WELCOME TO THE XXV FIG CONGRESS, KUALA LUMPUR, MALAYSIA, 16 TH 21 ST JUNE, 2014.

WELCOME TO THE XXV FIG CONGRESS, KUALA LUMPUR, MALAYSIA, 16 TH 21 ST JUNE, 2014. TS08H - Geospatial Data Processing 3 (Commission: 3) From Spot Heights to Cell Heights: the Data Structure and the Dynamics of the Digital Elevation Model BY DR. A.C. CHUKWUOCHA 1 AND MRS NGOZI AC-CHUKWUOCHA 2 1 Department of Surveying and Geoinformatics, Federal University of Technology Owerri, Nigeria 2 Department of Environmental Technology, Federal University of Technology Owerri, Nigeria 1 achukwuocha@yahoo.com; 2 chukwuochang@yahoo.com 2

1.0 INTRODUCTION The central place of topography in all aspects of environmental evolution and phenomena has been noted. Topography is a critical factor in soil-forming processes because it influences a number of factors including hydrological and thermal regimes of soils through climatic and meteorological characteristics. Topography is also at the base of gravity-driven lateral transportation of water and other substances both at the surface and subsurface levels. Spatial distribution of vegetation cover is influenced by topography due to the interaction of scaled endogenous and exogenous processes. 3 INTRODUCTION contd. Equally, topography of an area can be a pointer to the geological structure of the terrain.(florinsky, 2012). All these show the centrality of the topographic information as is increasingly being employed in qualitative and quantitative analyses in the geosciences. The need to improve the knowledge of how terrain features such as topography, soil type and vegetation, interact with atmospheric events to create environmental phenomena including flooding and erosion are at the foundations of the growing drive to account for the contribution of each piece oflandinitsownform. 4

INTRODUCTION contd. What has become of keener interest is not as much of digitalization of topographic data as it is the piecewise quantitative topographic characterization of every bit of landscape in the area of interest. The very dynamic DEM structure calls the surveyors to move the structuring of topographical information from spot heights structure to cell heights structure data formats thatmaydirectlybeusedinvarioustypesofanalysesofthe terrain topography This paper while presenting the trends of research in continuous topographical surface representations is also a call for the review of the curricula of topographical surveying, digital cartography, and GIS for surveyors to include the basic training needed for expressing topographical information in Digital Elevation Model (DEM) structures and of using the DEM in environmental analyses. 5 Commonly Associated Terms The term DEM, is increasingly being associated with grid cell representation of the bare earth terrain surface that are populated with elevation values of the ground they represent. A Digital Terrain Model (DTM) is an elevation model of the bare earth terrain surface, based on Triangulated Irregular Network (TIN) including breaklines and linework to help define edges of TIN triangles, or to enforce the downward flow of water in the drainage feature. The DEM or DTM may be employed with other measurable environmental phenomena in Digital Terrain Analyses (DTA) that leads to modelling land based phenomena. For instance the DEM or the DTM may be employed in runoff flow Digital Terrain Analysis, based on rain storm event leading to runoff flow modelling needed for delineation of drainage routes, erosion modelling, and flooding vulnerability studies, etc.

Some DEM based Terrain Phenomena Analyses A number of the evolving terrain phenomena analyses include: Delineation of hydrological features such as streams, drainage routes and ridges, Sediment transportation analyses Demarcation and characterization of subcatchments of watersheds, Erosion potential modelling, Flood potential modelling and their derivatives such as flood cost analyses. 7 Some DEM based Terrain Phenomena Analyses Contd. morphological analysis of landforms, site and route selection analyses in civil engineering. inter-visibility analyses Terrain analyses in soil and geological sciences Analyses for delineation of physiographic units andsoon. 8

