuracy are better than Random Forest Algorithm (despite classifying 3 classes) in most
years maps
•Manual refining stillconducted for each results to minimize errors.
Classification of land and water bodies (seawater in blue, turbid water in yellow) in the year 2000 by (A) RF with 80 trees (OA: 84%) and (B) GMO-
Maxent (OA: 93.6%)
Shoreline Changes from 2000 to 2019
•Out study identified regions of both
major erosion and major accretion in
the northwestern part of East Java
Province, which represents the delta
of the Bengawan Solo river and
coastal accretion, which represents
the delta of the Brantas/Porong river
Major shoreline changes in (A) the Bengawan Solo delta,
which experienced major erosion and accretion, and (B)
the Brantas/Porong delta, which experienced major
accretion
Shoreline Changes from 2000 to 2019
•The average movement of the shoreline derived from the analysis, was approximately +10.m/year, with some
areas experiencing erosion rates up to -87 m/year and some areas experiencing accretion rates up to 89.85
meter/year
Shoreline Changes from 2000 to 2019
•we found an average shoreline change of +13.28 m/year from 2000 to 2019. The rate of shoreline change
ranged from −19.98 to +111.75 m/year (EPR)
Land Use of the Accretion and Erosion Areas in 2000 to
2019
Based on the land-use classification results and the
shoreline changes in 2000 and 2019, the mangrove
and aquaculture areas were the main affected land-
use classes in those deltas.
Conclusions04
Conclusions
2
1
GMO-Maxent methods can give relatively stable, high
accuracies (84% to 95.2%) when compared with RF methods for
separating land, water bodies and suspended sediment, The
manually refined shoreline generated by the GMO-Maxent method
showed general accretion, at rates of +4.12 (EPR) and +4.26 m/year
(WLR)
Massive changes were found in two deltas: the Brantas/Porong
delta, which underwent major accretion, and the Bengawan Solo
delta, which experienced both major accretion and major erosion.