Investigation of Sampling and Interpolation Techniques for DEMs Derived from Different Data Sources
|
|
- Calvin Cole
- 5 years ago
- Views:
Transcription
1 Investigation of Sampling and Interpolation Techniques for DEMs Derived from Different Data Sources FARRAG ALI FARRAG 1 and RAGAB KHALIL 2 1: Assistant professor at Civil Engineering Department, Faculty of Engineering, Assiut University, Egypt. 2:Lecturer at Civil Engineering Department, Faculty of Engineering, Assiut University, Egypt. ملخص:.(GIS). (Interpolation methods) : 1) Inverse distance to a power, 2) Kriging, 3) Radial basis function and 4) Triangulation with linear interpolation. (GPS).(Total Station) (Control points). Interpolation ABSTRACT The Digital Elevation Model (DEM) is an important part of mapping technology. It is used for several purposes including contours derivation, geometric correction of photogrammetric and remote sensing images and Geographic Information System (GIS) applications. There are different procedures and techniques for collecting the data to generate DEMs. These techniques include digitizing contour maps, direct field observations using ground surveying methods, photogrammetric and remote sensing procedures and recently by Global Positioning System (GPS) and laser profiling and laser scanning. Interpolation is often required to create DEM from sparse number of points. In this paper the interpolation accuracy of four methods namely: 1) Inverse distance to a power, 2) Kriging, 3) Radial basis function and 4) Triangulation with linear interpolation are investigated. The investigation was practically performed using GPS and Total Station observations of the same test area for comparative purposes. Eight configurations of control points, which are different in number and distribution are analysed. KEY WORDS: Interpolation methods; DEM; Sampling; Contour map; Accuracy; GPS. 1
2 INTRODUCTION In a DEM, earth s surface is represented as spatially referenced regular grid points where each grid point represents a ground elevation value [2]. DEMs have a wide range of applications in surveying and mapping stated by [9]. A DEM is one of the most widely used data sets for analyzing the terrain and constructing a geographical information system [6]. The DEM also aids automatic recognition of terrain features in town planning and automatic building extraction and offers automated assessment of land resources and attributes [1]. DEMs have a major role to play in hydrological modeling, analysis of visibility and hazard mapping [2]. DEM is very important to the validity of soil erosion model [14]. The DEM technique is becoming a powerful tool for representation of both existing and proposed ground surface in the fields of civil surveying, geology, and mining engineering [4]. DEMs have been used to delineate drainage networks and watershed boundaries, to calculate slope characteristics, to enhance distributed hydrologic models and to produce flow paths of surface runoff [12]. There are different techniques for collecting the data to generate DEMs. DEMs can be created by digitizing contour maps, by direct field observations using ground surveying methods, by photogrammetric and remote sensing procedures and recently by GPS and laser profiling and laser scanning. In this paper the GPS and Total Station observation techniques were used to obtain data for DEM generation. The sampling pattern is an important factor for generating DEM. It may include regular, quasi-regular and irregular modes as stated by [1]. In regular (grid) mode the spot heights are measured in a regular geometric pattern. Quasi-regular mode, in which the data are observed along parallel lines spaced at regular intervals but with data randomly spaced along each line. Irregular mode is the one in which the data are collected at random without regard to their geometric distribution. The grid DEM is the easiest of all to manipulate using machines, even though it is time consuming specially if ground surveying techniques are used for collect the data and it can misrepresent the real surface in areas of highly variable terrain [5]. Configurations for minimizing the field observations are proposed and tested in this paper. Interpolation is one of the most important parts of DEM building [14]. It can be defined as procedure of determining the height of any intermediate point of known planimetric coordinates. Interpolation produces a regularly spaced array of Z values from irregularly spaced XYZ data for contour or surface plots. Estimates obtained from interpolation should reflect the real world physical features by incorporating spatial trends which are present in the point data [13]. In this paper the interpolation accuracy of four methods namely: 1) Inverse distance to a power, 2) Kriging, 3) Radial basis function and 4) Triangulation with linear interpolation (all of which are applicable to grid as well as scattered data), are investigated and practically tested using data obtained by GPS and Total Station observations. These methods were found to be the optimum interpolation methods as resulted by [5]. The mathematical background of the used interpolation techniques can be found in [3, 5, 7, 8, 9 and 11]. 2
3 TESTING PROCEDURE AND DATA PROCESSING An area of m 2 (200 x 200 m) near the new Assiut city (Egypt) formed the study area. Its average elevation is 146 m above mean sea level. 