2.0 TRENDS IN DIGITAL ELEVATION MODELLING Since adapting electronics in surveying, topographic data has been stored electronically as digital data in discrete x, y, z form especially as spot heights Contour lines are stored in digital forms with the identity of their elevation values and populated by sequential points of x, y coordinates and generated in computer graphics with spline (smoothening polynomial) functions. The digital contour and spot height are deficient for quantitative environmental analyses because the elevation so defined do not characterize defined land units. Two types of Digital Elevation Models are becoming established as normative. The grid Digital Elevation Model (DEM) and the Triangulated Irregular Network (TIN) are proving very useful forms of the Digital Elevation Model. 9 1.1 Study Area 2.1 The Triangulated Irregular Network(TIN) The Triangulated Irregular Network (TIN) is an irregular assemblage of planar triangles which vertexes (nodes) are formed at points known in 3 D (x, y, z). These vertexes are carefully chosen to meet triangulation and the Delaunay conditions. i) The basic figure so formed are only triangles. ii) The entire land space is completely divided into triangles iii) No edges of triangles should intersect at a point thatisnotavertex. iv) No vertex of the triangles is inside the circumcircle of any of the triangles - the Delaunay condition. 10

2.1.1 Conditions for Triangular IrregulatedNetworks (TIN) Fig 1: The TIN Triangulation and Delaunay Conditions. 11 2.2 The Grid Digital Elevation Model In a grid Digital Elevation Model, the land space is divided into a grid of rectangular cells, where each cell value represents the elevation of the land surface. The DEM internal data structure may be a constant elevation or an averaging function at the center point inside the square (Kreveld, 1996). Due to the efficiency of the grid DEM, the term Digital Elevation Model is increasingly being associated with the grid form only (Maidment, 2002). 12

2.2.1LAYOUT OF THE GRID DIGITAL ELEVATION MODEL Fig 2: The grid Digital XXV International Elevation Federation of Model Surveyors scheme. 13 2.2.2MATHEMATICS OF REPRESENTING THE TOPOGRAPHIC SURFACE WITH DEM The mathematics of the representation of the topographic surface with a DEM could address relatively small areas so that the assumption of plane holds. Two-dimensional(piecewise) continuous functions may be used to define relatively small portions of the topographic surface (Jancaitis, 1978; Strakhov, 2007; Florinsky, 2012). For large areas, the fact of a curvilinear surface would imply that spherical functions be used to define the topography of such areas Schroder and Sweldens (2000); Wieczorek,(2007); Florinsky(2012) 14

2.2.3 DIGITAL ELEVATION MODEL SIZES The grid Digital Elevation Model divides the entire landscape under question into regularly sized rectangular elevation cells using grids. If the DEM cell represents a very large area in non-flat areas, the credibility of the DEM will be in question and the result of the mathematics will not match natural occurrences in the field. The choice of the size of cells should be masterfully carried out as a linearization of topographical polynomials of the morphology of land space, so that when integrated, the result of the linearization will match the result of executing the polynomial directly to a very reasonable extent. Smaller cell sizes where possible will be advised. This however places a challenge on the computer memory, and is only necessary if there is enough data to populate each cell uniquely. 15 2.2.4 ADVANTAGES OF GRID DEM The use of contour lines and triangulated irregular networks for delineating catchment boundaries and flow paths may provide reliable results, however, they require extensive data storage and computation time. The computational efficiency and the availability of topographic databases are making the grid cell elevation model gain widespread application for analyzing hydrological problems (Bertolo, 2000). The simplicity of the grid DEM and its adaptability makes it the most popular one considering that it has been repeatedly argued that DEMs should be generated considering critical elements of the topographic surface. Florinsky,(2012); Mark,(1979). Furthermore, gridded DEMs have been shown to produce higher accuracy than TIN-based DEMs Kumler,(1994). Since morphometric variables are usually derived from gridded DEMs, the use of plane grids is reasonable. To convert irregular grids to regular ones will require further interpolation (Florinsky, 2012). 16

