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Ugbelase Vincent Nwacholundu, Igbokwe Joel Izuchukwu, Emengini Josephine Ebele, Ejikeme Joseph Onyedika, and Igbokwe Esomchukwu Chinagorom. "Generating and analyzing Terrain characteristics from Shuttle Radar Topographic Mission (SRTM), DEM." World Journal of Advanced Research and Reviews 10, no. 3 (2021): 198–206. http://dx.doi.org/10.30574/wjarr.2021.10.3.0272.
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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.
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Liu, Xiao Li, Xue Li, Jing Gang Li, and Qiu Liang Wang. "Extraction and Application of Water System and Physiognomy Morphological Characteristics Based on DEM in ArcGIS Environment." Advanced Materials Research 807-809 (September 2013): 1940–43. http://dx.doi.org/10.4028/www.scientific.net/amr.807-809.1940.
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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.
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SHEVCHUK, V., Z. KUZYK, and L, AVDASOVA. "Creation of Sumy oblast tourist GIS by means of GIS technologies." Modern achievements of geodesic science and industry 41, no. I (2021): 140–50. http://dx.doi.org/10.33841/1819-1339-1-41-140-150.
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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.
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Marchak, A. "The methods morphometric analysis’ of basinal systems’ within mountain territories using GIS (case study of the Chornogora’s part of Prut’s basin)." Visnyk of the Lviv University. Series Geography 2, no. 40 (2012): 68–90. http://dx.doi.org/10.30970/vgg.2012.40.2085.
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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.
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Abdullah, Afiq, Jasmee Jaafar, Khairul Nizam Tahar, and Mohamad Hezri Razali. "Shipping Container Counting Approach Using Unmanned Aerial Vehicle (UAV) and ArcGIS." Built Environment Journal 16, no. 2 (2019): 15. http://dx.doi.org/10.24191/bej.v16i2.9693.
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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
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Liu, Dong Wen, Zhi Yong Qiao, Ting Ting Wei, Shu Jiang, Ya Kai Chen, and Ji Yong Zeng. "The Coupling Relationship between Forest Vegetation and Terrain of Daliuta Mine." Applied Mechanics and Materials 641-642 (September 2014): 1191–94. http://dx.doi.org/10.4028/www.scientific.net/amm.641-642.1191.
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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.
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Dysarz, Tomasz. "Development of RiverBox—An ArcGIS Toolbox for River Bathymetry Reconstruction." Water 10, no. 9 (2018): 1266. http://dx.doi.org/10.3390/w10091266.
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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.
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Miandad, Javed, Margaret M. Darrow, Michael D. Hendricks, and Ronald P. Daanen. "Landslide Mapping Using Multiscale LiDAR Digital Elevation Models." Environmental and Engineering Geoscience 26, no. 4 (2020): 405–25. http://dx.doi.org/10.2113/eeg-2268.
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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.
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Abdulrazzaq, Zaidoon, Nadia Aziz, and Abdulkareem Mohammed. "Flood modelling using satellite-based precipitation estimates and digital elevation model in eastern Iraq." International Journal of Advanced Geosciences 6, no. 1 (2018): 72. http://dx.doi.org/10.14419/ijag.v6i1.8946.
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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.
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Gudowicz, Joanna, and Renata Paluszkiewicz. "MAT: GIS-Based Morphometry Assessment Tools for Concave Landforms." Remote Sensing 13, no. 14 (2021): 2810. http://dx.doi.org/10.3390/rs13142810.
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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.
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Shrestha, Him Lal, and Mahesh Poudel. "Landslide Susceptibility Zonation Mapping in Post- Earthquake Scenario in Gorkha District." Forestry: Journal of Institute of Forestry, Nepal 15 (July 31, 2018): 45–56. http://dx.doi.org/10.3126/forestry.v15i0.24920.
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Landslide hazard zonation map is prepared to assist planners to implement mitigation measures so that further damage and loss can be minimized. In this study, post 25 April 2015 earthquake remote sensing data were used to prepare landslide inventory. Landsat images after the earthquake were downloaded from the National Aeronautics and Space Administration (NASA) website and processed using ArcGIS, ERDAS imagine and Analytical Hierarchy Process (AHP) as an extension in ArcGIS. The study was carried out in Gorkha district as this was the epicenter of the main earthquake of 25 April 2015 and consequently was highly affected by earthquake triggered landslide. The digital imagery was processed to analyze land use/land cover type. Geological features were analyzed using the criteria like color, tone, topography, stream drainage, etc. Primary topographic features like slope, aspect, elevation, etc. were generated from Digital Elevation Model (DEM). Seismological data (magnitude and epicenter) were obtained from Department of Seismology. For Landslide Susceptibility Zonation (LSZ) different thematic maps like Land Use and Land Cover (LULC) map, slope map, aspect map, lithological map, buffer map (distance from road and river/water source), soil map, and seismological map were assigned relative weights on the ordinal scale to obtain Landslide Susceptibility Index (LSI). Threshold values were selected according to breaks in LSI frequency and a LSZ map was prepared which shows very low, low, moderate, high, very high hazard zones in Gorkha district.
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Habib, Maan, Yazan Alzubi, Ahmad Malkawi, and Mohammad Awwad. "Impact of interpolation techniques on the accuracy of large-scale digital elevation model." Open Geosciences 12, no. 1 (2020): 190–202. http://dx.doi.org/10.1515/geo-2020-0012.
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AbstractThere is no doubt that the tremendous development of information technology was one of the driving factors behind the great growth of surveying and geodesy science. This has spawned modern geospatial techniques for data capturing, acquisition, and visualization tools. Digital elevation model (DEM) is the 3D depiction of continuous elevation data over the Earth’s surface that is produced through many procedures such as remote sensing, photogrammetry, and land surveying. DEMs are essential for various surveying and civil engineering applications to generate topographic maps for construction projects at a scale that varies from 1:500 to 1:2,000. GIS offers a powerful tool to create a DEM with high resolution from accurate land survey measurements using interpolation methods. The aim of this research is to investigate the impact of estimation techniques on generating a reliable and accurate DEM suitable for large-scale mapping. As a part of this study, the deterministic interpolation algorithms such as ANUDEM (Topo to Raster), inverse distance weighted (IDW), and triangulated irregular network (TIN) were tested using the ArcGIS desktop for elevation data obtained from real total station readings, with different landforms to show the effect of terrain roughness, data density, and interpolation process on DEM accuracy. Furthermore, comparison and validation of each interpolator were carried out through the cross-validation method and numerous graphical representations of the DEM. Finally, the results of the investigations showed that ANUDEM and TIN models are similar and significantly better than those attained from IDW.
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Gupta, P. K., and P. Yadav. "Constructing a Comprehensive Tool for Deriving Drainage Network using Semi-Open Source Tools and Comparision on Different DEM Data Sources." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 1129–32. http://dx.doi.org/10.5194/isprsarchives-xl-8-1129-2014.
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Digital elevation model (DEM) provides elevation information in raster format for an area which help in analysis as these phenomena are gravity depended. Hydrological study requires creation of drainage network map. DEM is the primary input for this process. Generally 6 or more processes are required to be completed to get the drainage network. These are available in form of hydrology tools in the ArcGIS software. These processes are manual and time consuming which increases the chances of human error. An automated process is constructed in this paper which aims to create a tool that can handle multiple files in an intelligent manner. <br><br> The input DEM plays a significant role in hydrological studies. This study attempts to do a comparative study to analyse the variation in the drainage network and the intermediate products with the change in the input DEM. <br><br> A tool is created using ArcPy site package in Python programming language to integrate all required hydrology tools. The script is then used to create a tool in ArcGIS 10 which takes location as an input parameter and perform the process on all the DEM files inside the directory. The tool creates separate directory for every DEM file and thus reduces the chances of file mismanagement. The proposed tool is tested on two different datasets namely ASTER GDEM and Cartosat DEM. The tool runs efficiently on both the datasets and thus provides results to compare the drainage pattern produced by these different data sources.
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Zhang, Jianbo, Zhuangzhuang Ye, and Kai Zheng. "A Parallel Computing Approach to Spatial Neighboring Analysis of Large Amounts of Terrain Data Using Spark." Sensors 21, no. 2 (2021): 365. http://dx.doi.org/10.3390/s21020365.