441 three-dimensional coordinates were collected once using Total Station (TS) and once again using GPS. The fieldwork was carried out using Topcon (GTS 712) total station and the GPS technique was performed using two Trimble GPS receivers operating in differential mode. The base receiver was set on a permanent point of known coordinates at Assiut University campus (about 10 km away from the test field), while the other receiver was moved in a marked grid of 10 m intervals which covers the test area. The orthometric height was obtained from that of ellipsoidal height at the observation stations. A grid DEM was then obtained by using the tested interpolation techniques with different configurations of control points (distribution forms). The planimetric coordinates of the points to be interpolated coincide with the points where total station and GPS observations were made. The tested area represents a moderate terrain roughness with standard deviation of 2.76m (TS) and 3.28m (GPS) in heights at 10 m grids. To test the accuracy of each interpolation technique, the number and distribution of control points were selected in two distribution forms that can be described as follows: i- The first form based on using the minimum possible number of control points with a simple common distribution. It contains five different cases similar to the cases proposed by [1] as illustrated in Figure (1). The first case consists of five control points, four of them at the four corners of the test area and one point at the center of the area. In case 2 six control points were used; these were the four corner control points plus two more control points along the center line of the model at equal distances from the point at the center. In case 3 eight control points were used; these were the four corner control points plus four control points at the midsides of the area. A central control point was added to the control points of case 3 to form case 4. In the fifth case, ten control points were used; these were the eight control points of case 3 plus two more control points along the center line of the model at equal distances from the point at the center. In each case, the rest of the known points within the test area were used as check points. ii-the second form based on using the regular spaced control points with different spacing. It contains three different cases of 20, 40 and 50 meters between control points in both x and y directions. THE RESULTS AND ANALYSIS The standard deviation, σ, of the interpolated heights of the test points for each case in both distribution forms of control points was computed as: where σ = [ v ] 2 n 3
4 v = residual of the interpolated heights compared with the measured heights, n = number of the interpolated points in each case for each technique. Case 1 Case 2 Case 3 Case 4 Case 5 Control points Figure (1): Number and distribution of control points in the first form For all cases, 98% of the tested points satisfied the accuracy criteria of 3σ. The results of GPS observations are summarized for form 1 and form 2 in table 1 and table 2, and are graphically represented in figure 2 and figure 3, respectively. Table 1: The standard deviation (m) of the interpolated heights of form 1(GPS data) Case # Control points Inverse distance to power Kriging Radial basis function Triangulation with linear interpolation Table 2: The standard deviation (m) of the interpolated heights of form 2 (GPS data) Case# Point spacing Inverse distance to power Kriging Radial basis function Triangulation with linear interpolation
5 Table 1 indicates that the Kriging and the Radial basis function interpolation methods are the most accurate methods. The second most accurate is Triangulation with linear interpolation method. The accuracy obtained by Inverse distance to power interpolation method is the lowest in all cases of control points. Referring to Figure 2 and comparing case 1 with case 2 and 4 we can notice that the improvement in the accuracy due to one extra control point inside the area is more than that due to four extra control points at the borders. When comparing case 2 with case 5 we can notice that the same accuracy was obtained although case 5 has four extra control points at the borders. We can conclude that the control points inside the study area are more effective than the control points at the borders. Table 2 indicates that the Kriging, Radial basis function and Triangulation with linear interpolation gave the same results. This is also clear from Figure 3. The Inverse distance to power interpolation gave approximately the same results except at spacing 20 m it gave the lowest accuracy. Inverse distance Kriging Radial Basis Triangulation Standard Deviation (m) Case Figure 2: Accuracy of interpolated heights of form 1 (GPS data) 5
6 Standard Deviation (m) Inverse distance Kriging Radial Basis Triangulation Control Points spacing (m) Figure 3: Accuracy of interpolated heights of form 2 (GPS data) The results of all techniques showed improvement in accuracy with the decrease of the spacing between control points. The error range of the heights interpolated is approximately the same for all interpolation techniques and it decreased with increasing the number of control points. This is shown in figure 4 for the form (1) and figure 5 for the form (2) of control points. Inverse distance Kriging Radial basis Triangulation Error Range (m) Case Figure 4: Error range of form 1 (GPS data) 6
7 Inverse distance Kriging Radial basis Triangulation Error Range (m) Control Points spacing (m) Figure 5: Error range of form 2 (GPS data) The same investigations were performed on the data collected using total station. It noticed that similar results were obtained for different cases in both forms of control points. The results of form 1 are summarized in table 3, and are graphically represented in figure 6. Figure 6 shown that increasing the number of control points lead to increase the interpolation accuracy in spite of the location of these control points. The results of TS data are more accurate than the GPS data but the same ordinal and trend of the interpolation methods were obtained as shown in figure 7. Inverse distance to power showed to be the lowest accurate interpolation among the tested techniques. Table 3: The standard deviation (m) of the interpolated heights of form 1(minimum control points) (TS data) Case # Control points Inverse distance to power Kriging Radial basis function Triangulation with linear interpolation
8 Inverse distance Kriging Radial Basis Triangulation Standard Deviation (m) Case Figure 6: Accuracy of interpolated heights of form 1 (TS data) Table 4: The standard deviation (m) of the interpolated heights of form 2 (TS data) Case# Point spacing Inverse distance to power Kriging Radial basis function Triangulation with linear interpolation Standard Deviation (m) Inverse distance Kriging Radial basis Triangulation Control Points spacing (m) Figure 7: Accuracy of interpolated heights of form 2 (TS data) 8
