Academic literature on the topic 'ArcGIS digital elevation data'

Terrain analysis is the quantitative analysis of topographic surfaces. The purpose of a digital terrain system is to provide the digital representation of terrain so that environmental problem like soil erosion may be approached accurately and efficiently through automated means. Traditionally this was (and still is!) being done manually by using topographic/contour maps. With the availability of Digital Elevation Models (DEM) and GIS tools, watershed properties can be extracted by using automated procedures. Remote Sensing and Digital elevation models (DEMs) are known to be very useful data sources for the automated delineation of flow paths, sub watersheds and flow networks for hydrologic modelling and watershed characterization. The digital terrain model was extracted from a 90m resolution Shuttle Radar Topographic Mission (SRTM) of the study area. The SRTM data was corrected by removing voids, striping, tree offsets and random noise. The SRTM DEM data was projected from geographic coordinate WGS 84 to UTM zone 32 of the study area. The 3-D analysis tool of the ArcGIS 10.1 was used for this process. The DEM was processed to obtain the Slope, Contour, Flow direction, Flow accumulation, Flow length, Stream power Index of the study area. The study proved that SRTM elevation dataset has the ability to obviate the lack of terrain data for hydrologic modelling using ArcGIS where appropriate data for terrain modelling and simulation of hydrological processes is unavailable.

The Ms 7.0 Lushan earthquake triggered thousands of landslides. The main purpose of this paper is to present the use of the ASTER GDEM data, an incomplete landslide triggering factors of the M7.0 Lushan earthquake of China based on the ArcGIS platform and the DEM (Digital Elevation Models) technology. The sources of DEM are various. This paper discusses the prevalent DEM data source-ASTER GDEMs characteristic and applying GDEM data on extraction of water system and terrain characteristics of geological disasters using ArcGIS Hydro Tools package. A comprehensive quantitative analysis of the terrain parameters are performed such as elevation, slope, contour, drainage pattern, and thematic maps of geology and geomorphology lineament. These parameters are required as input to applications such as landslide susceptibility analysis.

Goal. The purpose of this paper is to create a tourist GIS of the Sumy oblast using cartographic materials and remote sensing data, as well as the development of new tourist routes in the Sumy oblast by means of modern geoinformation technologies and ArcGIS, ArcGIS Online, and AllTrails software. Method. The main stages of the creation of Sumy oblast tourist GIS were: search and analysis of the of input materials, necessary for the creation of a tourist GIS; create of the structural block diagram of research works; Satellite image processing, in particular the creation of synthesized images and the use of the Pansharpening technique for a better interpretation of objects; building a digital elevation model for tourist GIS; processing of cartographic materials in ArcGIS; creation of a graphical and attributive database; classification and layer-by-layer data visualization; development of tourism routes by means of ArcGIS Online and AllTrails web applications; analysis of the created of Sumy oblast tourist GIS. Results. As a result of the research: a structural diagram of the main stages of the research has been developed; a graphical-attributive database with information about tourist objects was organized; created a digital elevation model based on SRTM data of Sumy oblast, made the topographic basis of GIS; by means of the ArcGIS 10.3 software a tourist GIS of the Sumy oblast was created, which includes 255 tourist objects of various profiles; using web applications ArcGIS Online and AllTrails, 5 automobile tourist routes with a total length of 1234 kmand 1 pedestrian route 11 kmlong, which pass through the territory of Sumy oblast, have been developed. Scientific novelty. The novelty of the research lies in the methodology for creating a Sumy oblast tourist GIS, the development of new excursion tourist routes and objects, and their visualization based on the use of cartographic materials and satellite images by means of modern GIS, in particular ArcGIS 10.3, ArcGIS Online and AllTrails. Practical value. The research results can be used in the tourism industry, where the priority task is to provide tourists with modern highquality overview, cognitive and cartographic materials, including traditional maps, schematic maps, booklets, and digital maps, 3D models, web applications, audio, video and virtual tours, which are created using the latest digital and GIS technologies, as well as to popularize the tourist and recreational potential of the Sumy oblast among the population.

In the article is given the methods of fulfillment consecutive stages of the relief morphometric analysis of basinal systems' within mountain territories using software package ESRI ArcGIS Desktop 9.3 (case study of the Chornogora's part of Prut's basin). The results of fulfillment this algorithm is developed digital elevation model, range of analytical and synthetic morphometric maps and hypsographical profiles, circular charts, bar diagrams, plots and tables of relief's various morphometric parameters as well as apportionment for their further complex morphogenetical analysis. Key words: morphometric analysis of the relief, geoinformation systems, geoinformation data base, digital elevation models, morphometric parameters of the relief, analytical and synthetic morphometric maps.

In Malaysia, the existing of counting approach on the shipping container at depot is carried out by manual based system. This has made the efficiency of the method to be questioned which can be solved through automation. Under previous studies, Unmanned Aerial Vehicle (UAV) is demonstrated for automatic counting of cars and trees. Therefore, the possibility for shipping container counting is highly required in which promotes low-cost alternative and automatedpilot for data collection. Based on this study, the aerial images captured using UAV is combined with geographical information processing software, ArcGIS, towards automated approach for container counting. The overlapping aerial images are post-processed using photogrammetric technique to produce Digital Surface Model (DSM) that represents the ground and above surface feature’s elevations. Then, the constructed DSM is filtered to develop Digital Terrain Model (DTM) where it represents the ground surface’s elevation only. Then, container’s candidates are isolated using subtraction of the DTM from DSM to generate normalized DSM (nDSM) which represents the heights of container’s stacks. From the standard size and height of one container from ISO, the number of containers is extracted. The ModelBuilder tool available in ArcGIS is customized for automated geographical information processing. From results, the proposed approach contributed to 100% of counting accuracy. Keywords: Unmanned Aerial Vehicle, Counting, Shipping Container, ArcGIS, ModelBuilder

Taking Daliuta mine as research object, use its 2002, 2011 two same period Landsat TM/ ETM and remote sensing image as the data source, use pixel dichotomy to get its vegetation coverage evolution trend data; Use DEM digital elevation model data in the region to generate digital terrain model based on ArcGIS, and make overlay analysis with the vegetation coverage evolution trend data to study the relationship between the vegetation coverage and terrain factor of the mine area. The results showed that: From 2002 to 2011, the vegetation coverage evolution trend of Daliuta mining mainly moderate improvement and significantly improvement, and concentrated in middle altitude, low slope, sunny area.

