INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 6, No 1, 2015

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1 INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 6, No 1, 2015 Copyright 2010 All rights reserved Integrated Publishing services Research article ISSN Vertical accuracy assessment of SRTM3 V2.1 and aster GDEM V2 using GPS control points for surveying & geo-informatics applications - Case study of Rivers State, Nigeria Menegbo E. M, Doosu P Department of Surveying and Geo-informatics, Rivers State College of Arts and Science, Port Harcourt, Nigeria nenibarini@yahoo.com ABSTRACT This work investigates the vertical accuracy and relevance of two widely available digital elevation models (DEMs) in surveying and Geo-informatics using GPS (Global Positioning System) ground stations. The two DEMS assessed are SRTM3 (Shuttle Radar Topography Mission along with ASTER (Advanced Space borne Thermal Emission Reflectance Radiometer). These datasets are accessed using GPS ground control points in Rivers State, Nigeria. Assuming error (vertical) is distributed normally; the factor is used to calculate the linear error confidence statistical level of 95%. Vertical data accuracy with confidence level of 95% of the RMSE (Root Mean Square Error) is use as the standard measure of accuracy for Vertical Accuracy positioning. Their vertical accuracy with reference to GPS control station used in this study as true heights shows the RMSE for ASTER GDEM V2 and SRTM3 V2.1 is ± m and ± m, with vertical accuracy of ± m and ± m respectively. The SRTM3 and ASTER is suitable for mapping(topographic) within interval of contour of 14m and 18m interval in the region Other includes geomorphologic activities, and estimating the terrain corrections in quasi-geoid modelling in Rivers State. Keywords: Vertical accuracy assessment, ASTER GDEM, SRTM3, and GPS ground control. 1. Introduction Land use planning is one of the essential information for the preparation of construction projects and territorial planning. The attainment of elevations data acquired through on-site survey, with the use of topographical equipment, or in an indirect way using the data generated by sensors installed on orbital platforms. After the availability of SRTM, several studies using this data carried out in different areas, for example, in surveying applications (Koch and Lohmann, 2000) Kervyn et al. (2006) present the merit and demerit of Aster and SRTM topographic mapping in a volcanic. However, the overall accuracy assessment requires more studies at local scales involving control of ground truth and accuracy of test methods with higher precision and accuracy, as the GNSS system. Stevens et al. (2004) observed better representation of the topography of active volcanoes with Aster data than with the SRTM data. Globally, various researches have carried out at local level as Kervyn et al. (2006) pointed out. SRTM3 data referenced horizontally to the WGS84 ellipsoid and vertically to the EGM96 geoid heights (Hoffman and Walter, 2006). SRTM absolute height accuracies result calculated at 9 m in North America (Rodriguez et al., 2006). Submitted on May 2015 published on August

2 This validation present Engineers and Surveyors other professionals free open source dataset and to evaluate their accuracy and relevance. GIS databases assist in the integration of different dataset formats. The result of this work also serves as a calibration for both DEMs for the 71 GPS control points distributed all over the study area (Rivers State). 2. Study area Rivers State is located south-south of Nigeria with capital in Port Harcourt. Part of Rivers state inland is made of mangrove swamps and rainforest tropical Niger Delta. The State (Rivers) lies at latitude 4 45 north and longitude 6 50 east and covers an area of 10,432.3 square kilometres. It has a population of 5,198,716 (census 2006) 3.7% of Nigeria s total and a population density of 468 people per square kilometer. Figure 1: Map showing the study area Rivers State with GPS Controls Figure 1: Map showing the study area DEM and GPS controls Tools - R software, Photomod geographical calculator and ArcGIS 82

3 R is a language and environment for statistical computing and graphics and mapping. R is free and open source software under the terms of the GNU General Public License and is also used for GIS mapping and analysis. R was designed around computer language, and it a uses to additional functionality by defining new functions and packages. For computationallyintensive tasks, C, C++ and FORTRAN code can be linked and called at run time. Advanced users can write C code to manipulate R objects directly. R can be extended using packages. According to CRAN, Maptools package used in this thesis is a function of the Geospatial Data Abstraction Library to read and write GIS data with options to handling Coordinate Referent System (CRS). According to (Racurs, 2008), PHOTOMOD GeoCalculator user manual page 3, the PHOTOMOD GeoCalculator is aim to transform geographical data to different coordinate geodetic system. When you have no ground control point coordinates, you may need to recalculate height system to obtain correct results. PHOTOMOD GeoCalculator includes parameters of predefined geoid for such recalculation EGM-96 (Earth Gravity Model-1996). ArcGIS is a tool for spatial Database management software that enables mapping, data analysis, data management and manipulation, data storage, and advanced predictive modeling. Figure 3: GPS Controls RVOSG X1. 3. Methodology 3.1 Height Relationships According to Dennis and Dru (1996), the relationship between ellipsoid GPS heights (h), and orthometric elevation, H, and geoid (EGM96) height represented as N. These are express in an equation as cited in Dennis and Dru (1996) as ; h = H + N:.(1) h (Ellipsoidal height) = Distance along ellipsoid normal (Q to P) N (Geoid height) = Distance along ellipsoid normal (Q to Po) H (Orthometric height) = Distance along plumb line (Po to P) 83