3.0 APPLICATION ISSUES OF THE DEM The method of Digital Elevation Model assigns elevation value to each unit of horizontal area. Unlike the traditional forms of topographic representation, such as the spot height and the contour, every point in the DEM has an elevation value. These DEM cells can be attributed further with other terrain characteristics such as vegetation, soil type, erosivity, etc. These attributes may be done either as single cells or in clusters representing some geographical zones of uniform characteristics in different terrain models. Some major weaknesses of the DEM include that it generalizes the elevationofeachcellandmakestheterrainappeartobeasystem ofsteps.howeverthecellsizeofthedemcanbemadeextremely small that for all practical purposes the cell size will represent a spot relative to the size of the landscape. This will only challenge the memory space and processing speed of the computer as the number of cells increases. 17 3.0 contd. APPLICATION ISSUES OF THE DEM DEM data have become an integral part of geographic information systems(gis). Areas of terrain analyses where DEM are already being employed include: Hydrological modelling for flood simulation. Delineation and analyses of watersheds and drainage networks. Soil erosion and sediment transport modelling. Landslide hazard assessment plus delineation and study of physiographic units. 18

3.0 contd. APPLICATION ISSUES OF THE DEM Geomorphological evaluation of landforms plus soil and ecological studies. The DEM is also being employed in civil engineering and military applications including site and route analyses, and inter-visibility analyses. The DEM is equally being used for 3D analysis for enhancement of remotely sensed image. Digital topographic data are essential components of groundwater and climatic models. DEM has the advantage of not being blurred by land cover features which is often the case when stereoaerial photograph interpretation and remotely sensed image analysis are used in creating DTMs (Jordan, 2007). 19 3.1 Sources and Accuracies of DEM GROUND SURVEYS o Ground survey methods produce only heights of spots to mm accuracies which may then be interpolated to get the DEM. o It is limited in the area it can cover. Global Navigational Satellite Systems (GNSS) and photogrammetric surveys are useful in this regard as the GNSS provide for faster production of highly accurate ground controls while the photogrammetric methods using the established ground controls provide for a far wider coverage of the land space with elevation accuracies comparable to purely ground survey methods. REMOTELY SENSED DATA o The Remote sensing data sources make it possible to determine heightsofeachcellofthedemdirectly. oin this case then the elevation of each cell is determined theoretically by aggregating all the heights possible in each cell. o However the remotely sensed data sources have their own accuracy issues and will definitely affect the accuracy of the DEM derivative. 20

3.1 contd. Sources and Accuracies of DEM ACCURACIES o Ground Survey methods have achieved DEM of 0.60m over a very wide area(author s lab result). o For heights from SPOT images standard deviations of 2.97m for flat and open terrain and 3.66m for forest areas have been achieved. ofor heights from SRTM X-band 3.97m for open and 4.49m for forest areas have been achieved. owhile for SRTM C-band, 4.25m for open and 6.14m for forest areas have been achieved and for ASTER 7.29mforopenand8.08mforforestareashavebeen achieved(sefercik et al, 2007). 21 3.2 A Sample Application of Digital Elevation Model in Delineating Drainage Routes A sample use of the DEM in environmental phenomenon analyses was carried out in Owerri South East Nigeria to determine the storm water runoff natural flow routes using a DEMoftheprojectarea. 22