9 The volume of cut and fill from the mean elevation for both GPS and TS data were computed using both control points forms. The results of form 1 are shown in figure 8 for GPS data and in figure 9 for TS data. Comparing case 1 with case 4 and case 2 with case 5, show clearly the effect of the location of control points. Inverse distance Kriging Radial basis Triangulation Error in Volume (m3) Case Figure 8: Error in volume using form 1 (GPS data) Inverse distance Kriging Radial basis Triangulation Error in Volume (m3) Case Figure 9: Error in volume using form 1 (TS data) 9
10 The visual investigation of the effect of number and distribution of control points was carried out by generating perspective views of the original and interpolated DEM. The visual investigation was carried on both GPS and total station data where similar results were obtained. In order to avoid repetition the graphical representation of GPS data is only given as shown in figure 10, figure 11 and figure 12. Figure 10 represents the best case of form 1 (case 5). Figure 11 represents the worst case of form 2 (50 m spacing). Figure 12 represents the best case of form 2 (20 m spacing). In all figures the three-dimensional view of the original DEM obtained by GPS is indicated by (a), while the three-dimensional views of the resulting DEM from Inverse distance, Kriging, Radial basis function and triangulation with linear interpolation methods are indicated by (b), (c), (d) and (e) respectively. By comparing Figures 5b, 5c, 5d and 5e with the original DEM of Figure 5a it becomes clear that no one of them accurately represents the detailed undulation of the original terrain. This indicates that the proposed number and distribution of control points in form 1 is not sufficient to represent the original surface even with the most accurate interpolation technique. Although Figure 6, the worst case of form 2 (regular distribution and spacing of control points), doesn t represent the details of the original terrain, one can notice that, these results are better than those of Figure5. Figure 10: Perspective view of the original GPS-derived DEM (10a) and four derived DEMs of form 1 case 5: Inverse distance (10b), Kriging (10c), Radial basis (10d), Triangulation (10e) 10
11 Figure 11: Perspective view of the original GPS-derived DEM (11a) and four derived DEMs of form 2; 50 m spacing: Inverse distance (11b), Kriging (11c), Radial basis (11d), Triangulation (11e) Figure 12: Perspective view of the original GPS-derived DEM (12a) and four derived DEMs of form 2; 20 m spacing: Inverse distance (12b), Kriging (12c), Radial basis (12d), Triangulation (12e) 11
12 Figure 12 shows clearly that the short spacing between control points leads to good results. The Kriging interpolation technique (Figure 12c) and Radial Basis function (Figure 12d) produced surfaces that are most similar to the original surface (Figure 12a). The surface produced by the Triangulation with linear interpolation technique (Figure 12e) is almost similar to Figures 12c and 12d, and it is the next most accurate followed by the Inverse distance to power technique. CONCLUSIONS From the results and analysis the following remarks could be concluded: 1- The closer the control data to the interpolated points, the better the accuracy of interpolation. These expected results are clear from the tabulated results. 2- Regular spacing sampling provides better results compared with using few control points on the boundaries and a few points inside the tested area (form1), where such configuration is not sufficient to represent details of the surface undulation. 3- The control points that lay inside the tested area are more effective than that at the borders. 4- Kriging interpolation gave the best accuracy for surface representation followed by Radial basis function and triangulation with linear interpolation. 5- For accurate digital representation of ground surfaces of similar terrain roughness, it is recommended to use spacing between control points of 20 m. 6- The used GPS observation technique gave results close to that of the total station observations; but it is recommended to perform further studies on the accuracy of the different GPS observation techniques for DEM generated. REFERENCES 1. Algarni D. and Elhassan, I., 2001 Comparison of thin plate spline, polynomial, C`function and shepard's interpolation techniques with GPS-drived DEM, International journal of Applied Earth observation and Geoinformation, Volume 3, Issue 2, Pages Ardiansyah P. and Yokoyama R., 2002 DEM generation method from contour lines based on the steepest slope segment chain and a monotone interpolation function, ISPRS Journal of Photogrammetry and Remote Sensing, Volume 57, Issues 1-2, November, Pages Driscoll T. and Fornberg B., 2002 "Interpolation in the Limit of Increasingly Flat Radial Basis Functions", Computers and Mathematics with Applications, Volume 43, Pages Du, CH., 1996 An Interpolation Method for Grid-Based Terrain Modelling, the computer journal, Vol. 39, No. 10, pages
13 5. Khalil R., 2003 "The optimum choice for contouring", Civil Engineering Research Magazine (CERM), Al-Azhar University, Egypt, Vol.25, No. 2, April Kim S-B., 2004 Eliminating extrapolation using point distribution criteria in scattered data interpolation, Computer Vision and Image Understanding, Vol. 95, Pages Kim S., Kim T., Park W. and Lee H.K., 1999 An optimal interpolation scheme for producing a DEM from the automated stereo-matching of full-scale SPOT images, Workshop Of ISPRS Working Groups I/1, I/3 And Iv/4 "Sensors And Mapping From Space 1999", Hanover, Germany, Sept 27 To Lazzaro D. and Montefusco L. B., 2002 " Radial basis functions for the multivariate interpolation of large scattered data sets", Journal of Computational and Applied Mathematics, Volume 140, Issues 1-2, Pages Meul M. and Meirvenne M.V.., 2003 Kriging soil texture under different types of nonstationarity, GEODERMA, Volume112, Pages Mohamed A. A., Farrag A. and Khalil R., 1996 Study of some factors affecting the accuracy of DEM, Bulletin of the faculty of Engineering, Assiut University, Volume 24, No. 2, July, Pages SURFER software electronic manual. 12. Wang X. and Yin Z. Y., 1998 "A comparison of drainage networks derived from digital elevation models at two scales", Journal of Hydrology Volume 210, Issues 1-4, September, Pages Wilson C., 1996 Assessment of Two Interpolation Methods, Inverse Distance Weighting and Geostatistical Kriging, /~cwilson/interpolation/interpol.htm. 14. Xie K., Wu Y., Ma X., Liu Y., Liu B. and Hessel R., 2003 Using contour lines to generate digital elevation models for steep slope areas: a case study of the Loess Plateau in North China, CATENA 13