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Spatial neighboring analysis is an indispensable part of geo-raster spatial analysis. In the big data era, high-resolution raster data offer us abundant and valuable information, and also bring enormous computational challenges to the existing focal statistics algorithms. Simply employing the in-memory computing framework Spark to serve such applications might incur performance issues due to its lack of native support for spatial data. In this article, we present a Spark-based parallel computing approach for the focal algorithms of neighboring analysis. This approach implements efficient manipulation of large amounts of terrain data through three steps: (1) partitioning a raster digital elevation model (DEM) file into multiple square tile files by adopting a tile-based multifile storing strategy suitable for the Hadoop Distributed File System (HDFS), (2) performing the quintessential slope algorithm on these tile files using a dynamic calculation window (DCW) computing strategy, and (3) writing back and merging the calculation results into a whole raster file. Experiments with the digital elevation data of Australia show that the proposed computing approach can effectively improve the parallel performance of focal statistics algorithms. The results also show that the approach has almost the same calculation accuracy as that of ArcGIS. The proposed approach also exhibits good scalability when the number of Spark executors in clusters is increased.
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Zhang, Jianbo, Zhuangzhuang Ye, and Kai Zheng. "A Parallel Computing Approach to Spatial Neighboring Analysis of Large Amounts of Terrain Data Using Spark." Sensors 21, no. 2 (2021): 365. http://dx.doi.org/10.3390/s21020365.
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Spatial neighboring analysis is an indispensable part of geo-raster spatial analysis. In the big data era, high-resolution raster data offer us abundant and valuable information, and also bring enormous computational challenges to the existing focal statistics algorithms. Simply employing the in-memory computing framework Spark to serve such applications might incur performance issues due to its lack of native support for spatial data. In this article, we present a Spark-based parallel computing approach for the focal algorithms of neighboring analysis. This approach implements efficient manipulation of large amounts of terrain data through three steps: (1) partitioning a raster digital elevation model (DEM) file into multiple square tile files by adopting a tile-based multifile storing strategy suitable for the Hadoop Distributed File System (HDFS), (2) performing the quintessential slope algorithm on these tile files using a dynamic calculation window (DCW) computing strategy, and (3) writing back and merging the calculation results into a whole raster file. Experiments with the digital elevation data of Australia show that the proposed computing approach can effectively improve the parallel performance of focal statistics algorithms. The results also show that the approach has almost the same calculation accuracy as that of ArcGIS. The proposed approach also exhibits good scalability when the number of Spark executors in clusters is increased.
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Muhammad, Sher, and Lide Tian. "Assessment of ArcGIS based extraction of geoidal undulation compared to National Geospatial Intelligence Agency (NGA) model – A case study." Journal of Applied Geodesy 14, no. 1 (2020): 77–81. http://dx.doi.org/10.1515/jag-2019-0030.
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AbstractGlobal Navigation Satellite System (GNSS) and remote sensing Digital Elevation Models (DEMs) represent earth’s surface elevation with reference to ellipsoid and orthometric heights. Proper estimation of the geoid (difference of ellipsoid and orthometric heights) is necessary before comparing data referenced to the different vertical datum. In this paper, an error in estimating EGM96 orthometric height is highlighted, verified by NGA/NASA developed model and MATLAB®. A significant error was found in the ArcGIS derived EGM96 orthometric heights range between ±6.9 meters. In addition, interpolation of low-resolution geoid data also produces significant biases depending on geographic location and the number of the interpolation data point. The bias was maximum negative in the central part of Tibetan Plateau and Himalaya. Therefore, estimation of orthometric height similar to NGA/NASA model precision is necessary for comparison of DEMs for natural resources management, 3D modelling and glaciers mass balance mainly in the mountainous regions.
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Chan, Yili, and Masatoshi Mori. "The Construction of a Flood Monitoring System with Alert Distribution Using Google Earth and 3D GIS." Journal of Disaster Research 8, no. 3 (2013): 512–18. http://dx.doi.org/10.20965/jdr.2013.p0512.
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Locations of floods are not always known. Persons nearby for whom there is a possibility of danger due to flooding need information with which to predict flooding and to find refuge quickly and accurately. A Webbased Flood Monitoring System (FMS) using Google Earth and 3D GIS has been developed by employing Google Earth pro v. 6.0 and ArcGIS 10.0 (ESRI). The FMS provides a viewer for Windows PCs and smart phones. This viewer provides information consisting of digital elevation data from a 2 m Digital Surface Model (DSM) integrating 1:2500 digital topographic maps from the Geographical Survey Institute of Japan with official river information from the Ministry of Land, Infrastructure, Transport and Tourism of Japan and local river offices. It includes flood simulations and hazard maps from local governments. Users are able to download KML file data and/or Shape file data for private use. In addition, a reporting system for preregistered users who want immediate information has been prepared for alert and flood information.
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Demir, Vahdettin, and Ozgur Kisi. "Flood Hazard Mapping by Using Geographic Information System and Hydraulic Model: Mert River, Samsun, Turkey." Advances in Meteorology 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/4891015.
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In this study, flood hazard maps were prepared for the Mert River Basin, Samsun, Turkey, by using GIS and Hydrologic Engineering Centers River Analysis System (HEC-RAS). In this river basin, human life losses and a significant amount of property damages were experienced in 2012 flood. The preparation of flood risk maps employed in the study includes the following steps: (1) digitization of topographical data and preparation of digital elevation model using ArcGIS, (2) simulation of flood lows of different return periods using a hydraulic model (HEC-RAS), and (3) preparation of flood risk maps by integrating the results of (1) and (2).
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Ficher, Kevin Nunes, Donizete Dos Reis Pereira, Josiane Silva Oliveira, André Quintão de Almeida, and Eduardo Morgan Uliana. "Assessment of digital elevation models to obtain morphometric characteristics in relief transition region." Ambiente e Agua - An Interdisciplinary Journal of Applied Science 14, no. 1 (2019): 1. http://dx.doi.org/10.4136/ambi-agua.2280.
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The purpose of this study was to evaluate the performance of Digital Elevation Models (DEMs) in the morphometric characterization of a basin located in a transitional region between the São Francisco Plateau, São Francisco Depression and Espinhaço Range reliefs. For the study, four DEMs were generated by interpolation of the SRTM data and topographic maps, using the Topo To Raster interpolator with and without mapped hydrography support, available in ArcGIS® 9.3 software. Another DEM was obtained from the SRTM original data. From the generated DEMs, the morphometric characteristics of the basin were determined and compared to those obtained from topographic maps, denominated reference (REF), by means of percentage errors. The evaluation was also performed in a qualitative way, comparing the drainage and the basin delineations. In general, the DEMs obtained with the support of the mapped hydrography (SRTM-TRH and CT-TRH) provided the best results, with small errors, mainly for the main morphometric characteristics of the basin, drainage area and main river length, which ranged from 0.38 to 1.12% and 5.28 to 7.07%, respectively. On the other hand, the DEMs generated without the support of the mapped hydrography (SRTM-O, SRTM-TR and CT-TR) presented major errors mainly in determining the drainage area and length of the main river, which varied from 18.1 to 26.6% and 26.7 to 34.4%, respectively. These occurred due to a deviation of the main river in the São Franciscana Depression region, which allows us to conclude on the necessity and importance of evaluating DEMs before their use.
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Hnusuwan, Benjawan, Siriwan Kajornkasirat, and Supattra Puttinaovarat. "Dengue Risk Mapping from Geospatial Data Using GIS and Data Mining Techniques." International Journal of Online and Biomedical Engineering (iJOE) 16, no. 11 (2020): 57. http://dx.doi.org/10.3991/ijoe.v16i11.16455.