Fig. 3.1a Map of Nigeria with XXV LGAs, International showing Federation Imo of Surveyors State South East Nigeria in deep red colour 23 216000.000000 2000.000000 450000.000000 462000.000000 474000.000000 486000.000000 498000.000000 Orsu 510000.000000 522000.000000 Ideato North 534000.000000 546000.000000 558000.000000 216000.000000 2000.000000. Okigwe Legend 198000.000000 Orlu Ideato South Unuimo 198000.000000 Study area boundary imo state <all other values> LGAS Aboh-Mbaise Ahazu Mbaise Oru West Nkwere Ehime Mbano Ezinihitte Mbaise 189000.000000 Oru East Mjaba Isu Nwangele 189000.000000 Ideato North Ideato South Ikeduru Isiala Mbano Isu Oguta Isiala Mbano Ehime Mbano Mbaitolu Mjaba 180000.000000 180000.000000 Ngor-Okpala Nkwere Nwangele Obowo Oguta Mbaitolu Obowo Ohaji/Egbema Okigwe Orlu 1000.000000 Ikeduru Ahazu Mbaise 1000.000000 Orsu Oru East Oru West Owerri Municipal Owerri North Owerri West Unuimo Subcatchments 162000.000000 Owerri West Owerri Municipal Text Owerri North Aboh-Mbaise Ezinihitte Mbaise 162000.000000 <all other values> Area 320.05350896 360.276453488 461.573081563 466.2301963 487.3011449 Ohaji/Egbema 495.2605097 153000.000000 153000.000000 495.736435724 615.032625947 628.2323178 631.90240374 652.461431266 653.824198211 3.1645103 3.981928217 144000.000000 Ngor-Okpala 144000.000000 725.350858253 744.662830032 8.883640897 886.3175499 1157.54464801 1158.1022 1251.65930107 135000.000000 135000.000000 1477.021535 1942.42028488 450000.000000 462000.000000 474000.000000 486000.000000 498000.000000 510000.000000 522000.000000 534000.000000 546000.000000 558000.000000 Scale: 1:250,000 30 15 0 30 Kilometers Fig. 3.1b Map of Imo State with LGAs, showing the project area in red 24

Fig 3c: Map of the Project Area 25 A FLOW CHART OF THE Delineation of Drainage Routes and Sub-catchments INPUT DATA Topographical data of the project area DIGITAL DATA CAPTURE Scanning, Georeferencing and Digitizing of topographical maps, ground survey data, photogrammetric data, Satellite images, SRTM, ASTER, LIDAR data etc DATA PROCESSING Conversion of Topo Data to Digital Elevation Model (DEM) Check for Adequacy of Topo Data, Errors and Sinks in the Digital Elevation Model (DEM) Processing the DEM to produce Flow Direction Grid Processing the Flow Direction Grid to produce Flow Accumulation Grid Processing the Flow Direction & Flow Accumulation Grids to produce the Stream Segmentation Grid (Stream Link Grid) Processing the Flow Direction Grid and the Stream Link Grid to produce the Drainage Line Feature Class DELINEATED RUNOFF FLOW ROUTE OF THE PROJECT AREA Fig. 4 Flow Chart of the DEM based delineation of drainage routes and sub-catchments 26

3.2.1 DATA ACQUISITION The research essentially involved the analysis of topographic data of the about 186.024 Sq. Km,(18,602.3857308 Ha) project area. Thankfully topographic maps of the wide area of coverage of Owerri Nucleus area were made available by the Imo State Surveyor General and the Head of the Survey Department, Owerri Capital Development Authority. 27 500000.000000 505000.000000 510000.000000 515000.000000 520000.000000 174000.000000 1000.000000-174000.000000 1000.000000 159000.000000 162000.000000 162000.000000 165000.000000 165000.000000 1000.000000 1000.000000 Scale: 1:100,000 5 2.5 0 5 Kilometers 159000.000000 156000.000000 500000.000000 505000.000000 510000.000000 515000.000000 520000.000000 156000.000000 Fig. 5 Georeferenced Topo Maps of the Project Area in mosaic 28

