Watershed is a region inland that group on how the water flow, accumulate, and dischare based on its morphology. Every watershed has its morphometric parameter, and it might affect the flood frequency or hazard in the region. One of the parameters is the circularity ratio or Rc, the ratio of areas of a watershed and a circle with the same circumference/perimeter. There has not been any research that tries to compare the Rc and flood hazard on multiple watersheds. Here we try to calculate the Rc and flood hazard on multiple watersheds on the island of Java. The purpose is to find any correlation and pattern that can explain the rate of flooding using geometric and morphometric characteristics of the watershed. The watershed geometry is acquired from KLHK, and the flood hazard is generated from the Normalized Difference Flood Index (NDFI) of multi-temporal Sentinel-1 SAR Imagery. The result shows there are two patterns of relationship found on low (0 - 0.2) and high (0.6 - 0.8) Rc. These two groups show that higher Rc means a lower flood area but a higher flood hazard score. This pattern does not show up in the middle-value groups of Rc (0.2 - 0.6). Using other flood data or regions might show a different result.
Purwodadi and Bagelen sub-districts are areas that are frequently inundated by floods from the overflow of the Bogowonto River. These inundations can disrupt community activities and has an impact on material, social and economic damage. Therefore, it is necessary to have an effective and efficient flood potential in the Bogowonto watershed. The purpose of this study is to extract data of land use and river geometry using remote sensing data and geographic information systems for estimating flood discharges and constructing flood inundation spatial models using HEC-RAS and ArcGIS software in return periods 1, 2, 5, 10, 20, 50, and 100 years. Modeling is doing with integrating HEC-RAS and ArcGIS software. This study generally carried out hydrological and hydraulic modeling in the Bogowonto watershed. Hydrological modeling was carried out to convert rainfall data into flood discharge using the Nakayasu Synthetic Unit Hydrograph. The data used is the maximum daily rainfall for 2010-2022 from 10 rain stations in the Bogowonto watershed. Hydraulic modeling was carried out to simulate flood inundation using the HEC-RAS software with 2D unsteady flow simulation. The data required in this study are river geometry, design flood discharge, and Manning’s values. River geometry data and Manning’s values were obtained from digitizing remote sensing data in the form of DEMNAS and Sentinel-2A. The results of the modeling were analyzed and visualized using ArcGIS. This study shows that remote sensing data and geographic information systems can extract land use and river geometry data, which can then be used in flood modeling.
KEYWORDS: Landslide (networking), Data modeling, Raster graphics, Java, Roads, Data conversion, Digital imaging, Data processing, Agriculture, Analytical research
Landslide is caused by meteorological and geomorphological factors. Landslide is one of the most common disaster that occur in Indonesia. Purworejo is one of the potential area that could be experiencing landslides, because the geomorphological conditions which are included in Menoreh Hills are geographically sloping to very steep. Based on the Indonesian Disaster Information Data (DIBI) and the National Disaster Management Agency (BNPB) in the last five years from 2014 to April 2019 there have been 64 landslides in Purworejo. To reduce the impact of landslide, effective evacuation routes are needed. Determining of evacuation routes can be done in various methods, one of methods is use a spatio-cost approach. The purpose of this research is to determine the most effective evacuation routes to reduce the impact of landslide. Spatio-cost parameters obtained by certain paramaters. The parameters are physical parameters and some social parameters derived from the appearance on the surface of the earth, such as housing, number of population, land use, slope direction, roads and also the wide of the roads. These parameters are processed to look for evacuation routes using Least Cost Path (LCP) method. The expected result of this research is evacuation routes that can help people around disaster-prone areas to prepare. This on going research is important to improve disaster manajemen in Indonesia, especially for landslide in Bruno, Purworejo, Central Java.
KEYWORDS: Landslide (networking), Data modeling, Visual process modeling, Visualization, 3D modeling, 3D visualizations, Information visualization, Roads, Raster graphics, Associative arrays
Indonesia is one of the disaster-prone countries. Based on the Indonesian Disaster Information Data (DIBI) and the National Disaster Management Agency (BNPB) in the last five years from 2014 to April 2019 there have been 65 landslides in Purworejo. Landslide is one of the most common disaster that occur in Indonesia. Landslide is caused by meteorological and geomorphological factors. Purworejo is one of the potential area that could be experiencing landslides, because the geomorphological conditions which are included in Menoreh Hills are geographically sloping to very steep. Landslide susceptibility modeling in Purworejo Regency was carried out using three different methods, namely Information Value Model (IVM), Information Value Model-Analytical Hierarchy Process (IVM-AHP) and Information Value Model-Gray Clustering (IVM-GC). Each modeling is conducted using the Natural Breaks (Jenks) method to produce five classes, namely very low, low, medium, high and very high class based on the IVM value of each method. This research’s goal is to visualized 3 maps of modelling results. The visualization used is 3-dimensional mapping. This mapping is intended to make it easier to compare the map results of modeling that have been done before. The expected results of this study are accurate and reliable 3-dimensional visualization to study the advantages and disadvantages of each of the modeling methods used.
Data related to socio-economic activities in Indonesia mostly used statistical data. Statistics for large numbers of socioeconomics will make it difficult to interpret and analyze because it consists of many columns and rows with each value. Geo-visualization is a visualization of data represented in a geographic coordinate system. Socio-economic statistics can be visualized to facilitate the process of spatial analysis data that considers spatial surface of earth. Study area is in Special Region of Yogyakarta. This study aims to (1) Select, test and find out color symbol scheme most effective classification method for choropleth mapping of Demographic Map, (2) Mapping happiness profile of population using small area estimation method, (3) Analyzing tourist trends based on Instagram data using space time cube visualization. Secondary data used are population and happiness, while primary data uses social media data for tourist visualization. Geo-visualization of population and happiness used choropleth method. In social media geo-visualization for tourists using space time cube geo-visualization with hexagonal tessellation cells. The results obtained are population maps with best classification scheme, happiness maps at different scale levels, and tourist map using space time cube in Yogyakarta Special Region.
Map can show information needed by map users from various scientific fields, especially in Indonesia. Effective maps can help users understand. One of the factors that influence the effectiveness of map reading is the color symbol scheme used in symbolization. Effectiveness’ study of color symbol scheme applied on choropleth mapping. Choropleth map is using population density data in Special Region of Yogyakarta. The selection of the study area in the Special Province of Yogyakarta is because the Special Region of Yogyakarta is one of the provinces in Indonesia which has a fairly high population density in the area of 3,185.80 km2 . In 2016, the population density of the Special Province of Yogyakarta ranked 4th in the Indonesian Statistics 2017 by the Central Bureau of Statistics, which amounted to 1,188 population per km2 . The effectiveness of color symbol schemes adapts the capabilities of each user. This study is expected to be able to study the effect of age group differences on maps with the best color symbol scheme. All scientific field that used choropleth map of population density consist of 2 age groups, those are 20-25 years old and >5 years old respondents. The purpose of this study was to observe age group influence for the most effective color symbol scheme for mapping population density in the Special Region of Yogyakarta. The result of this study shows the difference between age group based on the important aspects of conventional-eye tracking. The important aspects to consider are average answering duration, the accuracy of the answer and easiness level of symbolization readings. The first group (20-25 years) shows map 3 (diverging color scheme) as a map with the most effective color symbol scheme. While group 2 (>25 years) shows map 1 (ArcGIS 10.3 color scheme) as a map with the most effective color symbol scheme. This research is expected to be able to show the influence of age in determining the best color symbol scheme on population density maps so that its effectiveness can be adjusted specifically to map users.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.