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Dengue fever is a major public health problem and has been an epidemic in Thailand for a long time. Therefore, there is a need to find a way to prevent the disease. This research aimed to explore the important factors of dengue fever, to study the factors affecting dengue hemorrhagic fever in Surat Thani Province, and to map the potential outbreak of dengue fever. Collecting patient information was done including, Rainfall, Digital Elevation Model (DEM), Land Use and Land Cover (LULC), Population Density, and Patients in Surat Thani Province, which was analyzed using data mining techniques involving analysis using 3 algorithms comprising Random Forest, J48, and Random Tree. The correct result is Random Forest since the accuracy of the data is 96.7 percent followed by J48 with accuracy of 95.9 percent. The final sequence is Random Tree with accuracy of 93.5 percent. Then, using the information can be displayed through ArcGIS program to see the risk points that are compared to the risk areas that have been previously done. The results can be very risky in Mueang District, Kanchanadit District, and Don Sak District, corresponding to the information obtained from the Public Health Office and the risk map created from the patient information.
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Bakhsh, A., and R. S. Kanwar. "Soil and landscape attributes interpret subsurface drainage clusters." Soil Research 46, no. 8 (2008): 735. http://dx.doi.org/10.1071/sr08065.
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Water in excess of evapotranspiration follows topographically defined flow paths and can affect spatial subsurface drainage patterns. This 1993–2003 field study was conducted near Nashua, Iowa, to delineate the subsurface drainage clusters and identify the landscape and hydrologic variables that contributed significantly in discriminating these clusters. A digital elevation model was developed using 6695 elevation data measurements collected with GPS navigation system across 36 field plots (0.4 ha in size each). A spherical model was used to interpolate the elevation data within a Spatial Analyst tool of ArcGIS software. Plot-scale average topographic attributes of elevation, slope, aspect, and curvature were derived using the Zonal function in the Spatial Analyst tool. Hydrologic attributes of flow direction, flow length, and flow accumulation were derived using the Hydrology module of Spatial Analyst tool after performing Fill function for the sink areas. Annual normalised subsurface drainage data and plot-scale derived soil and topographic attributes were used in the cluster and discriminant analysis, respectively, to investigate their relationships. Stepwise discriminant analysis identified elevation and flow accumulation as the variables that discriminated the subsurface drainage clusters of low, medium, and high categories significantly (P = 0.01). The role of elevation and flow accumulation was verified using discriminant functions that predicted all members of the high drainage cluster accurately with zero error rates. GIS data layer of subsurface drainage clusters also showed that high drainage clusters were located at the lower elevation levels and were in close agreement with the elevation and flow accumulation data layers. The results of this study indicate that elevation and flow accumulation GIS data layers can be used as a guideline to minimise nutrient losses through subsurface drainage water.
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Hapep, Aya M., and Maythm AL-Bakri. "Comparison of Different DEM Generation Methods based on Open Source Datasets." Journal of Engineering 26, no. 1 (2019): 63–85. http://dx.doi.org/10.31026/j.eng.2020.01.07.
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Digital Elevation Model (DEM) is one of the developed techniques for relief representation. The definition of a DEM construction is the modeling technique of earth surface from existing data. DEM plays a role as one of the fundamental information requirement that has been generally utilized in GIS data structures. The main aim of this research is to present a methodology for assessing DEMs generation methods. The DEMs data will be extracted from open source data e.g. Google Earth. The tested data will be compared with data produced from formal institutions such as General Directorate of Surveying. The study area has been chosen in south of Iraq (Al-Gharraf / Dhi Qar governorate. The methods of DEMs creation are kriging, IDW (inverse distance weight), spline, and natural neighbor. This research used different software for processing and analysis such as ArcGIS 10.2, TCX and Civil 3D. Two- sample t-test has been adopted to investigate the mean of elevation differences between compared datasets. The results showed that the spline is the best method that can be used to build DEM in this study area.
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Zobkov, Mikhail, Aleksey Tarasov, Dmitry Subetto, and Maksim Potakhin. "GIS-MODELING OF LAKE ONEGO SHORELINE IN THE HOLOCENE AND LATE PLEISTOCENE." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 1 (June 15, 2017): 316. http://dx.doi.org/10.17770/etr2017vol1.2541.
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The application of GIS software for reconstruction of Lake Onego shoreline in the Holocene and the Late Pleistocene presented. Reconstruction was originated from the ideas of the Lake Onego depression deglaciation model proposed by I. Demidov [1] and the data of E. Deviatova [2] concerning Lake Onego depression isostatic uplift in the Holocene. ArcGIS software was used to perform GIS-modelling which was based on the original digital elevation model of the lakebed and its watershed. Twelve digital paleogeographic maps were developed as a result. Paleogeographic maps were verified by hand-drawn images of I. Demidov and E. Deviatova and by matching the lake shoreline and the position of archeological sites. Maps are available on-line in the electronic form [3]. The surface area of the Lake was determined at different stages of its development. The quantitative data obtained in this study is valuable for estimation of the lake volumes and the rates of discharge in the past.
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Dong, Pinliang, Ruofei Zhong, Jisheng Xia, and Shucheng Tan. "A semi-automated method for extracting channels and channel profiles from lidar-derived digital elevation models." Geosphere 16, no. 3 (2020): 806–16. http://dx.doi.org/10.1130/ges02188.1.
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Abstract With the advent of digital elevation models (DEMs) and geographic information systems (GIS), several methods have been proposed to extract channels from raster DEMs. Light detection and ranging (lidar) can produce high-resolution DEMs and poses new challenges to existing methods for channel extraction. This paper introduces a semi-automated method for extracting stream channels and channel profiles from high-resolution DEMs using image processing techniques. Based on user-specified approximate locations of start and end points and a few simple parameters, the method implements five automated steps: (1) channel detection using a local minimum value search; (2) channel delineation using Bresenham’s line algorithm and mathematical morphological operation; (3) vectorization; (4) profile generation; and (5) accuracy assessment. The method is implemented as an ArcGIS Python add-in toolbar named Channel Extraction. The application of the toolbar is demonstrated using a lidar-derived DEM in a study area along the San Andreas fault in California, USA. The software and test data are freely available for download (see Supplemental Files1). The demonstrated samples suggest that this new semi-automated method for extracting channels and channel profiles is flexible and user-friendly and can produce accurate results to support geomorphic studies.
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Bühler, Y., S. Kumar, J. Veitinger, M. Christen, and A. Stoffel. "Automated identification of potential snow avalanche release areas based on digital elevation models." Natural Hazards and Earth System Sciences 13, no. 5 (2013): 1321–35. http://dx.doi.org/10.5194/nhess-13-1321-2013.
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Abstract. The identification of snow avalanche release areas is a very difficult task. The release mechanism of snow avalanches depends on many different terrain, meteorological, snowpack and triggering parameters and their interactions, which are very difficult to assess. In many alpine regions such as the Indian Himalaya, nearly no information on avalanche release areas exists mainly due to the very rough and poorly accessible terrain, the vast size of the region and the lack of avalanche records. However avalanche release information is urgently required for numerical simulation of avalanche events to plan mitigation measures, for hazard mapping and to secure important roads. The Rohtang tunnel access road near Manali, Himachal Pradesh, India, is such an example. By far the most reliable way to identify avalanche release areas is using historic avalanche records and field investigations accomplished by avalanche experts in the formation zones. But both methods are not feasible for this area due to the rough terrain, its vast extent and lack of time. Therefore, we develop an operational, easy-to-use automated potential release area (PRA) detection tool in Python/ArcGIS which uses high spatial resolution digital elevation models (DEMs) and forest cover information derived from airborne remote sensing instruments as input. Such instruments can acquire spatially continuous data even over inaccessible terrain and cover large areas. We validate our tool using a database of historic avalanches acquired over 56 yr in the neighborhood of Davos, Switzerland, and apply this method for the avalanche tracks along the Rohtang tunnel access road. This tool, used by avalanche experts, delivers valuable input to identify focus areas for more-detailed investigations on avalanche release areas in remote regions such as the Indian Himalaya and is a precondition for large-scale avalanche hazard mapping.
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Ustaoglu, Beyza, and Aslı Uzun. "Determination of suitable land for special cimate requirements of agricultural products in Mediterranean Region (Turkey) by weighted overlay analysis Akdeniz Bölgesi'nde (Türkiye) yetiştirilen tarım ürünlerinin özel iklim isteklerine uygun arazilerin ağırlıklı çakıştırma analizi ile belirlenmesi." Journal of Human Sciences 15, no. 4 (2018): 2433. http://dx.doi.org/10.14687/jhs.v15i4.5573.
