scholarly journals Built-Up Growth Impacts on Digital Elevation Model and Flood Risk Susceptibility Prediction in Muaeng District, Nakhon Ratchasima (Thailand)

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1496 ◽  
Author(s):  
Patiwat Littidej ◽  
Nutchanat Buasri
Keyword(s):  
Land Use ◽  
Digital Elevation Model ◽  
Flood Risk ◽  
Linear Regression Method ◽  
Factors Affecting ◽  
Digital Elevation ◽  
Development Plans ◽  
Elevation Model ◽  
Major Factors ◽  
Spatial Locations

The transformation of land-use and land cover in Nakhon Ratchasima province, Thailand has rapidly changed over the last few years. The major factors affecting the growth in the province arise from the huge expansion of developing areas, according to the government’s development plans that aim to promote the province as a central business-hub in the region. This development expansion has eventually intruded upon and interfered with sub-basin areas, which has led to environmental problems in the region. The scope of this study comprises three objectives, i.e., (i) to optimize the Cellular Automata (CA) model for predicting the expansion of built-up sites by 2022; (ii) to model a linear regression method for deriving the transition of the digital elevation model (DEM); and (iii) to apply Geographic Weighted Regression (GWR) for analyzing the risk of the stativity of flood areas in the province. The results of this study show that the optimized CA demonstrates accurate prediction of the expansion of built-up areas in 2022 using Land use (LU) data of 2-year intervals. In addition, the predicting model is generalized and converged at the iteration no. 4. The prediction outcomes, including spatial locations and ground-water touch points of the construction, are used to estimate and model the DEM to extract independent hydrology variables that are used in the determination of Flood Risk Susceptibility (FRS). In GWR in the research called FRS-GWR, this integration of quantitative GIS and the spatial model is anticipated to produce promising results in predicting the growth and expansion of built-up areas and land-use change that lead to an effective analysis of the impacts on spatial change in water sub-basin areas. This research may be beneficial in the process of urban planning with respect to the study of environmental impacts. In addition, it can indicate and impose important directions for development plans in cities to avoid and minimize flood area problems.

scholarly journals Analysis of Landslide Prone Areas in Tampahan, Toba Samosir Regency, North Sumatra Province

2020 ◽  
Vol 1 (1) ◽  
pp. 25-30
Author(s):  
Winda Lestari Turnip
Keyword(s):  
Land Use ◽  
Digital Elevation Model ◽  
Spatial Data ◽  
Field Data ◽  
Class Interval ◽  
Digital Elevation ◽  
Elevation Model ◽  
North Sumatra ◽  
Toba Caldera

The topography of the Tampahan area which tends to be steep and dominated by tuff lithology can result in a landslide. The intensity of landslides and the resulting losses can be reduced by the analysis of landslide-prone areas in Tampahan. The administration of the area is located in Toba Samosir Regency, North Sumatra Province which is included in the Toba Caldera Region. Analysis of landslide-prone areas is carried out with five parameters namely slope, land use, morphological elevation, lithology, and rainfall. The data processed in this analysis comes from field data, DEMNas (National Digital Elevation Model), and other spatial data. Classification of each parameter and weighting based on literature is away in the analysis of landslide-prone areas of Tampahan. Then do each parameter overlay to get the value of landslide-prone and distinguished based on the calculation of the landslide class interval. The results are divided into five classes that are prone to landslides, namely classes not prone (1-1,8), rather prone (1,8-2,6), quite prone (2,6-3,4), prone (3,4-4,2), and very prone (4,2-5). Based on the analysis that has been done, some areas are very prone to landslides in the southeast while areas that are not prone to landslides are in the southwest of the study area. Therefore, landslide-prone studies are categorized as high landslides with almost 60% coverage of the study area.

scholarly journals Improving the Accuracy of Open Source Digital Elevation Models with Multi-Scale Fusion and a Slope Position-Based Linear Regression Method

2018 ◽  
Vol 10 (12) ◽  
pp. 1861 ◽  
Author(s):  
Yu Tian ◽  
Shaogang Lei ◽  
Zhengfu Bian ◽  
Jie Lu ◽  
Shubi Zhang ◽  
...  
Keyword(s):  
Linear Regression ◽  
Data Fusion ◽  
Digital Elevation Model ◽  
Regression Method ◽  
Slope Position ◽  
Surface Model ◽  
Linear Regression Method ◽  
Multi Scale ◽  
Digital Elevation ◽  
Elevation Model