Contents of Lecture. Surface (Terrain) Data Models. Terrain Surface Representation. Sampling in Surface Model DEM
Lecture 13: Advanced Data Models: Terrain mapping and Analysis Contents of Lecture Surface Data Models DEM GRID Model TIN Model Visibility Analysis Geography 373 Spring, 2006 Changjoo Kim 11/29/2006 1
More informationEngineering, Korea Advanced Institute of Science and Technology (hytoiy wpark tjkim Working Group
THE DEVELOPMENT OF AN ACCURATE DEM EXTRACTION STRATEGY FOR SATELLITE IMAGE PAIRS USING EPIPOLARITY OF LINEAR PUSHBROOM SENSORS AND INTELLIGENT INTERPOLATION SCHEME Hae-Yeoun Lee *, Wonkyu Park **, Taejung
More informationIMPROVING THE ACCURACY OF DIGITAL TERRAIN MODELS
STUDIA UNIV. BABEŞ BOLYAI, INFORMATICA, Volume XLV, Number 1, 2000 IMPROVING THE ACCURACY OF DIGITAL TERRAIN MODELS GABRIELA DROJ Abstract. The change from paper maps to GIS, in various kinds of geographical
More informationAUTOMATIC EXTRACTION OF TERRAIN SKELETON LINES FROM DIGITAL ELEVATION MODELS
AUTOMATIC EXTRACTION OF TERRAIN SKELETON LINES FROM DIGITAL ELEVATION MODELS F. Gülgen, T. Gökgöz Yildiz Technical University, Department of Geodetic and Photogrammetric Engineering, 34349 Besiktas Istanbul,
More informationLecture 9. Raster Data Analysis. Tomislav Sapic GIS Technologist Faculty of Natural Resources Management Lakehead University
Lecture 9 Raster Data Analysis Tomislav Sapic GIS Technologist Faculty of Natural Resources Management Lakehead University Raster Data Model The GIS raster data model represents datasets in which square
More informationInternational Journal of Civil Engineering and Geo-Environment. Close-Range Photogrammetry For Landslide Monitoring
International Journal of Civil Engineering and Geo-Environment Journal homepage:http://ijceg.ump.edu.my ISSN:21802742 Close-Range Photogrammetry For Landslide Monitoring Munirah Bt Radin Mohd Mokhtar,
More informationJournal Online Jaringan COT POLIPD (JOJAPS) Accuracy Assessment of Height Coordinate Using Unmanned Aerial Vehicle Images Based On Leveling Height
JOJAPS eissn 2504-8457 Abstract Journal Online Jaringan COT POLIPD (JOJAPS) Accuracy Assessment of Height Coordinate Using Unmanned Aerial Vehicle Images Based On Leveling Height Syamsul Anuar Bin Abu
More informationThe Accuracy of Determining the Volumes Using Close Range Photogrammetry
IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE) e-issn: 2278-1684,p-ISSN: 2320-334X, Volume 12, Issue 2 Ver. VII (Mar - Apr. 2015), PP 10-15 www.iosrjournals.org The Accuracy of Determining
More informationL7 Raster Algorithms
L7 Raster Algorithms NGEN6(TEK23) Algorithms in Geographical Information Systems by: Abdulghani Hasan, updated Nov 216 by Per-Ola Olsson Background Store and analyze the geographic information: Raster
More informationDIGITAL TERRAIN MODELLING. Endre Katona University of Szeged Department of Informatics
DIGITAL TERRAIN MODELLING Endre Katona University of Szeged Department of Informatics katona@inf.u-szeged.hu The problem: data sources data structures algorithms DTM = Digital Terrain Model Terrain function:
More informationGetting Started with Spatial Analyst. Steve Kopp Elizabeth Graham
Getting Started with Spatial Analyst Steve Kopp Elizabeth Graham Spatial Analyst Overview Over 100 geoprocessing tools plus raster functions Raster and vector analysis Construct workflows with ModelBuilder,
More informationEVALUATION OF WORLDVIEW-1 STEREO SCENES AND RELATED 3D PRODUCTS
EVALUATION OF WORLDVIEW-1 STEREO SCENES AND RELATED 3D PRODUCTS Daniela POLI, Kirsten WOLFF, Armin GRUEN Swiss Federal Institute of Technology Institute of Geodesy and Photogrammetry Wolfgang-Pauli-Strasse
More informationApplied Cartography and Introduction to GIS GEOG 2017 EL. Lecture-7 Chapters 13 and 14
Applied Cartography and Introduction to GIS GEOG 2017 EL Lecture-7 Chapters 13 and 14 Data for Terrain Mapping and Analysis DEM (digital elevation model) and TIN (triangulated irregular network) are two
More informationStatistical surfaces and interpolation. This is lecture ten
Statistical surfaces and interpolation This is lecture ten Data models for representation of surfaces So far have considered field and object data models (represented by raster and vector data structures).
More informationImplementation of Flight Simulator using 3-Dimensional Terrain Modeling
Implementation of Flight Simulator using 3-Dimensional Terrain Modeling 1 1, First Author School of Computer Engineering, Hanshin University, Osan City, S. Korea, stryoo@hs.ac.kr Abstract During the last
More informationEstimating the Accuracy of Digital Elevation Model Produced by Surfer Package
International Journal of Computer Science and Telecommunications [Volume 4, Issue 11, November 213] 2 ISSN 247-3338 Estimating the Accuracy of Digital Elevation Model Produced by Surfer Package Dr. Nagi
More informationDigital photogrammetry project with very high-resolution stereo pairs acquired by DigitalGlobe, Inc. satellite Worldview-2
White PAPER Greater area of the City of La Paz, Bolivia Digital photogrammetry project with very high-resolution stereo pairs acquired by DigitalGlobe, Inc. satellite Worldview-2 By: Engineers Nelson Mattie,
More informationCredibility of 3D Volume Computation Using GIS for Pit Excavation and Roadway Constructions
American Journal of Engineering and Applied Sciences Original Research Paper Credibility of 3D Volume Computation Using GIS for Pit Excavation and Roadway Constructions 1,2 Ragab Khalil 1 Department of
More informationCharacterizing Strategies of Fixing Full Scale Models in Construction Photogrammetric Surveying. Ryan Hough and Fei Dai
697 Characterizing Strategies of Fixing Full Scale Models in Construction Photogrammetric Surveying Ryan Hough and Fei Dai West Virginia University, Department of Civil and Environmental Engineering, P.O.
More informationREGISTRATION OF AIRBORNE LASER DATA TO SURFACES GENERATED BY PHOTOGRAMMETRIC MEANS. Y. Postolov, A. Krupnik, K. McIntosh
REGISTRATION OF AIRBORNE LASER DATA TO SURFACES GENERATED BY PHOTOGRAMMETRIC MEANS Y. Postolov, A. Krupnik, K. McIntosh Department of Civil Engineering, Technion Israel Institute of Technology, Haifa,