THE RESULTING DIGITAL CONTOUR OF THE PROJECT AREA 514000.000000 518000.000000 12 5 103 12 1 67 6 8 67 165000.000000 Contours 162000.000000 62 50 62 46 525 4 6 0 67 50 65 52 51 65 64 62 5 49 8 49 42 Legend 60 66 11 6 72 1000.000000 97 125 123 123 105 111 127 96 11 6 113 124 73 128 112 120 59 74 7 73 2 66 57 54 57 59 56 56 58 54 59 60 58 59 56 57 56 55 53 51 55 4 11 6 1 11 12 72 65 4 62 6 55 66 76 76 1000.000000 1000.000000 104 107 165000.000000 112 0 11 76 66 65 67 66 510000.000000 514000.000000 Scale: 1:100,000 0 2.5 118 122 112 6 90 80 80 81 18 10 2 1 00 6 84 86 12 06 1 48 82 8 1 84 89 83 86 84 0 74 88 8 67 66 83 506000.000000 5 77 72 502000.000000 162000.000000 109 119 113 94 84 57 159000.000000 3 11 94 123 5 12 12 3 123-12 6 109 115 10 95 9 95 9 9 97 101 11 9 11 0 107 1 12 2 12 72 72 0 72 7 57 58 57 56 54 4 12 1 23 4 7 2 122 12 1 121 57 58 59 59 123 67 61 61 60 498000.000000 58 128 10 117 9 12 6 12 7 123 12 113 124 4 125 10 4 120 16 109 5 66 79 93 2 23 122 1 1 1 86 114 114 111 72 11 123 63 72 80 11 9 104 3 115 61 60 7 109 11 115 67 10 74 116 117 11 123 63 9 79 96 92 9 3 2 8 64 80 8 2 1 94 12 62 1 1 88 10 120 4 86 8 62 73 66 67 7 86 94 65 88 67 72 86 8 6 0 7 90 64 67 65 6 62 66 8 67 7 8 58 6758 62 6 64 66 4 0 0 64 7 60 0 52 66 67 72 0 7 9 6 67 65 62 59 7 6 67 64 67 66 66 67 65 57 59 58 54 63 62 8 44 4 6 5 55 58 65 8 5 73 58 59 82 78 8 12 127 127 76 76 72 65 65 63 62 67 65 61 64 60 66 63 65 62 7 61 6 65 60 63 56 61 9 61 5 57 57 2 61 58 57 66 6 60 59 56 59 59 59 61 58 62 11 9 10 2 125 67 7 7 5 2 75 127 74 12 9 128 8 9 10 0 0 9 11 125 7 5 3 85 11 10 124 120 17 118 115 119 1 63 2 6 2 5 66 11 15 62 8 03 9 62 1 10 1 93 60 55 63 117 4 56 6 3 6 6 62 94 5 81 118 11 64 56 67 2 2 89 8 3 66 11 10 7 55 55 6 77 3 91 8 76 74 11 55 66 2 98 7 80 57 61 54 6 91 5 8 6 5 10 7 63 64 6 89 4 92 6 7 73 67 82 7 8 2 66 64 90 84 6 6 74 72 77 7 72 7 67 11 8 78 75 77 75 75 77 76 74 74 76 77 77 174000.000000 510000.000000 1000.000000 506000.000000 159000.000000 502000.000000 174000.000000 498000.000000 518000.000000 5 Kilometers Congress, Kuala Lumpur, Malaysia, 16 21 Fig. 6 Resulting Contour of the Project Area 29 504000.000000 508000.000000 512000.000000 516000.000000 1000.000000 166000.000000 163000.000000 160000.000000 160000.000000 163000.000000 166000.000000 1000.000000 172000.000000 4 175000.000000 500000.000000 172000.000000 496000.000000 175000.000000 THE RESULTING DIGITAL SPOT HEIGHT OF THE PROJECT AREA 496000.000000 500000.000000 504000.000000 508000.000000 0 2 512000.000000 4 516000.000000 8 Kilometers Scale: 1:100,000 Fig. 7 Resulting Congress, SpotKuala Height of 16the Lumpur, Malaysia, 21 Project Area 30