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In this study, the areas where wheat, corn, cotton, grape and olive plants of high economic value in the Mediterranean Region can be grown in accordance with the special climate requirements have been determined with Weighted Overlay Analysis in Geographical Information Systems. Burdur, Isparta, Kahramanmaras, Antalya, Mersin, Adana, Osmaniye and Iskenderun were selected for this purpose as the automatic meteorological observation stations having long observation period and homogeneous distribution. Including the years between 1991-2017, the daily average temperature, daily average maximum temperature, daily average minimum temperature and daily total rainfall data were used as climate data along the elevation and slope data generated from the digital elevation model (DEM) as topography data. Phenological periods of agricultural products from Turkey Phenology Atlas and special climate requirements in these periods according to literature review were determined as first step of the methodology. Then, climate data were arranged according to phenological periods and transferred to ArcGIS 10.1 program. Climate data were interpolated by IDW method in order to create a continuous surface from climate data. The weighted overlay tool included in the ArcGIS 10.1 program was applied to the topography data and interpolated climate data. The areas compatible with temperature and precipitation conditions which are special climate requirements of the agricultural products and the areas where the elevation is below 1000 meters and the slope is below %20 are classified as suitable; and the areas that do not meet these criteria are classified as unsuitable. Then the distribution maps are constructed. It is determined that the areas classified as suitable for agricultural production by the study overlap with the areas currently having the greatest amount of agriculture production. According to the results obtained from the analysis; the effect of elevation, hill and climate factors in determining the areas where agricultural products can be cultivated economically is clearly determined.Extended English summary is in the end of Full Text PDF (TURKISH) file. ÖzetBu çalışmada Akdeniz Bölgesi'nde ekonomik değeri yüksek olan buğday, mısır, pamuk, üzüm ve zeytinin özel iklim isteklerine uygun olarak yetiştirilebileceği alanlar Coğrafi Bilgi Sistemleri’nde Ağırlıklı Çakıştırma Analizi (Weighted Overlay Analysis) ile tespit edilmiştir. Bu amaçla çalışma alanındaki gözlem süresi uzun olan ve homojen dağılım gösteren otomatik meteoroloji gözlem istasyonlarından Burdur, Isparta, Kahramanmaraş, Antalya, Mersin, Adana, Osmaniye ve İskenderun seçilmiştir. Bu istasyonlara ait 1991-2017 yılları arasını kapsayan, günlük ortalama sıcaklık, günlük ortalama maksimum sıcaklık, günlük ortalama minimum sıcaklık, günlük en yüksek maksimum ve en düşük minimum sıcaklık ve günlük toplam yağış verileri ile sayısal yükseklik modelinden (dem) oluşturulan yükselti ve eğim verileri, topoğrafya verisi olarak kullanılmıştır. Metot olarak, öncelikle tarım ürünlerinin Türkiye Fenoloji Atlası’ndan fenolojik dönemleri ve literatürden bu dönemlerdeki özel iklim istekleri belirlenmiştir. Fenolojik dönemlere göre düzenlenen iklim verileri ArcGIS 10.1 programına aktarılmıştır. İklim verilerinden sürekli yüzey oluşturabilmesi için sıcaklık ve yağış değerleri IDW yöntemiyle interpole edilmiştir. Topoğrafya verileri ve interpole edilmiş iklim verilerine ArcGIS 10.1 programında weighted overlay aracıyla ağırlıklı çakıştırma analizi uygulanmıştır. Tarım ürünlerinin özel iklim isteklerinden sıcaklık ve yağış koşullarına uyumlu, yükseltinin 1000 metre ve eğimin %20’nin altında olduğu alanlar uygun, bu kriterleri sağlamayan alanlar uygun değil olarak sınıflandırılmış ve dağılış haritaları yapılmıştır. Tarımsal üretim için uygun olan alanların tarımsal üretim tutarlarının da yüksek olduğu alanlara karşılık geldiği gözlemlenmiştir. Analizden elde edilen sonuçlara göre; bölgedeki yükselti ve eğim faktörleri ile iklim koşullarının tarım ürünlerinin ekonomik olarak yetiştirilebileceği alanları belirlemedeki etkisi açık bir şekilde tespit edilmiştir.
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Kumhálová, Jitka. "Inference of topographical characteristics for precision agriculture." Geografie 119, no. 2 (2014): 161–78. http://dx.doi.org/10.37040/geografie2014119020161.
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Quantitative knowledge of the factors and interactions affecting agricultural yield is essential for site-specific yield management. Topography of the terrain certainly remains on these yield affecting factors. For this reason, this paper deals with the prospects of modelling topographic features – digital elevation models and slope models for an experimental plot with an area of 11.5 hectares. The basis for the creation of these models is formed by data from various sources (combine yield monitor, RTK-GPS and data from airborne laser scanning). These data sets have been then modified via ArcGIS software in order to most accurately describe the topography of the analysed landscape. The resulting models of topographical characteristics were compared with crop yields during the observed period of 2004–2012, in order to determine which data source is best for the evaluation of the influence topography holds over yield values. Data from airborne laser scanning turned out to be the most suitable dataset for the tasks, because of their sufficient accuracy and frequency.
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Shrivastav, M., S. K. Mickelson, and D. Webber. "Using ArcGIS hydrologic modeling and LiDAR digital elevation data to evaluate surface runoff interception performance of riparian vegetative filter strip buffers in central Iowa." Journal of Soil and Water Conservation 75, no. 1 (2019): 123–29. http://dx.doi.org/10.2489/jswc.75.1.123.
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Tran, Ducthien, Dawei Xu, Vanha Dang, and Abdulfattah A. Q. Alwah. "Predicting Urban Waterlogging Risks by Regression Models and Internet Open-Data Sources." Water 12, no. 3 (2020): 879. http://dx.doi.org/10.3390/w12030879.
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In the context of climate change and rapid urbanization, urban waterlogging risks due to rainstorms are becoming more frequent and serious in developing countries. One of the most important means of solving this problem lies in elucidating the roles played by the spatial factors of urban surfaces that cause urban waterlogging, as well as in predicting urban waterlogging risks. We applied a regression model in ArcGIS with internet open-data sources to predict the probabilities of urban waterlogging risks in Hanoi, Vietnam, during the period 2012–2018 by considering six spatial factors of urban surfaces: population density (POP-Dens), road density (Road-Dens), distances from water bodies (DW-Dist), impervious surface percentage (ISP), normalized difference vegetation index (NDVI), and digital elevation model (DEM). The results show that the frequency of urban waterlogging occurrences is positively related to the first four factors but negatively related to NDVI, and DEM is not an important explanatory factor in the study area. The model achieved a good modeling effect and was able to explain the urban waterlogging risk with a confidence level of 67.6%. These results represent an important analytic step for urban development strategic planners in optimizing the spatial factors of urban surfaces to prevent and control urban waterlogging.
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Kisaka, M. Oscar, M. Mucheru-Muna, F. K. Ngetich, J. N. Mugwe, D. Mugendi, and F. Mairura. "Rainfall Variability, Drought Characterization, and Efficacy of Rainfall Data Reconstruction: Case of Eastern Kenya." Advances in Meteorology 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/380404.
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This study examined the extent of seasonal rainfall variability, drought occurrence, and the efficacy of interpolation techniques in eastern Kenya. Analyses of rainfall variability utilized rainfall anomaly index, coefficients of variance, and probability analyses. Spline, Kriging, and inverse distance weighting interpolation techniques were assessed using daily rainfall data and digital elevation model using ArcGIS. Validation of these interpolation methods was evaluated by comparing the modelled/generated rainfall values and the observed daily rainfall data using root mean square errors and mean absolute errors statistics. Results showed 90% chance of below cropping threshold rainfall (500 mm) exceeding 258.1 mm during short rains in Embu for one year return period. Rainfall variability was found to be high in seasonal amounts (CV = 0.56, 0.47, and 0.59) and in number of rainy days (CV = 0.88, 0.49, and 0.53) in Machang’a, Kiritiri, and Kindaruma, respectively. Monthly rainfall variability was found to be equally high during April and November (CV = 0.48, 0.49, and 0.76) with high probabilities (0.67) of droughts exceeding 15 days in Machang’a and Kindaruma. Dry-spell probabilities within growing months were high, (91%, 93%, 81%, and 60%) in Kiambere, Kindaruma, Machang’a, and Embu, respectively. Kriging interpolation method emerged as the most appropriate geostatistical interpolation technique suitable for spatial rainfall maps generation for the study region.