The growing need to monitor changes in the surface of the Earth requires a high-quality, accessible Digital Elevation Model (DEM) dataset, whose development has become a challenge in the field of Earth-related research. The purpose of this paper is to improve the overall accuracy of public domain DEMs by data fusion. Multi-scale decomposition is an important analytical method in data fusion. Three multi-scale decomposition methods—the wavelet transform (WT), bidimensional empirical mode decomposition (BEMD), and nonlinear adaptive multi-scale decomposition (N-AMD)—are applied to the 1-arc-second Shuttle Radar Topography Mission Global digital elevation model (SRTM-1 DEM) and the Advanced Land Observing Satellite World 3D—30 m digital surface model (AW3D30 DSM) in China. Of these, the WT and BEMD are popular image fusion methods. A new approach for DEM fusion is developed using N-AMD (which is originally invented to remove the cycle from sunspots). Subsequently, a window-based rule is proposed for the fusion of corresponding frequency components obtained by these methods. Quantitative results show that N-AMD is more suitable for multi-scale fusion of multi-source DEMs, taking the Ice Cloud and Land Elevation Satellite (ICESat) global land surface altimetry data as a reference. The fused DEMs offer significant improvements of 29.6% and 19.3% in RMSE at a mountainous site, and 27.4% and 15.5% over a low-relief region, compared to the SRTM-1 and AW3D30, respectively. Furthermore, a slope position-based linear regression method is developed to calibrate the fused DEM for different slope position classes, by investigating the distribution of the fused DEM error with topography. The results indicate that the accuracy of the DEM calibrated by this method is improved by 16% and 13.6%, compared to the fused DEM in the mountainous region and low-relief region, respectively, proving that it is a practical and simple means of further increasing the accuracy of the fused DEM.

scholarly journals The impact of digital elevation model and land use spatial information on Hydrologic Simulation Program-FORTRAN – predicted stream flow and sediment uncertainty

2013 ◽  
Vol 16 (5) ◽  
pp. 989-1003 ◽  
Author(s):  
Huiliang Wang ◽  
Xuyong Li ◽  
Wenzan Li ◽  
Xinzhong Du
Keyword(s):  
Land Use ◽  
Digital Elevation Model ◽  
Spatial Resolution ◽  
Simulation Program ◽  
Hydrologic Simulation ◽  
Hspf Model ◽  
Sediment Loads ◽  
Digital Elevation ◽  
Elevation Model ◽  
The Impact

The Hydrologic Simulation Program-FORTRAN (HSPF) model is widely used to develop management strategies for water resources. The spatial resolution of the input data used to parameterize the HSPF model may lead to uncertainty in model outputs. In this study, we evaluated the impact of the spatial resolution of the digital elevation model (DEM) and land use data on uncertainty in HSPF-predicted flow and sediment. The resolution of DEMs can affect stream length, watershed area, and average slope, while the resolution of land use data can influence the distribution of land use information. Results showed that DEMs and land use maps with finer resolutions generated higher flow volumes and sediment loads. There was a non-linear relationship between changes in resolution of the DEM and land use data and changes in the uncertainty of predicted flow and sediment loads. Relative error was used to describe model uncertainty and the probability density function was used to estimate these uncertainties. The best-fit distributions of uncertainty in modeled flow and sediment related to DEM and land use data resolution were the generalized Pareto distribution and the Johnson SB distribution, respectively. The results of this study provide useful information for better understanding and estimating uncertainties in the HSPF model.

scholarly journals GIS-Based Study To Develop Landslide Susceptibility Zonation Map Of District Mandi, Himachal Pradesh

2021 ◽  
Author(s):  
Sachin Verma ◽  
Vidya Sagar Khanduri
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Digital Elevation Model ◽  
Landslide Susceptibility ◽  
Drainage Density ◽  
Land Use Land Cover ◽  
Landslide Susceptibility Zonation ◽  
Zonation Map ◽  
Digital Elevation ◽  
Elevation Model

Abstract Rising Incidents of landslide at district Mandi is issue of concern in Himachal Pradesh. Every year many people losses their life and property in these landslide event. This study is conducted with aim to preparation of landslide susceptibility zonation map of district Mandi using method of frequency ratio. Causative factor of landslide involved in preparation of Landslide susceptibility zonation map is Lithology, Slope, Drainage density, Aspect and Land use land cover. Slope, Drainage density, Aspect map are extracted through digital elevation model. Source of Digital elevation model used here is based on SRTM data whereas lithology map is based on data of geological survey of India. Land use land cover map is extracted by images of Landsat 8 satellite. Total of 52 existing landslides are used to model final map. LSZ map show 40.42% area is falling under medium susceptibility class, 34.5 % under low and 25.07% is under high susceptibility class which cover tehsils Mandi, Chachyot, Thunag and some part of Padhar, Aut and Bali Chowki. Further to validate these result areas under curve (AUC) method is use which give prediction rate of 76.06%.