3.2.2 DATA PROCESSING AND ANALYSIS DEMThe Digital Elevation Model (DEM) created in ArcGISusing the contour features. The DEM is a digital grid in which each cell holds the elevation value of the land space the cell represents. 31 Fig. 8 Screen Print ofdemof the Project Area 3.2.3 DEM VALIDATION The DEM was validated using orthometric heights derived from GPS surveys of random points across the project area. The full details are in the paper proper. But Table 1 shows the statistics Table 1: Statistics of the Validation: GPS orthometric height value minus DEM value Only Points All Points 1-57 5-57 Range 9.374 3.934 Average -0.509 0.173 RMSE XXV International Federation 1.947 of Surveyors 0.598 32

COMPARING WITH OTHER POSSIBLE SOURCES OF DEM SOURCES RMSE Open Areas OF DEMRMSE Forest Areas SPOT -flat terrain 2.97m 3.66m SRTM X-band 3.97m 4.49m SRTM C-band 4.25m 6.14m ASTER 7.29m 8.08m Validated Topo Map Without and outlier distorted site 0.598m With 2% outlier of badly distorted site 1.947m 33 32 NW 64 N 128 NE 16 W 1 E 8 SW 4 S 2 SE Fig. 9 Flow Direction Scheme 34

141 140 140 141 142 142 141 142 139 138 137 139 139 139 139 140 138 135 135 136 137 136 137 139 134 134 132 134 135 134 136 138 131 131 129 133 133 132 134 137 128 127 126 132 131 130 132 133 126 123 124 126 128 129 131 133 124 120 125 127 129 129 130 132 DIGITAL ELEVATION MODEL 2 2 4 8 4 4 4 8 2 4 4 8 2 4 8 8 4 2 4 8 2 4 8 2 4 2 4 8 2 4 8 8 2 2 4 8 2 4 8 4 2 4 4 8 8 8 16 16 2 4 16 16 16 16 16 16 1 0 16 32 32 32 16 16 FLOW DIRECTION SCHEME Fig. 10 Digital Flow Direction Scheme 35 Figure 11 Flow Accumulation Grid 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Figure 12 Drainage Route Cells 36

Runoff Flow Routes Figure 13 Drainage Route 37 20-cell Stream Definition Grid Scheme 498000.000000 502000.000000 506000.000000 510000.000000 514000.000000 1000.000000-1000.000000 162000.000000 162000.000000 165000.000000 165000.000000 1000.000000 1000.000000 Legend 159000.000000 OwDrainageLine20 1 159000.000000 498000.000000 502000.000000 506000.000000 510000.000000 Scale: 1:82,2 3 1.5 0 3 Kilometers 514000.000000 Fig. 14 Stream Definition XXV International Grid Federation of the of Surveyors project area using 20 cell accumulation threshold 38

140-cell Stream Definition Grid Contd. The resulting Stream Definition Grid is shown hereunder 498000.000000 502000.000000 506000.000000 510000.000000 514000.000000 1000.000000-162000.000000 162000.000000 165000.000000 165000.000000 1000.000000 1000.000000 1000.000000 Legend 159000.000000 OwDrainageLine 1 159000.000000 498000.000000 502000.000000 506000.000000 510000.000000 Scale: 1:82,575 3 1.5 0 3 Kilometers 514000.000000 Fig. 15 Stream XXV International Definition Federation of Surveyors Grid of 140 cell accumulation threshold 39 498000.000000 Drainage Line Processing 502000.000000 506000.000000 510000.000000 514000.000000 1000.000000-162000.000000 162000.000000 165000.000000 1000.000000 165000.000000 1000.000000 1000.000000 Legend 159000.000000 OwDrainageLine 159000.000000 498000.000000 502000.000000 506000.000000 510000.000000 Scale: 1:82,575 3 1.5 0 3 Kilometers 514000.000000 Fig. 16 Owerri Drainage Network. 40