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Muñoz, David, Jordan Cissell, and Hamed Moftakhari. "Adjusting Emergent Herbaceous Wetland Elevation with Object-Based Image Analysis, Random Forest and the 2016 NLCD." Remote Sensing 11, no. 20 (2019): 2346. http://dx.doi.org/10.3390/rs11202346.
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Emergent herbaceous wetlands are characterized by complex salt marsh ecosystems that play a key role in diverse coastal processes including carbon storage, nutrient cycling, flood attenuation and shoreline protection. Surface elevation characterization and spatiotemporal distribution of these ecosystems are commonly obtained from LiDAR measurements as this low-cost airborne technique has a wide range of applicability and usefulness in coastal environments. LiDAR techniques, despite significant advantages, show poor performance in generation of digital elevation models (DEMs) in tidal salt marshes due to large vertical errors. In this study, we present a methodology to (i) update emergent herbaceous wetlands (i.e., the ones delineated in the 2016 National Land Cover Database) to present-day conditions; and (ii) automate salt marsh elevation correction in estuarine systems. We integrate object-based image analysis and random forest technique with surface reflectance Landsat imagery to map three emergent U.S. wetlands in Weeks Bay, Alabama, Savannah Estuary, Georgia and Fire Island, New York. Conducting a hyperparameter tuning of random forest and following a hierarchical approach with three nomenclature levels for land cover classification, we are able to better map wetlands and improve overall accuracies in Weeks Bay (0.91), Savannah Estuary (0.97) and Fire Island (0.95). We then develop a tool in ArcGIS to automate salt marsh elevation correction. We use this ‘DEM-correction’ tool to modify an existing DEM (model input) with the calculated elevation correction over salt marsh regions. Our method and tool are validated with real-time kinematic elevation data and helps correct overestimated salt marsh elevation up to 0.50 m in the studied estuaries. The proposed tool can be easily adapted to different vegetation species in wetlands, and thus help provide accurate DEMs for flood inundation mapping in estuarine systems.
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Webber, David F., Manveen Bansal, Steven K. Mickelson, et al. "Assessing Surface Flowpath Interception by Vegetative Buffers Using ArcGIS Hydrologic Modeling and Geospatial Analysis for Rock Creek Watershed in Central Iowa." Transactions of the ASABE 61, no. 1 (2018): 273–83. http://dx.doi.org/10.13031/trans.12350.
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Abstract. Nonpoint-source (NPS) pollution is a major cause of surface water quality degradation due to the transport of chemicals, nutrients, and sediments into lakes and streams. Vegetative buffers comprise several effective landscape best management practices (BMPs) that include vegetative filter strips (VFS) and grassed waterways. However, some BMPs are less effective due to concentrated surface flow, improper cropland-to-VFS area ratios, and surface flowpaths that partially or completely bypass vegetative buffers. The overall objective of this study was to quantify the accuracy of simulated flowpaths relative to observed and global positioning system (GPS)-assisted ground-truthed surface flowpaths for improved placement of VFS and other vegetative buffers to effectively intercept surface runoff. This study was conducted on three research sites in Rock Creek watershed in central Iowa. Geographic information system (GIS) software was used for flowpath hydrologic modeling and geospatial map comparison analysis. Digital elevation model (DEM) datasets were used for flowpath simulation and included internet-available USGS 30 m × 30 m grid (typically used to design and site VFS buffers) and light detection and ranging (LiDAR) 5 m × 5 m grid DEMs. Results from this study indicate that the LiDAR 5 m × 5 m DEM generated significantly more accurate simulated flowpaths than the USGS 30 m × 30 m DEM. These results quantitatively underscore the efficacy of using high-resolution LiDAR DEM data to more accurately determine how well surface flowpaths are intercepted by VFS and other vegetative buffers. These results also demonstrate the benefits of coupling high-resolution aerial imagery with quantitative geospatial map comparison data to improve visualization and comparison of field-scale and watershed-scale hydrologic and terrestrial attributes. Ultimately, the results and procedures from this study will be applied to the development of a novel cloud-based, user-interactive, virtual-reality decision support (DS) tool that can be used to remotely assess hydrologic landscape conditions, prescribe improvements to existing BMPs, and determine new sites for enhanced BMP placement and functionality within a high-resolution 3-D imagery environment. Keywords: ArcGIS, Best management practices (BMPs), Decision support (DS) tool, Digital elevation model (DEM), Geospatial analysis, Light detection and ranging (LiDAR), Nonpoint-source (NPS) pollution, Surface runoff, Vegetative filter strip (VFS), Watershed hydrol
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H.O, Nwankwoala,, Harry, M. T, and Warmate, T. "ASSESSING AQUIFER VULNERABILITY AND CONTAMINANT PLUME AT ARTISANAL REFINING SITES IN PARTS OF OKRIKA AND OGU-BOLO LOCAL GOVERNMENT AREAS, RIVERS STATE, NIGERIA." Water Conservation and Management 4, no. 2 (2020): 68–72. http://dx.doi.org/10.26480/wcm.02.2020.68.72.
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This study aims at the assessment of aquifer vulnerability and contaminants plume where artisan refining of crude is taking place, which is a threat to availability of potable water. The ArcGIS version 10.3, ENVI version 4.7, Surfer 10, SPSS 22 and Microsoft Enterprise were used for the interpretation and the water and soil samples were analyzed in the laboratory using standard methods. A total number of sixteen (16) sampling points were selected using random sampling techniques for the water points and soil samples within Ogu Bolo and Okrika. The Digital Elevation Model was created from the elevation data obtained from SRTM (Short Radar Thematic Mapper) satellite image and contour extracted from the topographic map. The influence of the soil type, slope, flow accumulation, flow direction of the study area was used to delineate the level of contaminant plume. This was generated from the DEM using the ArcGIS 10.3 3-D analyst tool function. A water Quality index rating of 1 was measured in the study area which is an indication that the water is very bad. Also, the physiochemical analysis on soil and water revealed poor water and soil. Water analysis showed high concentration of Fe and Zn which made the water in the area unsuitable for drinking. Also, the soil samples recorded high levels of crude content from 1m, with concentration reducing with depth up to 3m. A general contamination map of Okrika/Ogu-bolo was modelled, indicating the contamination rating of the total land mass of the study area, with 23.59km (5.71%) rated very good, while 85.65km (20.71%) were rated good. Also, 140.37km (33.95%) had only showed moderate level of contamination while 112.56km (27.22%) recorded high level of contamination, with 51.29km (12.40%) of the total land mass having a very bad contamination record.
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Hamed, Noor. "Object-Based Method for Urban Extraction through Using Quick Bird Satellite Imagery, LiDAR Data and Digital Urban Geomatics Techniques." Tikrit Journal of Engineering Sciences 28, no. 2 (2021): 1–14. http://dx.doi.org/10.25130/tjes.28.2.01.
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Urban extraction mapping has become increasingly important in recent years and particularity extraction urban features based on remotely sensed data such as highresolution imagery and LiDAR data. Though the researchers used the high spatial resolution image to extract urban area but he methods are still complex and still there are challenges associated with combining data that were acquired over differing time periods using inconsistent standards. So, this study will focus on the extraction of urban area based on an object-based classification method with integration of Quickbird satellite image and digital surface elevation (DSM) extracted from LiDAR data for the Rusafa city of Baghdad, Iraq. All the processes were done in eCognition and ArcGIS software for feature extraction and mapping, respectively. The overall methodological steps proposed in this research for the extraction of urban area using object-based method. In addition of that both the image data and LiDAR-derived DSM were integrated based on the eCognition software for extraction urban map of Rusafa city, Baghdad. Finally, the results indicated that the Artificial Neural Networks (ANN) model achieved the highest training and testing accuracies and performed the best compared to RF and Support Vector Machines (SVM) methods. And also, the results showed that the Artificial Neural Networks (ANN) had capability to extract the boundaries of the buildings and other urban features more accurately than the other two methods. This could be interpreted as the Artificial Neural Networks (ANN) model can learn complex features by the optimization process of the model and its multi-level feature extraction property
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Natsagdorj, B., S. Dalantai, E. Sumiya, et al. "ASSESSMENT OF SOME METEOROLOGY DATA OF AVERAGE MONTHLY AIR TEMPERATURE OVER MONGOLIA USING DIGITAL ELEVATION MODEL (DEM) AND GIS TECHNIQUES." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2021 (June 30, 2021): 117–21. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2021-117-2021.