More informationGetting Started with Spatial Analyst. Steve Kopp Elizabeth Graham
Getting Started with Spatial Analyst Steve Kopp Elizabeth Graham Workshop Overview Fundamentals of using Spatial Analyst What analysis capabilities exist and where to find them How to build a simple site
More informationCPSC 695. Methods for interpolation and analysis of continuing surfaces in GIS Dr. M. Gavrilova
CPSC 695 Methods for interpolation and analysis of continuing surfaces in GIS Dr. M. Gavrilova Overview Data sampling for continuous surfaces Interpolation methods Global interpolation Local interpolation
More informationBUILDING DETECTION AND STRUCTURE LINE EXTRACTION FROM AIRBORNE LIDAR DATA
BUILDING DETECTION AND STRUCTURE LINE EXTRACTION FROM AIRBORNE LIDAR DATA C. K. Wang a,, P.H. Hsu a, * a Dept. of Geomatics, National Cheng Kung University, No.1, University Road, Tainan 701, Taiwan. China-
More informationLiterature review for 3D Design Terrain Models for Construction Plans and GPS Control of Highway Construction Equipment
Literature review for 3D Design Terrain Models for Construction Plans and GPS Control of Highway Construction Equipment Cassie Hintz Construction and Materials Support Center Department of Civil and Environmental
More informationDeriving Appropriate Digital Elevation Model (DEM) from Airborne LIDAR Data and Evaluating the Horizontal Highway Geometry for Transportation Planning
Deriving Appropriate Digital Elevation Model (DEM) from Airborne LIDAR Data and Evaluating the Horizontal Highway Geometry for Transportation Planning Nursu TUNALIOĞLU, Metin SOYCAN, KutalmıGÜMÜ and Taylan
More informationCreating Surfaces. Steve Kopp Steve Lynch
Steve Kopp Steve Lynch Overview Learn the types of surfaces and the data structures used to store them Emphasis on surface interpolation Learn the interpolation workflow Understand how interpolators work
More informationSurface Analysis. Data for Surface Analysis. What are Surfaces 4/22/2010
Surface Analysis Cornell University Data for Surface Analysis Vector Triangulated Irregular Networks (TIN) a surface layer where space is partitioned into a set of non-overlapping triangles Attribute and
More informationAn Improved Method for Watershed Delineation and Computation of Surface Depression Storage. PO Box 6050, Fargo, ND , United States
1113 An Improved Method for Watershed Delineation and Computation of Surface Depression Storage Xuefeng Chu, A.M.ASCE 1,*, Jianli Zhang 1, Yaping Chi 1, Jun Yang 1 1 Department of Civil Engineering (Dept
More informationOn the Selection of an Interpolation Method for Creating a Terrain Model (TM) from LIDAR Data
On the Selection of an Interpolation Method for Creating a Terrain Model (TM) from LIDAR Data Tarig A. Ali Department of Technology and Geomatics East Tennessee State University P. O. Box 70552, Johnson
More informationLecture 6: GIS Spatial Analysis. GE 118: INTRODUCTION TO GIS Engr. Meriam M. Santillan Caraga State University
Lecture 6: GIS Spatial Analysis GE 118: INTRODUCTION TO GIS Engr. Meriam M. Santillan Caraga State University 1 Spatial Data It can be most simply defined as information that describes the distribution
More information[Youn *, 5(11): November 2018] ISSN DOI /zenodo Impact Factor
GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES AUTOMATIC EXTRACTING DEM FROM DSM WITH CONSECUTIVE MORPHOLOGICAL FILTERING Junhee Youn *1 & Tae-Hoon Kim 2 *1,2 Korea Institute of Civil Engineering
More informationA METHOD TO PREDICT ACCURACY OF LEAST SQUARES SURFACE MATCHING FOR AIRBORNE LASER SCANNING DATA SETS
A METHOD TO PREDICT ACCURACY OF LEAST SQUARES SURFACE MATCHING FOR AIRBORNE LASER SCANNING DATA SETS Robert Pâquet School of Engineering, University of Newcastle Callaghan, NSW 238, Australia (rpaquet@mail.newcastle.edu.au)
More informationChapters 1 7: Overview
Chapters 1 7: Overview Photogrammetric mapping: introduction, applications, and tools GNSS/INS-assisted photogrammetric and LiDAR mapping LiDAR mapping: principles, applications, mathematical model, and
More informationGeometric Accuracy Evaluation, DEM Generation and Validation for SPOT-5 Level 1B Stereo Scene
Geometric Accuracy Evaluation, DEM Generation and Validation for SPOT-5 Level 1B Stereo Scene Buyuksalih, G.*, Oruc, M.*, Topan, H.*,.*, Jacobsen, K.** * Karaelmas University Zonguldak, Turkey **University
More informationIntegrating the Generations, FIG Working Week 2008,Stockholm, Sweden June 2008
H. Murat Yilmaz, Aksaray University,Turkey Omer Mutluoglu, Selçuk University, Turkey Murat Yakar, Selçuk University,Turkey Cutting and filling volume calculation are important issues in many engineering
More informationMONO-IMAGE INTERSECTION FOR ORTHOIMAGE REVISION
MONO-IMAGE INTERSECTION FOR ORTHOIMAGE REVISION Mohamed Ibrahim Zahran Associate Professor of Surveying and Photogrammetry Faculty of Engineering at Shoubra, Benha University ABSTRACT This research addresses
More informationAnalysis of different interpolation methods for uphole data using Surfer software
10 th Biennial International Conference & Exposition P 203 Analysis of different interpolation methods for uphole data using Surfer software P. Vohat *, V. Gupta,, T. K. Bordoloi, H. Naswa, G. Singh and
More informationChapters 1 9: Overview
Chapters 1 9: Overview Chapter 1: Introduction Chapters 2 4: Data acquisition Chapters 5 9: Data manipulation Chapter 5: Vertical imagery Chapter 6: Image coordinate measurements and refinements Chapters
More informationGEOGRAPHIC INFORMATION SYSTEMS Lecture 24: Spatial Analyst Continued
GEOGRAPHIC INFORMATION SYSTEMS Lecture 24: Spatial Analyst Continued Spatial Analyst - Spatial Analyst is an ArcGIS extension designed to work with raster data - in lecture I went through a series of demonstrations
More informationFOUR ADVANCES IN HANDLING UNCERTAINTIES IN SPATIAL DATA AND ANALYSIS
FOUR ADVANCES IN HANDLING UNCERTAINTIES IN SPATIAL DATA AND ANALYSIS Wenzhong Shi Advanced Research Centre for Spatial Information Technology Department of Land Surveying and Geo-Informatics The Hong Kong
More informationLecture 4: Digital Elevation Models
Lecture 4: Digital Elevation Models GEOG413/613 Dr. Anthony Jjumba 1 Digital Terrain Modeling Terms: DEM, DTM, DTEM, DSM, DHM not synonyms. The concepts they illustrate are different Digital Terrain Modeling