Manually generated drainage area polygons with the drainage lines creates the drainage map 498000.000000 502000.000000 506000.000000 510000.000000 514000.000000 1000.000000 8.883641 466.2302 320.053509-1000.000000 1477.0215 1251.659301 461.573082 1000.000000 725.350858 653.824198 744.66283 360.276453 Legend OwDrainageLine Subcatchments 1000.000000 <all other values> Area 3.981928 886.3175 320.05350896 165000.000000 495.736436 652.461431 360.276453488 461.573081563 466.2301963 487.3011449 495.2605097 165000.000000 631.902404 495.736435724 615.032625947 628.2323178 631.90240374 162000.000000 487.3011 1157.544648 3.164517 1942.420285 652.461431266 653.824198211 3.1645103 3.981928217 162000.000000 628.2323 1158.1 725.350858253 744.662830032 8.883640897 886.3175499 159000.000000 615.032626 495.2605 1157.54464801 1158.1022 1251.65930107 1477.021535 1942.42028488 159000.000000 498000.000000 502000.000000 506000.000000 510000.000000 Scale: 1:82,575 3 1.5 0 3 Kilometers 514000.000000 Fig. 17 Drainage Map of Owerri 41 3.2.5 SITE VALIDATION OF DRAINAGE AREAS On 6 th October 2011 and 20 th July 2012 visits weretakento 3 ofthesitesdelineatedinthe analyses to be drainage lines to check their state of flooding or otherwise after the rains. It was discovered that they were heavily flooded. The photographs presented hereunder are those of the visited sites.. 42

Works Layout Area 6 th October 2011 : Conduit C11 series. Fully developed pond now due to high runoff coefficient of a developed urban area. Plate 1 43 Works Layout Area6 th October 2011 : Conduit C11 series. Plate 2 44

Works Layout Area, 6 th October 2011: Conduit C11 series. Congress, Kuala Plate Lumpur, Malaysia, 3 16 21 45 Federal Housing Estate 20 th July 2012: C14 series Plate 4 46

Federal Housing Estate: 20th July 2012 C14 series Congress, Kuala Lumpur, Malaysia, 16 21 Plate 5 47 Federal Housing Estate: 20th July 2012 C14 series Congress, Kuala Lumpur, Malaysia, 16 21 Plate 6 48

Federal Housing Estate:20 th July 2012 C14 series Plate 7 49 Chukwuma Nwoha Road Area 20 July, 2012: C14 series Plate 8 50

3.2.6 Results and Discussion The demarcation of the natural flow routes holds an advantage in selecting best drainage routes for the drainage network design of the city. This is very useful both in designing the main network of a virgin area for future development, or when responding to drainage needs of an already existing urban area. The demarcated flow routes are of high advantage in drainage design since the slope of the routes, their lengths and their end coordinates are extracted as resultsoftheresearchonagisplatform. The results of the research also include the delineation and characterization of the straight units of the flow routes and the determined 23 sub-catchments of the project area of Owerri. 51 3.2.6 Results and Discussion Contd. These are very important tools in flood mitigation, erosion control, urban area planning, urban development monitoring and management, engineering design of drainage facilities, the studies of distribution of water borne diseases, sediment transportation and agriculture. The results of the research demonstrate the importance of the DEM in the analyses of flow environmental phenomena such as erosion, sediment transportation and flooding analyses andmodellingandsoon. 52

4.0 SURVEYOR -EDUCATION ISSUES FOR DEM DEVELOPMENT Training curricula of Colleges and Universities in the developing world are reviewed relatively slowly. The need to develop curricula that equip students of Surveying and Geoinformatics in Nigeria and possibly other parts with the necessary skills required for the processing and application of the highly dynamic topographical data structures of the Digital Elevation Models is obvious. It has been suggested elsewhere that the need to continually developing and improving efficient algorithms on terrains is an interesting area of research. It notes that the GIS developers, GIS researchers, and computational geometers can work together to develop a number of elegant and efficient solutions to practical problems on terrains. The analysis of efficiency of these solutions should be based on realistic assumptions on terrains Kreveld(1996). 53 4.0 CONCLUSION AND RECOMMENDATION 54