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Abstract. The climate of Mongolia is a harsh continental climate with four distinctive seasons, high annual and diurnal temperature fluctuations, and low rainfall. Because of the country’s high altitude, it is generally colder than that of other countries in the same latitude. This study focuses on evaluating the suitability of two interpolation methods in terms of their accuracy at the air temperature data in Mongolia. Four data sets of air temperature from 1982 to 2019 in 60 meteorological stations located in Mongolia and elaborated from a 90 m resolution digital elevation model (DEM), latitude and longitude using two interpolation methods. ArcGIS is used to produce the spatially distributed air temperature data by using IDW and ordinary kriging. Three statistical methods are multiple regression, RMSE and bias, which showed that the IDW the best for this data from other methods by the results that have been obtained. Statistics on the latitude, longitude and surface elevation of each of the 37 years in Mongolia at 60 meteorological stations have been statistically valid with dependent coefficients at 95–99.9%. As the average air temperature, recorded at the meteorological stations, had a statistical correlation of −0.606 with latitude, 0.295 with longitude, and −0.432 with altitude, a multiple regression equation was developed and a highly accurate map for long terms air temperature covering 1982–2019 using interpolation IDW and Kriging method. Also, the highest RMSE value for maps used IDW was 1.38 while the lowest and average values were 0.03 and 0.44, respectively, and the highest bias was 1.21, lowest 0.95, and average 1.01. As opposed to, highest RMSE value for maps that used Kriging, was 6.16, lowest 0.27 and average 1.08 while highest bias was 1.29 and lowest was 0.85, with 1.01 as average. This demonstrates that IDW offers much better accuracy as opposed to Kriging and shows less bias errors. When the air temperature map that used the IDW method is compared against the meteorological station data the significance was 0.98 and when compared against ERA5 model results, significance was 0.95 showing strong statistical significance. Also, a comparison of air temperature map, processed by Kriging method and the meteorological station data shows 0.97 statistical significance, and comparison with ERA5 model shows (validation) 0.94 significance, which is very high. The mean value of the calculated temperature regression model in Mongolia and the root mean square error 0.02–0.09 for each station indicates that the estimation method is good and can be used in the future.
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Jaskulski, Marcin, and Tomasz Nowak. "Transformations of Landscape Topography of the Bełchatów Coal Mine (Central Poland) and the Surrounding Area Based on DEM Analysis." ISPRS International Journal of Geo-Information 8, no. 9 (2019): 403. http://dx.doi.org/10.3390/ijgi8090403.
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The authors analyze topography changes related to the construction and operation of the Bełchatów Brown Coal Open Mine and Power Plant, one of Europe’s larger open-pit mines, situated in central Poland. In order to achieve this, a DEM (Digital Elevation Model) is prepared, based on archival materials from the pre-investment period. Source materials include German topographical maps, issued in 1944 by the Supreme High Command of the German Army (Oberkommando des Heeres/Generalstab). The second model of the same area is prepared based on DEM data included in the Topographical Database available by CODGiK (Main Centre of Geodetic and Cartographic Documentation). The preparation of two terrain models from different periods make it possible to evaluate the changes in the morphometry. Both models are compared using ArcGIS (ESRI) tools. The comparative analysis of the models allows for observing topography changes resulting from anthropogenic transformations related to the construction of the Brown Coal Open Mine Bełchatów and Power Plant complex.
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Ijaware, V. A. "GIS based Flood Vulnerability Studies for Ife Central Local Government Area, Osun State, Nigeria." Nigerian Journal of Environmental Sciences and Technology 4, no. 1 (2020): 160–71. http://dx.doi.org/10.36263/nijest.2020.01.0184.
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Flood has negatively affected Ife Central Local Government Area of Osun State, Nigeria. This work is aimed at mapping the vulnerability of the area to flood. Its objectives addressed the ranking of various natural and artificial factors causing flood, the determination and delineation of vulnerability to flood in the study area. Using remote sensing and GIS techniques, coordinates of flooded sites were acquired with Global Navigation Satellite System receiver; Landsat 8 data were acquired from the USGS website. To map land use, elevation data were acquired from the Shuttle Radar Topographic Mission Digital Elevation Models, soil data was obtained from the Nigerian Geological Survey website, and rainfall data was acquired from Tropical Rainfall Measuring Mission satellit. Using Pairwise Comparison, the various weights of factors constituting flood in the area were acquired. Weighted Linear Combination and Analytical Hierarchical Process was used in producing the flood hazard and flood vulnerability maps. ArcGIS 10.2 Software was used in spatial and attribute data acquisition, processing, and information presentation. The Pairwise Comparison method adopted was validated and observed to have a consistency ration of 0.003. Results obtained show that 9.2% of the study area is highly prone to flood hazards 20.4% is prone to flood hazard and 44.3% is moderately prone to flood hazard. The method adopted correctly identifies all existing flood incidence areas within the flood- prone areas in the hazard map. The maps produced will serve as an effective tool to aid the prevention and mitigation of flood disaster in the flood-prone area.
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Greer, Ashton D., Zachary B. Wilbanks, Leah D. Clifton, Bradford Wilson, and Andrew J. Graettinger. "GIS-Enabled Culvert Design: A Case Study in Tuscaloosa, Alabama." Advances in Civil Engineering 2018 (September 19, 2018): 1–10. http://dx.doi.org/10.1155/2018/4648134.
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A GIS-enabled culvert design module is presented. This module employs Python programming to combine a proposed culvert location, topography, land use, and rainfall data to automatically design a culvert. The module is embedded within ESRI ArcGIS 10.4 software, providing a seamless single platform that eliminates error propagation associated with cross-platform data transfer as well as providing 95% time savings over traditional calculation methods. The module uses United States Geological Survey digital elevation data to analyze watershed topography. Runoff coefficients are determined from data available through the National Land Cover Database. Rainfall data are retrieved from the National Oceanic and Atmospheric Administration and combined with watershed and land use information to calculate peak discharge using the rational method. Peak discharge is then combined with culvert design parameters to design a single-barrel culvert. The module was used to redesign ten existing culverts along a highway in Tuscaloosa, Alabama, resulting in designs for updated land cover and rainfall conditions. Results from the techniques developed herein can be used for planning purposes and to highlight vulnerabilities in the existing infrastructure. The automation methods may be extended to other hydrologic objectives and runoff mitigation design such as open-channel design and detention or retention ponds.
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Wang, Xueliang, Haiyang Liu, and Juanjuan Sun. "A New Approach for Identification of Potential Rockfall Source Areas Controlled by Rock Mass Strength at a Regional Scale." Remote Sensing 13, no. 5 (2021): 938. http://dx.doi.org/10.3390/rs13050938.
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The identification of rockfall source areas is a fundamental work for rockfall disaster prevention and mitigation. Based on the Culmann model, a pair of important indicators to estimate the state of slope stability is the relief and slope angles. Considering the limit of field survey and the increasing requirements for identification over a large area, a new approach using the relief–slope angle relationship to identify rockfall source areas controlled by rock mass strength at a regional scale is proposed in this paper. Using data from helicopter-based remote sensing imagery, a digital elevation model of 10 m resolution, and field work, historical rockfalls in the Wolong study area of Tibet where frequent rockfalls occur are identified. A clear inverse relationship between the relief and slope angles of historical rockfalls enables us to calculate the rock mass strength of the landscape scale by the Culmann model and the relief–slope angle relationship curve. Other parameters used in our proposed approach are calculated by ArcGIS and statistic tools. By applying our approach, the potential rockfall source areas in the study are identified and further zoned into three susceptibility classes that could be used as a reference for a regional rockfall susceptibility study. Using the space partition of historical rockfall inventory, our prediction result is validated. Most of the rockfall source areas (i.e., 71.92%) identified in the validation area are occupied by historical rockfalls, which proves the good prediction of our approach. The dominant uncertainty in this paper is derived from the process of calculating rock mass strength, defining the specific area for searching potential rockfall source areas, and the resolution of the digital elevation model.