More informationLearn how to delineate a watershed using the hydrologic modeling wizard
v. 11.0 WMS 11.0 Tutorial Learn how to delineate a watershed using the hydrologic modeling wizard Objectives Import a digital elevation model, compute flow directions, and delineate a watershed and sub-basins
More informationAssimilation of Break line and LiDAR Data within ESRI s Terrain Data Structure (TDS) for creating a Multi-Resolution Terrain Model
Assimilation of Break line and LiDAR Data within ESRI s Terrain Data Structure (TDS) for creating a Multi-Resolution Terrain Model Tarig A. Ali Department of Civil Engineering American University of Sharjah,
More informationA Method to Create a Single Photon LiDAR based Hydro-flattened DEM
A Method to Create a Single Photon LiDAR based Hydro-flattened DEM Sagar Deshpande 1 and Alper Yilmaz 2 1 Surveying Engineering, Ferris State University 2 Department of Civil, Environmental, and Geodetic
More informationGeographical Information System (Dam and Watershed Analysis)
Geographical Information System (Dam and Watershed Analysis) Kumar Digvijay Singh 02D05012 Under Guidance of Prof. Milind Sohoni Outline o Watershed delineation o Sinks, flat areas, flow direction, delineation
More informationSurface Analysis with 3D Analyst
2013 Esri International User Conference July 8 12, 2013 San Diego, California Technical Workshop Surface Analysis with 3D Analyst Khalid H. Duri Esri UC2013. Technical Workshop. Why use 3D GIS? Because
More informationLearn how to delineate a watershed using the hydrologic modeling wizard
v. 10.1 WMS 10.1 Tutorial Learn how to delineate a watershed using the hydrologic modeling wizard Objectives Import a digital elevation model, compute flow directions, and delineate a watershed and sub-basins
More informationSOME stereo image-matching methods require a user-selected
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 3, NO. 2, APRIL 2006 207 Seed Point Selection Method for Triangle Constrained Image Matching Propagation Qing Zhu, Bo Wu, and Zhi-Xiang Xu Abstract In order
More informationContour Simplification with Defined Spatial Accuracy
Contour Simplification with Defined Spatial Accuracy Bulent Cetinkaya, Serdar Aslan, Yavuz Selim Sengun, O. Nuri Cobankaya, Dursun Er Ilgin General Command of Mapping, 06100 Cebeci, Ankara, Turkey bulent.cetinkaya@hgk.mil.tr
More informationSection G. POSITIONAL ACCURACY DEFINITIONS AND PROCEDURES Approved 3/12/02
Section G POSITIONAL ACCURACY DEFINITIONS AND PROCEDURES Approved 3/12/02 1. INTRODUCTION Modern surveying standards use the concept of positional accuracy instead of error of closure. Although the concepts
More informationGIS in agriculture scale farm level - used in agricultural applications - managing crop yields, monitoring crop rotation techniques, and estimate
Types of Input GIS in agriculture scale farm level - used in agricultural applications - managing crop yields, monitoring crop rotation techniques, and estimate soil loss from individual farms or agricultural
More informationCO-REGISTERING AND NORMALIZING STEREO-BASED ELEVATION DATA TO SUPPORT BUILDING DETECTION IN VHR IMAGES
CO-REGISTERING AND NORMALIZING STEREO-BASED ELEVATION DATA TO SUPPORT BUILDING DETECTION IN VHR IMAGES Alaeldin Suliman, Yun Zhang, Raid Al-Tahir Department of Geodesy and Geomatics Engineering, University
More informationEngineering Geology. Engineering Geology is backbone of civil engineering. Topographic Maps. Eng. Iqbal Marie
Engineering Geology Engineering Geology is backbone of civil engineering Topographic Maps Eng. Iqbal Marie Maps: are a two dimensional representation, of an area or region. There are many types of maps,
More informationDIGITAL ROAD PROFILE USING KINEMATIC GPS
ARTIFICIAL SATELLITES, Vol. 44, No. 3 2009 DOI: 10.2478/v10018-009-0023-6 DIGITAL ROAD PROFILE USING KINEMATIC GPS Ashraf Farah Assistant Professor, Aswan-Faculty of Engineering, South Valley University,
More informationAutomatic DTM Extraction from Dense Raw LIDAR Data in Urban Areas
Automatic DTM Extraction from Dense Raw LIDAR Data in Urban Areas Nizar ABO AKEL, Ofer ZILBERSTEIN and Yerach DOYTSHER, Israel Key words: LIDAR, DSM, urban areas, DTM extraction. SUMMARY Although LIDAR
More informationDIGITAL TERRAIN MODELS
DIGITAL TERRAIN MODELS 1 Digital Terrain Models Dr. Mohsen Mostafa Hassan Badawy Remote Sensing Center GENERAL: A Digital Terrain Models (DTM) is defined as the digital representation of the spatial distribution
More informationAUTOMATIC IMAGE ORIENTATION BY USING GIS DATA
AUTOMATIC IMAGE ORIENTATION BY USING GIS DATA Jeffrey J. SHAN Geomatics Engineering, School of Civil Engineering Purdue University IN 47907-1284, West Lafayette, U.S.A. jshan@ecn.purdue.edu Working Group
More informationADS40 Calibration & Verification Process. Udo Tempelmann*, Ludger Hinsken**, Utz Recke*
ADS40 Calibration & Verification Process Udo Tempelmann*, Ludger Hinsken**, Utz Recke* *Leica Geosystems GIS & Mapping GmbH, Switzerland **Ludger Hinsken, Author of ORIMA, Konstanz, Germany Keywords: ADS40,
More informationGeographic Surfaces. David Tenenbaum EEOS 383 UMass Boston
Geographic Surfaces Up to this point, we have talked about spatial data models that operate in two dimensions How about the rd dimension? Surface the continuous variation in space of a third dimension
More informationLIDAR MAPPING FACT SHEET
1. LIDAR THEORY What is lidar? Lidar is an acronym for light detection and ranging. In the mapping industry, this term is used to describe an airborne laser profiling system that produces location and
More informationExercise 1: Introduction to ILWIS with the Riskcity dataset
Exercise 1: Introduction to ILWIS with the Riskcity dataset Expected time: 2.5 hour Data: data from subdirectory: CENN_DVD\ILWIS_ExerciseData\IntroRiskCity Objectives: After this exercise you will be able
More informationSurface Creation & Analysis with 3D Analyst
Esri International User Conference July 23 27 San Diego Convention Center Surface Creation & Analysis with 3D Analyst Khalid Duri Surface Basics Defining the surface Representation of any continuous measurement
More informationifp Universität Stuttgart Performance of IGI AEROcontrol-IId GPS/Inertial System Final Report
