Simulation of Coastal Erosion Model to Support Disaster Mitigation in Coastal Sayung, Demak District

Coastal Sayung, Demak has occurred agricultural land and mangroves conversion for opening the ponds. Land use change inflict 2 small villages sink, namely Tambaksari (1997) and Rejosari (2004). The small villages are damaged by coastal erosion. This coast is an area affected by tides. The study aims to evaluate the erosion in coastal Sayung, by simulation model with mathematic model. The simulation results are calibrated with March and June 2016 bathymetry data. Bathymetry data is obtained by echosounder to acquiring contour depth. Wind data was obtained from NOAA for 10 years. Sediment sampling results indicate the type of silt (72%), clay (24%), and fine sand (4%), with specific gravity 1.51 – 1.85 tons/m3. The data used for hydrodynamics and erosion modeling with mathematic model. The simulation results indicate the greatest erosion value occurs in the transition season I, which is 94,000 m3. Patterns of erosion strongly influenced by the current patterns of a particular season. When the West, current and erosion patterns move towards northeast, and otherwise with the East. The most eroded villages are Sriwulan and Bedono, then Timbulsloko, and the smallest is Surodadi. The results of this study can be used to support disaster mitigation in the coastal Sayung, Demak. Keywords: bathymetry, coastal Sayung, erosion, mathematic model, sedimen

Hydrodynamics Features and Coastal Vulnerability of Sayung Sub-District, Demak, Central Java, Indonesia

The Sayung sub-district is an abrasion area in Demak Regency that is mostly affected by sea level rise. The purpose of this research is to determine the features of hydrodynamics and coastal dynamics occurrence in the sub-district of Sayung. Collecting field data/information and modeling approach (tides, waves, currents, weather and coastline changes) have been done in Sayung, Demak. The wave height in the eastern coast is the highest. The significant wave height in 2004 was greater than March 2016 showing that in 2004 the wind energy transfers were larger than 2016. The refraction coefficient in 2016 for all directions was the greatest from the west at the depth of 8 m and the smallest one was identified in the south. The refraction coefficient in 2004 for any direction yielded the largest value in the southwest at the depth of 2 m and the smallest one was identified the south as well. During a cycle of tidal fluctuation, it occurs twice flood and ebb events. The maximum depth is 6.5 m located about 3.8 km from the coastline. The sediment thickness reached 564,886.39 m3. Coastline changes occurred in 2003 and started to gain sedimentation in 2015. Data and information produced can be useful as a basis for further developments to mitigate abrasion and to create policy-brief in managing coastline affected abrasion even though some improvement efforts have been made

Extracting Urban Morphology for Atmospheric Modeling from Multispectral and SAR Satellite Imagery

This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1) Digital Elevation Model (DEM) and 2) land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP).Peer reviewe

Fuzzy Classification for Shoreline Change Monitoring in a Part of the Northern Coastal Area of Java, Indonesia

This study presents an unsupervised fuzzy c-means classification (FCM) to observe the shoreline positions. We combined crisp and fuzzy methods for change detection. We addressed two perspectives of uncertainty: (1) uncertainty that is inherent to shoreline positions as observed from remote sensing images due to its continuous variation over time; and (2) the uncertainty of the change results propagating from object extraction and implementation of shoreline change detection method. Unsupervised FCM achieved the highest kappa (κ) value when threshold (t) was set at 0.5. The highest κ values were 0.96 for the 1994 image. For images in 2013, 2014 and 2015, the κ values were 0.95. Further, images in 2003, 2002 and 2000 obtained 0.93, 0.90 and 0.86, respectively. Gradual and abrupt changes were observed, as well as a measure of change uncertainty for the observed objects at the pixel level. These could be associated with inundations from 1994 to 2015 at the northern coastal area of Java, Indonesia. The largest coastal inundations in terms of area occurred between 1994 and 2000, when 739 ha changed from non-water and shoreline to water and in 2003–2013 for 200 ha. Changes from water and shoreline to non-water occurred between 2000 and 2002 (186 ha) and in 2013–2014 (65 ha). Urban development in flood-prone areas resulted in an increase of flood hazards including inundation and erosion leading to the changes of shoreline position. The proposed methods provided an effective way to present shoreline as a line and as a margin with fuzzy boundary and its associated change uncertainty. Shoreline mapping and monitoring is crucial to understand the spatial distribution of coastal inundation including its trend