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Omran, Adel, Kanij Fahmida, Dietrich Schröder, Mohamed O. Arnous, Ahmed E. El-Rayes, and Volker Hochschild. "GIS-based rockfall hazard zones modeling along the coastal Gulf of Aqaba Region, Egypt." Earth Science Informatics 14, no. 2 (2021): 691–709. http://dx.doi.org/10.1007/s12145-021-00580-y.
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AbstractRockfall is a natural hazard in mountainous areas not to be underestimated. Mass activities differing in rock volume may cause considerable economic damage. Accomplishing qualitative appraisal of high-potential zones for rockfall is a first step towards implementing mitigation strategies. Nowadays, Geographical Information Systems (GIS) are the state-of-the-art tool for a fast and economic approach of identifying potential hazard zones rather than using conventional mapping with in-situ field data. Primarily, current research focuses on designing and implementing user-friendly tools delineating potential rockfall hazard zonation (RHZ). The constructed model examines triggering factors like slope, aspect, elevation, lithology, structural lineament, rainfall intensity, and seismic activity focal depth of a mountainous coastal region (Gulf of Aqaba, Egypt). The extracted geomorphological parameters were based on a high-resolution TanDEM-X Digital Elevation Model. The enhanced Landsat ETM + 7 was used to generate the lithological and structural lineament parameters, while the rainfall data were collected from NASA project tool. The zonation model was implemented by means of ESRI’s ArcGIS Pro ModelBuilder. Google Earth Pro orthophotos compared with the generated rockfall hazard zonation map indicate the potential RHZ with high reliability. The achieved results show that 15 % of the study area qualifies as a high rockfall hazard zone. As the RHZs generated by the model depend on the input data and the selected rating scores and weights, obtaining ground truth is essential to get a trustworthy result. Finally, this study recommends employing the built RHZ model on similar terrains worldwide to support decision-makers involving any sustainable development projects.
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Sulistyowati, Anantri, Rachmad Jayadi, and Adam Pamudji Rahardjo. "Unit Hydrograph Modeling using Geomorphological Instantaneous Unit Hydrograph (GIUH) Method." Journal of the Civil Engineering Forum 4, no. 3 (2018): 223. http://dx.doi.org/10.22146/jcef.38860.
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Flood forecasting at Wonogiri Reservoir is restricted on the availability of hydrologic data due to limited monitoring gauges. This issue triggers study of unit hydrograph modeling using Geomorphological Instantaneous Unit Hydrograph (GIUH) which is based on Geographic Information System (GIS). Analysis of physical watershed parameters was conducted on Digital Elevation Model (DEM) data using software Watershed Modeling System (WMS) 10.1 and ArcGIS. Nash model and S-curve method were used to process triangular GIUH into hourly Instantaneous Unit Hydrograph (IUH) and Unit Hydrograph (UH) and then was compared with the observed UH of Collins method. A sensitivity analysis was conducted on parameter of RL and Nash-model k. Evaluation of accuracy of the simulated GIUH runoff hydrograph was also conducted. The GIUH model generated UH with smaller peak discharge Qp, also slower and longer of tp and tb values than the observed UH. Accuracy test of the simulated GIUH runoff hydrograph using Nash-Sutcliffe Efficiency (NSE) shows that Keduang watershed gives a satisfying result, while Wiroko watershed gives less satisfactory result. The inaccuracies occur due to limited flood events used to derive the observed UH and stream tributaries that were not properly modeled based on Strahler method.
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Faisal, Zulvyah, Akhmad Azis, Andi Muhammad Subhan, Sugiarto Badaruddin, and Devi Ayu Puspita. "Spatial Analysis Study on the Flood Impact of WalanaeCenranae River Area in Soppeng Regency South Sulawesi Province." INTEK: Jurnal Penelitian 7, no. 1 (2020): 39. http://dx.doi.org/10.31963/intek.v7i1.2112.
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Cabenge River is part of the WalanaeCenranae River area in Soppeng Regency. Annually, the area around the Cabenge River gets the most losses from floods, both in terms of facilities and infrastructures. This study aims to map the areas prone to flood and flood risk, based on the field that gets the most significant impact. This study uses a Geographic Information System (GIS) as a tool and ArcGis Software in determining the level of vulnerability and risk of flooding at the study site. This type of research is a combination of mapping (topographic results) and map analysis. The variables used are DEM (Digital Elevation Model) data and flood volume. The data processing technique used is the GIS-based inundation model approach using inundation height (H) based on a comparison between the volume of water (V) in inundated areas and the volume of water (Q) of flood sources. The results showed that Lilirilau District was in the high hazard class with an area of 100 km2 and had the biggest impact, while in Liliriaja District, the area that was in a high hazard class was 34 km2 and Ganra District was 21 km2.
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Alves, Marcelo Rodrigo, José A. M. Demattê, and Pedro Paulo Silva Barros. "Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils." Revista Brasileira de Ciência do Solo 39, no. 5 (2015): 1261–74. http://dx.doi.org/10.1590/01000683rbcs20140410.
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ABSTRACT In recent years, geotechnologies as remote and proximal sensing and attributes derived from digital terrain elevation models indicated to be very useful for the description of soil variability. However, these information sources are rarely used together. Therefore, a methodology for assessing and specialize soil classes using the information obtained from remote/proximal sensing, GIS and technical knowledge has been applied and evaluated. Two areas of study, in the State of São Paulo, Brazil, totaling approximately 28.000 ha were used for this work. First, in an area (area 1), conventional pedological mapping was done and from the soil classes found patterns were obtained with the following information: a) spectral information (forms of features and absorption intensity of spectral curves with 350 wavelengths -2,500 nm) of soil samples collected at specific points in the area (according to each soil type); b) obtaining equations for determining chemical and physical properties of the soil from the relationship between the results obtained in the laboratory by the conventional method, the levels of chemical and physical attributes with the spectral data; c) supervised classification of Landsat TM 5 images, in order to detect changes in the size of the soil particles (soil texture); d) relationship between classes relief soils and attributes. Subsequently, the obtained patterns were applied in area 2 obtain pedological classification of soils, but in GIS (ArcGIS). Finally, we developed a conventional pedological mapping in area 2 to which was compared with a digital map, ie the one obtained only with pre certain standards. The proposed methodology had a 79 % accuracy in the first categorical level of Soil Classification System, 60 % accuracy in the second category level and became less useful in the categorical level 3 (37 % accuracy).
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Liu, T., H. Yan, and L. Zhai. "Extract relevant features from DEM for groundwater potential mapping." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W4 (June 26, 2015): 113–19. http://dx.doi.org/10.5194/isprsarchives-xl-7-w4-113-2015.
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Multi-criteria evaluation (MCE) method has been applied much in groundwater potential mapping researches. But when to data scarce areas, it will encounter lots of problems due to limited data. Digital Elevation Model (DEM) is the digital representations of the topography, and has many applications in various fields. Former researches had been approved that much information concerned to groundwater potential mapping (such as geological features, terrain features, hydrology features, etc.) can be extracted from DEM data. This made using DEM data for groundwater potential mapping is feasible. In this research, one of the most widely used and also easy to access data in GIS, DEM data was used to extract information for groundwater potential mapping in batter river basin in Alberta, Canada. First five determining factors for potential ground water mapping were put forward based on previous studies (lineaments and lineament density, drainage networks and its density, topographic wetness index (TWI), relief and convergence Index (CI)). Extraction methods of the five determining factors from DEM were put forward and thematic maps were produced accordingly. Cumulative effects matrix was used for weight assignment, a multi-criteria evaluation process was carried out by ArcGIS software to delineate the potential groundwater map. The final groundwater potential map was divided into five categories, viz., non-potential, poor, moderate, good, and excellent zones. Eventually, the success rate curve was drawn and the area under curve (AUC) was figured out for validation. Validation result showed that the success rate of the model was 79% and approved the method’s feasibility. The method afforded a new way for researches on groundwater management in areas suffers from data scarcity, and also broaden the application area of DEM data.
