scholarly journals MATLAB functions for extracting hypsometry, stream-length gradient index, steepness index, chi gradient of channel and swath profiles from digital elevation model (DEM) and other spatial data for landscape characterisation

2020 ◽  
Vol 7 ◽  
pp. 100033
Author(s):  
Nilesh K. Jaiswara ◽  
Sravan Kumar Kotluri ◽  
Prabha Pandey ◽  
Anand K. Pandey
Keyword(s):  
Digital Elevation Model ◽  
Spatial Data ◽  
Gradient Index ◽  
Stream Length ◽  
Digital Elevation ◽  
Elevation Model

scholarly journals Automated Conflation of Digital Elevation Model with Reference Hydrographic Lines

2020 ◽  
Vol 9 (5) ◽  
pp. 334
Author(s):  
Timofey E. Samsonov
Keyword(s):  
Spatial Analysis ◽  
Digital Elevation Model ◽  
Spatial Data ◽  
Drainage Network ◽  
Map Generalization ◽  
Data Types ◽  
Digital Elevation ◽  
Elevation Data ◽  
Elevation Model ◽  
Different Sources

Combining misaligned spatial data from different sources complicates spatial analysis and creation of maps. Conflation is a process that solves the misalignment problem through spatial adjustment or attribute transfer between similar features in two datasets. Even though a combination of digital elevation model (DEM) and vector hydrographic lines is a common practice in spatial analysis and mapping, no method for automated conflation between these spatial data types has been developed so far. The problem of DEM and hydrography misalignment arises not only in map compilation, but also during the production of generalized datasets. There is a lack of automated solutions which can ensure that the drainage network represented in the surface of generalized DEM is spatially adjusted with independently generalized vector hydrography. We propose a new method that performs the conflation of DEM with linear hydrographic data and is embeddable into DEM generalization process. Given a set of reference hydrographic lines, our method automatically recognizes the most similar paths on DEM surface called counterpart streams. The elevation data extracted from DEM is then rubbersheeted locally using the links between counterpart streams and reference lines, and the conflated DEM is reconstructed from the rubbersheeted elevation data. The algorithm developed for extraction of counterpart streams ensures that the resulting set of lines comprises the network similar to the network of ordered reference lines. We also show how our approach can be seamlessly integrated into a TIN-based structural DEM generalization process with spatial adjustment to pre-generalized hydrographic lines as additional requirement. The combination of the GEBCO_2019 DEM and the Natural Earth 10M vector dataset is used to illustrate the effectiveness of DEM conflation both in map compilation and map generalization workflows. Resulting maps are geographically correct and are aesthetically more pleasing in comparison to a straightforward combination of misaligned DEM and hydrographic lines without conflation.

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.

Estimation of solar radiation from digital elevation model in area of rough topography

2016 ◽  
Vol 13 (5) ◽  
pp. 453-460 ◽  
Author(s):  
Lurwan Mahmoud Sabo ◽  
Norman Mariun ◽  
Hashim Hizam ◽  
Mohd Amran Mohd Radzi ◽  
Azmi Zakaria
Keyword(s):  
Solar Radiation ◽  
Digital Elevation Model ◽  
Spatial Data ◽  
Energy Planning ◽  
Solar Photovoltaic ◽  
Content Type ◽  
Digital Elevation ◽  
Elevation Model ◽  
The Impact ◽  
Topographic Parameters

Purpose The purpose of this study is to evaluate the reliability of the technique for estimating solar radiation in areas of rough topography and to detect the source of error and means for improvement. Design/methodology/approach Spatial data of the study area in the form of digital elevation model (DEM) coupled with geographic information system (GIS) were used to estimate the monthly solar radiation at locations with rough topography. The generated data were compared with measured data collected from all the selected locations using NASA data. Findings The results show that the variation in topographic parameters has a strong influence on the amount of solar radiation received by two close locations. However, the method performed well for solar radiation estimated in the areas of rough topography. Research limitations/implications The proposed approach overestimates the monthly solar radiation as compared with NASA data due to the impact of topographic parameters accounted for by the model which are not accounted by conventional methods of measurements. This approach can be improved by incorporating the reflected component of radiation in the model used to estimate the solar radiation implemented in the GIS. Originality/value The approach of using GIS with DEM to estimate solar radiation enables to identify the spatial variability in solar radiation between two closest locations due to the influence of topographic parameters, and this will assist in proper energy planning and decision making for optimal areas of solar photovoltaic installation.

scholarly journals Impacts of spatial data resolution on simulated discharge, a case study of Xitiaoxi catchment in South China