4 Figure 4: Diagram showing relationships between ellipsoid, geoid and orthometric heights. 3.2 Vertical Accuracy Let: RMSEZ = sqrt[ (Zdata i - Zcheck i)2/n] --- (2) Where; Z data i = coordinate of the vertical i th in checked point of dataset. Z check i = coordinate of the vertical i th in checked point of independent higher accuracy source n = checked points number, i = integer of one to n According to (NSSDA, 1998), its assumed that errors (systematic) should be eliminated. If vertical error is in normal distribution error vertically, the factor used to compute error (linear) of 95% level of statistical confidence as cited by Schultz and Greenwalt, Therefore, vertical accuracy, Accuracy z, deduce as follows as stated by NSSDA (1998): 3.3 Methods Accuracyz = RMSEz * (3) The ASTER GDEM version 2 (GDEM2) and SRTM3 version 2 was downloaded from and Version2_1/SRTM3 respectively. The GPS controls dataset collected from office of the Surveyor-General, Rivers State, Nigeria. Firstly, the two DEM in this study was mosaicked and masked to study area shape files (administrative map of Rivers State) using ArcGIS 10. VTBuilder 1.52 was used to converts DEM to grids to be read in R software enviroment. R software package maptools was used for extraction of DEM based heights in EGM96. Then Photomod geographical calculator was used to converts DEM based heights in EGM96 to ellip-soidal heights. Lastly, Microsoft excels sheet was used for computation of the heights residuals, root-mean-squared error, and accuracy (95% confidence levels). R software was used for linear regression and hypotheses. The methods for evaluation of elevations accuracy of the topographic data using DGPS measurements as shown in figure 3. The details of which are summarized in figure 5 below. 84

5 Figure 5: Flowing chart of GIS methodology of the SRTM3 and ASTER GDEM validation with GPS Control Points. 4. Results and analysis The summary statistics shows minimum error for Aster GDEM V2 and Srtm3 V2.1 are m and m while the maximum errors are m and m with mean errors are m and m. The RMSE error is ± m for Aster GDEM V2 and ± m for SRTM3 V2.1, with vertical accuracy of ± m and ± m respectively. Error parameters Table 1: Statistical Analysis for ASTER, GPS, and SRTM3. Statistical Analysis ASTER SRTM3 GPS ERROR = GDEM DEM Ellipsoidal GPS - Ellipsoidal Ellipsoidal Height (m) ASTER Height (m) Height (m) ERROR= GPS SRTM3 Count Min Max Range Sum Mean SE.Mean Std.Dev RMSE ± ± Accuracyz = *RMSEz ± ± Linear regression was carried out using with the free statistical software R. R2 and 85

6 correlation coefficient (r) values were computed using statistical software R. Figure 6: Figure showing goodness of fit with histograph Figure 7: Figure showing goodness of fit with boxplot. Table 2: Statistical Analysis for ASTER, GPS, and SRTM3. Correlation Coefficient ASTER_HEIGHT with GPS Elevation SRTM3_HEIGHT with GPS Elevation r R

7 4.1 Test of significance between the SRTM, Aster, and GPS elevation The free statistical software R was used to further confirm hypothesis testing with p-values between the two elevation model with GPS elevation of the study area, hypotheses was carried out using a simple t-test of the difference in means between two DEMs and GPS Height within five percent level of significance. Testing of Hypothesis: No correlation between Aster & SRTM, GPS height, Hypothesis Null: H0: ρ = 0 Alternative Hypothesis: H1: ρ 0 Significance Level: 5% Test Statistic: ρ = Pr (Dataset H0) Where; ρ = ρ - value Pr = probability of sampling the dataset H0 = the null hypothesis given that is true. For ASTER AND GPS HEIGHT (note = with equal variance) Two Sample t-tests Data: HEIGHTS3.csv$ASTER_HEIGHT and HEIGHTS3.csv$GPS_Height t = , df = 140, p-value = Alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: Sample estimates: mean of x mean of y For SRTM3 AND GPS HEIGHT (note = with equal variance) Two Sample t-tests Data: HEIGHTS3.csv$SRTM3_HEIGHT and HEIGHTS3.csv$GPS_Height t = , df = 140, p-value = Alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: Sample estimates: Mean of x mean of y Conclusion Results show that, H0: ρ=0 so not accepted (rejected) and H1: ρ 0 is accepted. For p value interpretation different scholars have different suggestion. But for me from the test values with equal variance above, the p-value are , that is 25.5% in Aster and GPS Height, and (0.4%) for SRTM3 and GPS HEIGHT. So, Significance Level at 5% for Aster and GPS the null-hypothesis is true at 25.5%, and for SRTM3 and GPS HEIGHT null hypothesis in favours of an alternative at 0.4% that there is an actual difference in there mean value. 87