Evaluation of Global Digital Elevation Model for Flood Risk Management in Perlis

2018 ◽  
pp. 1007-1017
Author(s):  
Muhammad Faiz Pa’suya ◽  
Ami Hassan Md Din ◽  
Zulkarnaini Mat Amin ◽  
Kamaludin Mohd Omar ◽  
Amir Hamzah Omar ◽  
...  
Keyword(s):  
Risk Management ◽  
Digital Elevation Model ◽  
Flood Risk ◽  
Flood Risk Management ◽  
Digital Elevation ◽  
Elevation Model

scholarly journals The Changes of Runoff with DEM Resolution Variations

2020 ◽  
Vol 8 (6) ◽  
pp. 2531-2538
Keyword(s):  
Land Use ◽  
Digital Elevation Model ◽  
Field Measurement ◽  
Surface Runoff ◽  
Satellite Images ◽  
Rational Method ◽  
The Past ◽  
Digital Elevation ◽  
Elevation Model ◽  
Upstream Catchment

Currently there has been a research gap in providing sufficient and reliable data for the estimation of surface runoff from ungauged catchment in Batang Kuranji watershed, City of Padang, West Sumatera, Indonesia. The need for such data arose from the fact that land cover changes occur rapidly in the past 20 years, and flash flood and river degradation have been experienced at an alarming scale. However, due to lack of discharge data from upstream catchment, modelling catchment response to the effect of land use changes is hampered. Field measurement is difficult due to accessibility to river tributaries in the upstream catchment. Therefore, the use of digital satellite images and digital elevation model is studied with various DEM (Digital Elevation Model) resolutions for the first time in this catchment. This catchment is situated from 95 to 1858 m above sea level with an annual rainfall of 3440 mm. This watershed is classified as steep with a watershed that has a slope of more than 40% reaching 37.01% of the entire Kuranji watershed area. This study used 30 m and 8 m DEM. Secondary data were gathered from satellite images such as MODIS (MODerate resolution Imaging Spectroradiometer) Land Use. Precipitation data were gathered from three rain gauging stations in or nearby the catchment. Stream geometry data were obtained from the Provincial Office for River Management. Annual discharge and 100-year discharge are calculated using rainfall data for the past 20 years. Runoff discharge was calculated using rational method and SCS (Soil Conservation Services) method. Overall, computed discharge decreases as DEM resolution decreases with percentage varies between 0.98% to 1.76%. The biggest difference between DEM of 30 m and 8 m was shown by the Rational method. However, the difference between years is inconsistent with methods used with no significant pattern. Using the rational method, the biggest difference was by 18.73 m3/s, making up 1.76%. With SCS-CN, however, the biggest difference was 14 m3/s or 1.32% and the smallest was 0.98%. Validation with field measurement suggests that the 8-m DEM varies only 0.16% with actual discharge. Therefore, in the Kuranji catchment, the SCS method coupled with 8-m DEM was found to be accurate for the estimation of surface runoff

scholarly journals OPTIMAL BENCH MARK DISTRIBUTION TO MONITOR SOUTHERN SEGMENT OF SUMATRAN FAULT

GeoEco ◽  
2019 ◽  
Vol 5 (2) ◽  
pp. 160 ◽  
Author(s):  
Satrio Muhammad Alif
Keyword(s):  
Land Use ◽  
Digital Elevation Model ◽  
Fault Zone ◽  
Bench Mark ◽  
Optimal Monitoring ◽  
Digital Elevation ◽  
Elevation Model ◽  
Sumatran Fault ◽  
Stress Accumulation ◽  
Research Show

<p><em>The s</em><em>outhern segment of</em><em> a</em><em> Sumatran fault zone </em><em>was</em><em> one of </em><em>the </em><em>sources of earthquakes in Lampung Province. The source of hazard c</em><em>ame</em><em> from stress accumulation of crust</em><em>,</em><em> which can be derived from movement of </em><em>bench mark</em><em> in surface.</em><em> Lack of research in southern segment </em><em>was</em><em> caused by small numbers of monitoring bench mark. </em><em>This research  show</em><em>n</em><em> optimal monitoring bench mark distribution by considering existing bench mark and location which is decent and representative to monitor Sumatran Fault Zone movement by considering on its position relative to Sumatran Fault Zone, earthquake history, Digital Elevation Model and land use.</em> <em>Decent location </em><em>was</em><em> determined by overlaying land use and slope processed from Digital Elevation Model</em><em>.</em> <em>Representative location was determined by taking into account the distance to Sumatran Fault Zone and earthquake history.</em> <em>Very decent location is around 10.5 percent of the total area. Very representative location is around 44.5 percent of the total area.</em> <em>There are total 15 planned bench marks location to make southern Segment of Sumatran Fault Zone monitoring bench mark more optimal.</em><em></em></p>

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