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Kang, Kai, Andrey Ponomarev, Oleg Zerkal, Shiyuan Huang, and Qigen Lin. "Shallow Landslide Susceptibility Mapping in Sochi Ski-Jump Area Using GIS and Numerical Modelling." ISPRS International Journal of Geo-Information 8, no. 3 (2019): 148. http://dx.doi.org/10.3390/ijgi8030148.
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The mountainous region of Greater Sochi, including the Olympic ski-jump complex area, located in the northern Caucasus, is always subjected to landslides. The weathered mudstone of low strength and potential high-intensity earthquakes are considered as the crucial factors causing slope instability in the ski-jump complex area. This study aims to conduct a seismic slope instability map of the area. A slope map was derived from a digital elevation model (DEM) and calculated using ArcGIS. The numerical modelling of slope stability with various slope angles was conducted using Geostudio. The Spencer method was applied to calculate the slope safety factors (Fs). The pseudostatic analysis was used to compute Fs considering seismic effect. A good correlation between Fs and slope angle was found. Combining these data, sets slope instability maps were achieved. Newmark displacement maps were also drawn according to empirical regression equations. The result shows that the static safety factor map corresponds to the existing slope instability locations in a shallow landslide inventory map. The seismic safety factor maps and Newmark displacement maps may be applied to predict potential landslides of the study area in the case of earthquake occurrence.
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Maina, C. W., and J. M. Raude. "Assessing Land Suitability for Rainwater Harvesting Using Geospatial Techniques: A Case Study of Njoro Catchment, Kenya." Applied and Environmental Soil Science 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/4676435.
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Water demand increases as population increases leading to overexploitation of water resource. Consequently, there is need for improved water resources management complemented with rain water harvesting within the catchments. This study sought to assess land suitability for surface runoff harvesting using geospatial techniques. Land use/land cover maps of the area were derived from Landsat image. Land use and soils data were used in generating curve number map of the catchment. Lineaments greatly affect the storage depending on whether runoff is for surface storage or ground water recharge purposes. As a result, ArcGIS was used in delineating the lineaments from Digital Elevation Model (DEM) of the catchment. Further, using weighted overlay the catchment was grouped into categories of restricted, not suitable, moderately suitable, suitable, or highly suitable. The study found that forest, agriculture, and built-up areas occupied about 39.42%, 36.32%, and 1.35% of catchment area, respectively. A large part of catchment was found to have curve number range of 82–89. About 50% of the catchment was found to fall within suitable and highly suitable categories. This implied that a great potential exists for rain water harvesting within the catchment.
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Sojka, Mariusz, Rafał Wróżyński, and Krzysztof Pyszny. "Application of 3D graphic software and GIS in visual impact assessment of high-voltage overhead transmission lines." E3S Web of Conferences 171 (2020): 02010. http://dx.doi.org/10.1051/e3sconf/202017102010.
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The paper presents the possibility of using GIS tools and 3D graphic software to assess the impact of high voltage overhead transmission lines on the landscape. The paper uses a digital elevation model developed on the basis of airborne laser scanning data. In addition, potential locations and high voltage overhead transmission lines tower heights have been used. The Viewshed tool available in the ArcGIS software made it possible to calculate the visibility range of tower. To limit the spatial range of the analysis 3D simulations were carried out in Blender version 2.79. Visibility range analysis was performed in the range from 250 m to 3000 m in steps of 250 m. The render analysis in relation to the percentage of the area occupied by the HVOTLs tower in the total field of view, allowed to limit the range of the analysis. Calculations have shown that the range of the HVOTLs tower impact assessment should be limited to 2 km. The very strong and strong visual impact of the tower range from 0 to 250 m. In contrast, there is a significant impact between 251 m and 750 m and a moderate and weak impact above 750 m.
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Nirwansyah and Braun. "Mapping Impact of Tidal Flooding on Solar Salt Farming in Northern Java using a Hydrodynamic Model." ISPRS International Journal of Geo-Information 8, no. 10 (2019): 451. http://dx.doi.org/10.3390/ijgi8100451.
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The number of tidal flood events has been increasing in Indonesia in the last decade, especially along the north coast of Java. Hydrodynamic models in combination with Geographic Information System applications are used to assess the impact of high tide events upon the salt production in Cirebon, West Java. Two major flood events in June 2016 and May 2018 were selected for the simulation within inputs of tidal height records, national seamless digital elevation dataset of Indonesia (DEMNAS), Indonesian gridded national bathymetry (BATNAS), and wind data from OGIMET. We used a finite method on MIKE 21 to determine peak water levels, and validation for the velocity component using TPXO9 and Tidal Model Driver (TMD). The benchmark of the inundation is taken from the maximum water level of the simulation. This study utilized ArcGIS for the spatial analysis of tidal flood distribution upon solar salt production area, particularly where the tides are dominated by local factors. The results indicated that during the peak events in June 2016 and May 2018, about 83% to 84% of salt ponds were being inundated, respectively. The accurate identification of flooded areas also provided valuable information for tidal flood assessment of marginal agriculture in data-scarce region.
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Matejicek, L. "Spatial modelling of air pollution in urban areas with GIS: a case study on integrated database development." Advances in Geosciences 4 (August 9, 2005): 63–68. http://dx.doi.org/10.5194/adgeo-4-63-2005.
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Abstract. A wide range of data collected by monitoring systems and by mathematical and physical modelling can be managed in the frame of spatial models developed in GIS. In addition to data management and standard environmental analysis of air pollution, data from remote sensing (aerial and satellite images) can ehance all data sets. In spite of the fact that simulation of air pollutant distribution is carried out by standalone computer systems, the spatial database in the framework of the GIS is used to support decision-making processes in a more efficient way. Mostly, data are included in the map layers as attributes. Other map layers are carried out by the methods of spatial interpolation, raster algebra, and case oriented analysis. A series of extensions is built into the GIS to adapt its functionality. As examples, the spatial models of a flat urban area and a street canyon with extensive traffic polluted with NOx are constructed. Different scales of the spatial models require variable methods of construction, data management, and spatial data sources. The measurement of NOx and O3 by an automatic monitoring system and data from the differential absorption LIDAR are used for investigation of air pollution. Spatial data contain digital maps of both areas, complemented by digital elevation models. Environmental analyses represent spatial interpolations of air pollution that are displayed in horizontal and vertical planes. Case oriented analyses are mostly focused on risk assessment methods. Finally, the LIDAR monitoring results and the results obtained by modelling and spatial analyses are discussed in the context of environmental management of the urban areas. The spatial models and their extensions are developed in the framework of the ESRI's ArcGIS and ArcView programming tools. Aerial and satellite images preprocessed by the ERDAS Imagine represent areas of Prague.
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Rudini, Abd Nasir Matori, Jasmi Ab Talib, and Abdul-Lateef Balogun. "Application of Geographic Information System (GIS) to Model the Hydrocarbon Migration: Case Study from North-East Malay Basin, Malaysia." E3S Web of Conferences 34 (2018): 02027. http://dx.doi.org/10.1051/e3sconf/20183402027.
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The purpose of this study is to model the migration of hydrocarbon using Geographic Information System (GIS). Understanding hydrocarbon migration is important since it can mean the difference between success and failure in oil and gas exploration project. The hydrocarbon migration modeling using geophysical method is still not accurate due to the limitations of available data. In recent years, GIS has emerged as a powerful tool for subsurface mapping and analysis. Recent studies have been carried out about the abilities of GIS to model hydrocarbon migration. Recent advances in GIS support the establishment and monitoring of prediction hydrocarbon migration. The concept, model, and calculation are based on the current geological situation. The spatial data of hydrocarbon reservoirs is determined by its geometry of lithology and geophysical attributes. Top of Group E horizon of north-east Malay basin was selected as the study area due to the occurrence of hydrocarbon migration. Spatial data and attributes data such as seismic data, wells log data and lithology were acquired and processed. Digital Elevation Model (DEM) was constructed from the selected horizon as a result of seismic interpretation using the Petrel software. Furthermore, DEM was processed in ArcGIS as a base map to shown hydrocarbon migration in north-east Malay Basin. Finally, all the data layers were overlaid to produce a map of hydrocarbon migration. A good data was imported to verify the model is correct.