2009 ◽  
Vol 21 ◽  
pp. 131-137 ◽  
Author(s):  
G. J. Zhao ◽  
G. Hörmann ◽  
N. Fohrer ◽  
J. F. Gao
Keyword(s):  
Land Use ◽  
Cell Size ◽  
Digital Elevation Model ◽  
South China ◽  
Spatial Data ◽  
Input Data ◽  
Grid Size ◽  
Digital Elevation ◽  
Data Resolution ◽  
Elevation Model

Abstract. In this paper we analyse the effects of different spatial input data resolution on water balance simulation using a simple distributed hydrological model: PCR-XAJ model. A data set consisting of land use and digital elevation model at 25 m resolution of Xitiaoxi catchment in South China is used for investigation. The model was first calibrated and validated at 50 m cell size, thereafter an aggregation of the digital elevation model (DEM) and land use maps at 100 m, 200 m, 300 m, 500 m and 1 km are applied to evaluate the effects of spatial data resolution on simulated discharge. The simulation results at a grid size of 50 m show a good correlation between measured and simulated daily flows at Hengtangcun station with Nash-Suttcliffe efficiency larger than 0.75 for both calibration and validation periods. In contrast, the model performs slightly worse at Fanjiacun station. The increasing grid size affects the characteristics of the slope and land use aggregation and causes important information loss. The aggregation of input data does not lead to significant errors up to a grid of 1 km. Model efficiencies decrease slightly with cell size increasing, and more significantly up to the grid size of 1 km.

scholarly journals Creation of digital elevation models for river floodplains

2019 ◽  
pp. 275-284
Author(s):  
A Klikunova ◽  
A Khoperskov
Keyword(s):  
Digital Elevation Model ◽  
Spatial Data ◽  
Shuttle Radar Topography Mission ◽  
Data Depth ◽  
Water Model ◽  
River Floodplains ◽  
Digital Elevation ◽  
Elevation Model ◽  
Small Channels

A procedure for constructing a digital elevation model (DEM) of the northern part of the Volga-Akhtuba interfluve is described. The basis of our DEM is the elevation matrix of Shuttle Radar Topography Mission (SRTM) for which we carried out the refinement and updating of spatial data using satellite imagery, GPS data, depth measurements of the River Volga and River Akhtuba stream beds. The most important source of high-altitude data for the Volga-Akhtuba floodplain (VAF) can be the results of observations of the coastlines dynamics of small reservoirs (lakes, eriks, small channels) arising in the process of spring flooding and disappearing during lowflow periods. A set of digitized coastlines at different times of flooding can significantly improve the quality of the DEM. The method of constructing a digital elevation model includes an iterative procedure that uses the results of morphostructural analysis of the DEM and the numerical hydrodynamic simulations of the VAF flooding based on the shallow water model.

STUDY OF THE LANDSLIDE MORPHOLOGY BASED ON GNSS DATA AND AIRBORNE SOUNDING (ON THE EXAMPLE OF A SECTION OF THE PROTVA RIVER VALLEY)

2018 ◽  
Vol 12 (5-6) ◽  
pp. 50-57 ◽  
Author(s):  
I. S. Voskresensky ◽  
A. A. Suchilin ◽  
L. A. Ushakova ◽  
V. M. Shaforostov ◽  
A. L. Entin ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Geodetic Network ◽  
Aerial Survey ◽  
River Valley ◽  
Ease Of Use ◽  
Digital Elevation ◽  
Loose Deposits ◽  
Positioning Method ◽  
Landslide Body ◽  
Elevation Model

To use unmanned aerial vehicles (UAVs) for obtaining digital elevation models (DEM) and digital terrain models (DTM) is currently actively practiced in scientific and practical purposes. This technology has many advantages: efficiency, ease of use, and the possibility of application on relatively small area. This allows us to perform qualitative and quantitative studies of the progress of dangerous relief-forming processes and to assess their consequences quickly. In this paper, we describe the process of obtaining a digital elevation model (DEM) of the relief of the slope located on the bank of the Protva River (Satino training site of the Faculty of Geography, Lomonosov Moscow State University). To obtain the digital elevation model, we created a temporary geodetic network. The coordinates of the points were measured by the satellite positioning method using a highprecision mobile complex. The aerial survey was carried out using an unmanned aerial vehicle from a low altitude (about 40–45 m). The processing of survey materials was performed via automatic photogrammetry (Structure-from-Motion method), and the digital elevation model of the landslide surface on the Protva River valley section was created. Remote sensing was supplemented by studying archival materials of aerial photography, as well as field survey conducted immediately after the landslide. The total amount of research results made it possible to establish the causes and character of the landslide process on the study site. According to the geomorphological conditions of formation, the landslide refers to a variety of landslideslides, which are formed when water is saturated with loose deposits. The landslide body was formed with the "collapse" of the blocks of turf and deluvial loams and their "destruction" as they shifted and accumulated at the foot of the slope.

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