8 The linear regression, correlation coefficient (r) used here to measures the strength and linear relationship within the elevations been studied (SRTM and GPS and Aster). Correlation coefficient (r) for SRTM3 is while ASTER is R2 is that is 96% and that is 50% for SRTM3 and ASTER DEMs respectively. For value relatively closer to 1 indication of dataset points is close to line of least square and explain the data variation with dependable accuracy. Histogragh and boxplot shows data distribution. From the boxplot, the length of the box is interquartile range. The middle of the box is the median (50% of data is greater than value middle of dataset), the minimum (smallest sample value), the lower quartile (25%of dataset), the upper quartile and the maximum (largest sample value). 5.1 Summary, Discussion, and Outlook DEMs are very useful for geodetic, geomorphologic, and mapping applications. This study has validated the elevation accuracy of two global DEMs the ASTER and SRTM3. The GPS stations on the ground that covers Rivers State region of Nigeria, has been utilized to evaluate accuracy for these elevation dataset. Their vertical accuracy with reference to GPS ground stations show minimum error for ASTER GDEM V2 and SRTM3 V2.1 are m and m while the maximum errors are m and m, mean errors are m and m. The RMSE error is ± m for Aster GDEM V2 and ± m for SRTM3 V2.1, with vertical accuracy of ± m and ± m respectively. The resullts obtained show that SRTM3 and ASTER can be used to develop terrain model contour map of interval of 14m and 18m interval in the region, since vertical accuracy standard requires 90% of the tested elevation points should be correct among half of the contour line interval as adopted by the United States Geological Survey (USGS) standards cited in USGS For the linear regression, correlation coefficient (r) criterion used to evaluate linear relationship within aster and SRTM dataset. Correlation coefficient (r) for SRTM3 is that is 98% while ASTER is , 71%. The regression fit model, R2 is and for SRTM3 and ASTER DEMs respectively. For value relatively closer to 1 indicates variation within dataset with accuracy reliability. Recommendations drawn here is that each (ASTER and SRTM3 DEMs respectively) DEM can be apply in topographic mapping, geomorphologic activities, geodetic and, and estimating the terrain corrections in quasi-geoid modelling in Rivers State. Future work will contain solutions for horizontal accuracy validation for mapping and precise local geoid modelling using GPS heights. Acknowledgement I wish to thank all people who have provided support and encouragement for this research and its outcomes. I would also like to thank Surveyor-General of Rivers State, Surveyor Gaius Assor and Surv. Peter Ogolo for the GPS controls and administrative map of Rivers state used for this this research. To my late father my appreciation for your ideas and dream for my success. 6. References 1. Dennis G. M., and Dru A. S., (1996), Converting GPS Height into NAVD88 Elevation with the GEOID96 Geoid Height Model. 88

9 2. Greenwalt C.R. and M.E. Schultz, (1968), Principles and Error Theory and Cartographic Applications, ACIC Technical Report No. 96: St. Louis, Mo., Aeronautical Chart and Information Centre, U.S. Air Force, 89 p. National Mapping Division, 1987, Procedure Manual for Map. 3. Hoffman J. and Walter, D. (2006), How Complimentary are SRTM-X and C Band Digital Elevation Models? In Photogrammetric Engineering & Remote Sensing, 72(3), pp Kervyn M., Goossens, R., Jacobs, P. & Ernst, G.G.J. (2006), Mapping volcano Topography with remote sensing: ASTER vs. SRTM. International Journal of Remote Sensing. 5. Koch A., Lohmann P. (2000), validation and assessment Quality and of digital surface derived models from the shuttle radar topography mission (SRTM), Proceedings, The International Archives of the, Photogrammetry, Remote Sensing and Spatial Information Sciences, 33, Amsterdam, National Bureau of Statistics State Information. 7. Rodriguez, E., C.S. Morris, J.E. Belz (2006), A global assessment of the SRTM performance, Photogrammetric Engineering and Remote Sensing Journal, 72, pp Stevens, N. F., Garbeil, H., Mouginis-Mark, P.J. (2004), NASA EOS Terra ASTER: Volcanic topographic mapping and capability, Remote Sensing of Environment, 90, pp Subcommittee for Base Cartographic Data, (1998), Geospatial Positioning Accuracy Standards: Federal Geographic Data Committee, chapter USGS (U.S. Geological Survey) (1999), Map accuracy standards, USGS Fact Sheet , November. 89

Keywords: ASTER, SRTM, Digital Elevation Model, GPS-Levelling data, Validation.

Keywords: ASTER, SRTM, Digital Elevation Model, GPS-Levelling data, Validation. www.sgem.org ACCURACY ASSESSMENT OF ASTER AND SRTM DIGITAL ELEVATION MODELS: A CASE STUDY IN TURKEY H. Tugba Arli IL 1 Dr. R. Alpay ABBAK 2 1 Ministry of Health - Turkey 2 Selcuk University - Turkey ABSTRACT