Universität Stuttgart Performance of IGI AEROcontrol-IId GPS/Inertial System Final Report Institute for Photogrammetry (ifp) University of Stuttgart ifp Geschwister-Scholl-Str. 24 D M. Cramer: Final report
More informationACCURACY ANALYSIS AND SURFACE MAPPING USING SPOT 5 STEREO DATA
ACCURACY ANALYSIS AND SURFACE MAPPING USING SPOT 5 STEREO DATA Hannes Raggam Joanneum Research, Institute of Digital Image Processing Wastiangasse 6, A-8010 Graz, Austria hannes.raggam@joanneum.at Commission
More informationGenerate Digital Elevation Models Using Laser Altimetry (LIDAR) Data. Christopher Weed
Generate Digital Elevation Models Using Laser Altimetry (LIDAR) Data Christopher Weed Final Report EE 381K Multidimensional Digital Signal Processing December 11, 2000 Abstract A Laser Altimetry (LIDAR)
More informationMULTI-TEMPORAL INTERFEROMETRIC POINT TARGET ANALYSIS
MULTI-TEMPORAL INTERFEROMETRIC POINT TARGET ANALYSIS U. WEGMÜLLER, C. WERNER, T. STROZZI, AND A. WIESMANN Gamma Remote Sensing AG. Thunstrasse 130, CH-3074 Muri (BE), Switzerland wegmuller@gamma-rs.ch,
More informationGenerating 50cm elevation contours from space PhotoSat s s new stereo satellite elevation processing system
Generating 50cm elevation contours from space PhotoSat s s new stereo satellite elevation processing system Gerry Mitchell PhotoSat November 2009 PhotoSat stereo satellite processing history PhotoSat has
More informationExperiments on Generation of 3D Virtual Geographic Environment Based on Laser Scanning Technique
Experiments on Generation of 3D Virtual Geographic Environment Based on Laser Scanning Technique Jie Du 1, Fumio Yamazaki 2 Xiaoyong Chen 3 Apisit Eiumnoh 4, Michiro Kusanagi 3, R.P. Shrestha 4 1 School
More informationN.J.P.L.S. An Introduction to LiDAR Concepts and Applications
N.J.P.L.S. An Introduction to LiDAR Concepts and Applications Presentation Outline LIDAR Data Capture Advantages of Lidar Technology Basics Intensity and Multiple Returns Lidar Accuracy Airborne Laser
More informationDESIGN AND SIMULATION OF SOIL SAVING DAMS IN THE MOUNTAINOUS AREAS BY USING GIS WITH DIGITAL ELEVATION MAP
DESIGN AND SIMULATION OF SOIL SAVING DAMS IN THE MOUNTAINOUS AREAS BY USING GIS WITH DIGITAL ELEVATION MAP KEY WORDS: Erosion,GIS,Hazard,Landslide ABSTRACT Masaaki SHIKADA and Junko YAMASHITA Kanazawa
More informationDijkstra's Algorithm
Shortest Path Algorithm Dijkstra's Algorithm To find the shortest path from the origin node to the destination node No matrix calculation Floyd s Algorithm To find all the shortest paths from the nodes
More informationMassive Data Algorithmics
In the name of Allah Massive Data Algorithmics An Introduction Overview MADALGO SCALGO Basic Concepts The TerraFlow Project STREAM The TerraStream Project TPIE MADALGO- Introduction Center for MAssive
More informationFILTERING OF DIGITAL ELEVATION MODELS
FILTERING OF DIGITAL ELEVATION MODELS Dr. Ing. Karsten Jacobsen Institute for Photogrammetry and Engineering Survey University of Hannover, Germany e-mail: jacobsen@ipi.uni-hannover.de Dr. Ing. Ricardo
More informationACCURACY ANALYSIS FOR NEW CLOSE-RANGE PHOTOGRAMMETRIC SYSTEMS
ACCURACY ANALYSIS FOR NEW CLOSE-RANGE PHOTOGRAMMETRIC SYSTEMS Dr. Mahmoud El-Nokrashy O. ALI Prof. of Photogrammetry, Civil Eng. Al Azhar University, Cairo, Egypt m_ali@starnet.com.eg Dr. Mohamed Ashraf
More informationEVALUATION OF LBTM FOR HRSI RECTIFICATION
EVALUATION OF LBTM FOR HRSI RECTIFICATION Sun Yushan a, Ahmed Shaker b, Wenzhong Shi c a Mapping from space, Key Laboratory of State Bureau of Surveying and Mapping, China Academy Surveying and Mapping
More informationGeographic Information Systems (GIS) Spatial Analyst [10] Dr. Mohammad N. Almasri. [10] Spring 2018 GIS Dr. Mohammad N. Almasri Spatial Analyst
Geographic Information Systems (GIS) Spatial Analyst [10] Dr. Mohammad N. Almasri 1 Preface POINTS, LINES, and POLYGONS are good at representing geographic objects with distinct shapes They are less good
More informationGeostatistics 2D GMS 7.0 TUTORIALS. 1 Introduction. 1.1 Contents
GMS 7.0 TUTORIALS 1 Introduction Two-dimensional geostatistics (interpolation) can be performed in GMS using the 2D Scatter Point module. The module is used to interpolate from sets of 2D scatter points
More informationPRODUCTION AND PRECISION ANALYSIS OF A DIGITAL ORTOPHOTO FROM 1:35000 SCALED AIRPHOTO AS A GIS COVERAGE
PRODUCTION AND PRECISION ANALYSIS OF A DIGITAL ORTOPHOTO FROM 1:35000 SCALED AIRPHOTO AS A GIS COVERAGE Sitki KULUR *, Ozan DIVAN** * Istanbul Technical University, Department of Geodesy and Photogrammetry
More informationLearn the various 3D interpolation methods available in GMS
v. 10.4 GMS 10.4 Tutorial Learn the various 3D interpolation methods available in GMS Objectives Explore the various 3D interpolation algorithms available in GMS, including IDW and kriging. Visualize the
More information3GSM GmbH. Plüddemanngasse 77 A-8010 Graz, Austria Tel Fax:
White Paper Graz, April 2014 3GSM GmbH Plüddemanngasse 77 A-8010 Graz, Austria Tel. +43-316-464744 Fax: +43-316-464744-11 office@3gsm.at www.3gsm.at Measurement and assessment of rock and terrain surfaces
More informationTitle: Improving Your InRoads DTM. Mats Dahlberg Consultant Civil
Title: Improving Your InRoads DTM Mats Dahlberg Consultant Civil Improving Your InRoads Digital Terrain Model (DTM) Digital Terrain Model A digital representation of a surface topography or terrain composed
More informationGEOGRAPHIC INFORMATION SYSTEMS Lecture 25: 3D Analyst
GEOGRAPHIC INFORMATION SYSTEMS Lecture 25: 3D Analyst 3D Analyst - 3D Analyst is an ArcGIS extension designed to work with TIN data (triangulated irregular network) - many of the tools in 3D Analyst also
More informationAUTOMATIC GENERATION OF DIGITAL BUILDING MODELS FOR COMPLEX STRUCTURES FROM LIDAR DATA
AUTOMATIC GENERATION OF DIGITAL BUILDING MODELS FOR COMPLEX STRUCTURES FROM LIDAR DATA Changjae Kim a, Ayman Habib a, *, Yu-Chuan Chang a a Geomatics Engineering, University of Calgary, Canada - habib@geomatics.ucalgary.ca,
More informationRaster Analysis. Overview Neighborhood Analysis Overlay Cost Surfaces. Arthur J. Lembo, Jr. Salisbury University
Raster Analysis Overview Neighborhood Analysis Overlay Cost Surfaces Exam results Mean: 74% STDEV: 15% High: 92 Breakdown: A: 1 B: 2 C: 2 D: 1 F: 2 We will review the exam next Tuesday. Start thinking
More informationWhat can we represent as a Surface?