4.1 CONCLUSION It is obvious that the Digital Elevation Model (DEM) is the way forward for quantitative and qualitative oriented topographical and environmental analyses. In the entire field of the geosciences the use of the DEM for terrain phenomenon characterizing and modelling and Digital Terrain Analysis (DTA) is obviously unlimited. The DEM has been shown to be the most important factor in the Digital Terrain Model and this is an indicator of the central position of properly skilled surveyors across the field of the geosciences. 55 4.2 RECOMMENDATIONS DEM development as a computational science is being driven by computational geometry. The need however remains for the role of the surveyors given the complex issues of datum transformations, geoidal models, accurate geospatial measurements and georeferencing or geolocation for all geospatial analyses. The call for the development of curricula of the institutions that train surveyors to include training for skills needed for expressing topographic data in the Digital Elevation Data Structure and for effective application of the DEM is inevitable. 56

THANK YOU 57 References 1. Bertolo, F., 2000,Catchment Delineation and Characterization,EC-JRC, (EUR 19563 EN), Space Applications Institute, Joint Research Center, European Commission, Ispra(VA), Italy http://agrienv.jrc.it/publications/pdfs/catchrev.pdf 2. Florinsky, I. V., 2012, Digital Terrain Analysis in Soil Science and Geology, Elsevier, Oxford. http://www.isprs.org/proceedings/xxxvi/1- W51/paper/Sefercik_jac_oruc_maramgoz.pdf 3. Jancaitis, J. R., 1978, Elevation Data Compaction by Polynomial Modeling. Report No. ETL-0140, p. 42, Fort Belvoir, VA: U.S., Army Engineer Topographic Laboratories. 4. Jordan, G., 2007, Digital Terrain Analysis in a GIS Environment: Concepts and Development: Digital Terrain Modeling. pp 1-43, Berlin Heidelberg, Springer- Verlag 5. Kreveld, M.V., 1996, Digital Elevation Models: Overview and Selected TIN Algorithms, In Course Notes for the CISM Advanced School on Algorithmic Foundations of Geographic Information Systems. www.cs.uu.nl/docs/vakken/gis/tinalg.pdf 6. Kumler, M. P., 1994, An Intensive Comparison of Triangulated Irregular Networks (TINs) and Digital Elevation Models(DEMs). Cartographica, 31, 1_99. 58

References Contd. 7. Lo, C. P. andyeung, A.K.W., 2002, Concepts and Techniques of Geographic Information Systems, New Jersey, Prentice Hall, Inc. 8. Maidment, D.R. ed., 2002, Arc Hydro: GIS for Water Resources, California, ESRI.. 8. Mark, D. M., 1979, Phenomenon-Based Data-Structuring and Digital Terrain Modelling. Geo-Processing, 1, 27_36. 9. Mark, D. M., 1984, Automated Detection of Drainage Networks from Digital Elevation Models. Cartographica, 21, 1_178. 10.Schroder, P., & Sweldens, W., 2000, Spherical Wavelets: Efficiently Representing Functions on a Sphere. Lecture Notes in Earth Sciences, 90, 158_188. 11.Sefercik, U., Jacobsen, K., Oruc, M., Marangoz, A., 2007, Comparison of SPOT, SRTM, and ASTER DEMs, Proc. International Society of Photogrammetry and Remote SensingXXXVI-1/W51. 12.Strakhov, V. N., 200, Change of epochs in Earth sciences. Russian Journal of Earth Sciences, 9, ES1001, doi:10.2205/2007es000217. 13.Wieczorek, M. A., 2007, Gravity and Topography of the Terrestrial Planets, In T. Spohn(ed.), Treatise on Geophysics, Vol. 10, pp. 165_206, Amsterdam Elsevier. 59