The main purpose of the present research is to develop software for reconstruction of the river bed on the basis of sparse cross-section measurements. The tools prepared should support the process of hydrodynamic model preparation for simulation of river flow. Considering the formats of available data and the requirements of modern modeling techniques, the prepared software is fully integrated with the GIS environment. The scripting language Python 2.7 implemented in ArcGIS 10.5.1 was chosen for this purpose. Two study cases were selected to validate and test the prepared procedures. These are stream reaches in Poland. The first is located on the Warta river, and the second on the Ner river. The data necessary for the whole procedure are: a digital elevation model, measurements of the cross-sections in the form of points, and two polyline layers representing an arbitrary river centerline and river banks. In the presented research the concept of a channel-oriented coordinate system is applied. The elevations are linearly interpolated along the longitudinal and transversal directions. The interpolation along the channel is implemented in three computational schemes linking different tools available in ArcGIS and ArcToolbox. A simplified comparison of memory usage and computational time is presented. The scheme linking longitudinal and spatial interpolation algorithms seems to be the most advantageous.

ABSTRACT This study presents a new methodology to identify landslide and landslide-susceptible locations in Interior Alaska using only geomorphic properties from light detection and ranging (LiDAR) derivatives (i.e., slope, profile curvature, and roughness) and the normalized difference vegetation index (NDVI), focusing on the effect of different resolutions of LiDAR images. We developed a semi-automated object-oriented image classification approach in ArcGIS 10.5 and prepared a landslide inventory from visual observation of hillshade images. The multistage work flow included combining derivatives from 1-, 2.5-, and 5-m-resolution LiDAR, image segmentation, image classification using a support vector machine classifier, and image generalization to clean false positives. We assessed classification accuracy by generating confusion matrix tables. Analysis of the results indicated that LiDAR image scale played an important role in the classification, and the use of NDVI generated better results. Overall, the LiDAR 5-m-resolution image with NDVI generated the best results with a kappa value of 0.55 and an overall accuracy of 83 percent. The LiDAR 1-m-resolution image with NDVI generated the highest producer accuracy of 73 percent in identifying landslide locations. We produced a combined overlay map by summing the individual classified maps that was able to delineate landslide objects better than the individual maps. The combined classified map from 1-, 2.5-, and 5-m-resolution LiDAR with NDVI generated producer accuracies of 60, 80, and 86 percent and user accuracies of 39, 51, and 98 percent for landslide, landslide-susceptible, and stable locations, respectively, with an overall accuracy of 84 percent and a kappa value of 0.58. This semi-automated object-oriented image classification approach demonstrated potential as a viable tool with further refinement and/or in combination with additional data sources.

Increasingly available and a virtually uninterrupted supply of satellite-estimated rainfall data is gradually becoming a cost-effective source of input for flood prediction under a variety of circumstances. The study conducted in Wasit province/Eastern Iraq when a flood occurs due to heavy rainfall in May 2013. In this study the capability of Tropical Rainfall Measuring Mission (TRMM) rainfall daily data have been used to estimate the relationship between measured precipitation and the Digital Elevation Model (DEM), also to study the relationship between rainfall intensity and flood waters areas. Rainfall estimation by remote sensing using satellite-derived data from the Tropical Rainfall Measuring Mission (TRMM) is a possible means of supplementing rain gauge data, having the better spatial cover of rainfall fields. The approach used throughout this paper has integrated recently compiled data derived from satellite imagery (rainfall, and digital elevation model) into a GIS geodatabase to study the relationship between rainfall intensity and floodwater's areas then the results' comparison with the Normalized Difference Water Index (NDWI) after the flood. ArcGIS software has been used to process, analyze the archived Tropical Rainfall Measuring Mission (TRMM) precipitation data, and calculate NDWI from Landsat 8 images. In conclusions, the study explains the flood-area clearly captured by the TRMM measurements; and the region’s water increased. Also, good correlation between measured precipitation and the Digital Elevation Model (DEM) has been detected.

The rapid development of remote sensing technology for obtaining high-resolution digital elevation models (DEMs) in recent years has made them more and more widely available and has allowed them to be used for morphometric assessment of concave landforms, such as valleys, gullies, glacial cirques, sinkholes, craters, and others. The aim of this study was to develop a geographic information systems (GIS) toolbox for the automatic extraction of 26 morphometric characteristics, which include the geometry, hypsometry, and volume of concave landforms. The Morphometry Assessment Tools (MAT) toolbox in the ArcGIS software was developed. The required input data are a digital elevation model and the form boundary as a vector layer. The method was successfully tested on an example of 21 erosion-denudation valleys located in the young glacial area of northwest Poland. Calculations were based on elevation data collected in the field and LiDAR data. The results obtained with the tool showed differences in the assessment of the volume parameter at the average level of 12%, when comparing the field data and LiDAR data. The algorithm can also be applied to other types of concave forms, as well as being based on other DEM data sources, which makes it a universal tool for morphometric evaluation.