Geography 38/42:376 GIS II Topic 7: Surface Representation and Analysis (Chang: Chapters 13 & 15) DeMers: Chapter 10 What can we represent as a Surface? Surfaces can be used to represent: Continuously
More informationIn addition, the image registration and geocoding functionality is also available as a separate GEO package.
GAMMA Software information: GAMMA Software supports the entire processing from SAR raw data to products such as digital elevation models, displacement maps and landuse maps. The software is grouped into
More informationApplied GIS a free, international, refereed e-journal (ISSN: )
Applied GIS a free, international, refereed e-journal (ISSN: 1832-5505) URL: http://www.appliedgis.net MANAGING EDITORS: Ray Wyatt ray.wyatt@unimelb.edu.au Jim Peterson Jim.Peterson@arts.monash.edu.au
More informationFOR 474: Forest Inventory. Plot Level Metrics: Getting at Canopy Heights. Plot Level Metrics: What is the Point Cloud Anyway?
FOR 474: Forest Inventory Plot Level Metrics from Lidar Heights Other Plot Measures Sources of Error Readings: See Website Plot Level Metrics: Getting at Canopy Heights Heights are an Implicit Output of
More informationUniversity of West Hungary, Faculty of Geoinformatics. Béla Márkus. Spatial Analysis 5. module SAN5. 3D analysis
University of West Hungary, Faculty of Geoinformatics Béla Márkus Spatial Analysis 5. module SAN5 3D analysis SZÉKESFEHÉRVÁR 2010 The right to this intellectual property is protected by the 1999/LXXVI
More informationSpatial Analysis and Modeling (GIST 4302/5302) Guofeng Cao Department of Geosciences Texas Tech University
Spatial Analysis and Modeling (GIST 4302/5302) Guofeng Cao Department of Geosciences Texas Tech University 1 Outline of This Week Last topic, we learned: Spatial autocorrelation of areal data Spatial regression
More informationGPS/GIS Activities Summary
GPS/GIS Activities Summary Group activities Outdoor activities Use of GPS receivers Use of computers Calculations Relevant to robotics Relevant to agriculture 1. Information technologies in agriculture
More informationTHE CONTOUR TREE - A POWERFUL CONCEPTUAL STRUCTURE FOR REPRESENTING THE RELATIONSHIPS AMONG CONTOUR LINES ON A TOPOGRAPHIC MAP
THE CONTOUR TREE - A POWERFUL CONCEPTUAL STRUCTURE FOR REPRESENTING THE RELATIONSHIPS AMONG CONTOUR LINES ON A TOPOGRAPHIC MAP Adrian ALEXEI*, Mariana BARBARESSO* *Military Equipment and Technologies Research
More informationEXAMINING THE ADVANTAGES OF AIRBORNE LIDAR INTEGRATED WITH GIS IN HYDROLOGIC MODELLING
EXAMINING THE ADVANTAGES OF AIRBORNE LIDAR INTEGRATED WITH GIS IN HYDROLOGIC MODELLING Hakan Celik* 1, H.Gonca Coskun 1, Nuray Bas 1, Oyku Alkan 1 1 Department of Geomatics,, Ayazaga Campus, 34469,. e-
More informationDEVELOPMENT OF ORIENTATION AND DEM/ORTHOIMAGE GENERATION PROGRAM FOR ALOS PRISM
DEVELOPMENT OF ORIENTATION AND DEM/ORTHOIMAGE GENERATION PROGRAM FOR ALOS PRISM Izumi KAMIYA Geographical Survey Institute 1, Kitasato, Tsukuba 305-0811 Japan Tel: (81)-29-864-5944 Fax: (81)-29-864-2655
More informationIntroduction to 3D Analysis. Jinwu Ma Jie Chang Khalid Duri
Introduction to 3D Analysis Jinwu Ma Jie Chang Khalid Duri Area & Volume 3D Analyst Features Detect Change Determine Cut/Fill Calculate Surface Area & Volume Data Management Data Creation Data Conversion
More informationLab 12: Sampling and Interpolation
Lab 12: Sampling and Interpolation What You ll Learn: -Systematic and random sampling -Majority filtering -Stratified sampling -A few basic interpolation methods Videos that show how to copy/paste data
More informationDIGITAL HEIGHT MODELS BY CARTOSAT-1
DIGITAL HEIGHT MODELS BY CARTOSAT-1 K. Jacobsen Institute of Photogrammetry and Geoinformation Leibniz University Hannover, Germany jacobsen@ipi.uni-hannover.de KEY WORDS: high resolution space image,
More informationCHAPTER 5 3D STL PART FROM SURFER GRID DEM DATA
CHAPTER 5 3D STL PART FROM SURFER GRID DEM DATA The Surfer Grid is another widely used DEM file format and found to be suitable for the direct conversion to faceted formats. The chapter begins with an
More informationTERRESTRIAL LASER SCANNER TECHNIC AS A METHOD FOR IDENTIFICATION AREAS OF SLOPS
77 TERRESTRIAL LASER SCANNER TECHNIC AS A METHOD FOR IDENTIFICATION AREAS OF SLOPS Bartłomiej Ćmielewski, Bernard Kontny Institute of Geodesy and Geoinformatics, Wroclaw University of Environmental and
More informationThe Research of Real 3D Modeling in the Digital Heritage Protection of Ancient Architecture
The Research of Real 3D Modeling in the Digital Heritage Protection of Ancient Architecture Conghua Wang 1,2, Shanxin Zhang 1,2, Erping Zhao 1, Xiaodan Guo 1 1. School of Information Engineering Tibet
More information