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Comparison and validation of ASTER-GDEM and SRTM elevation models over parts of Kaduna State, Nigeria by Olalekan Adekunle Isioye and Israel Castro Yang, Ahmadu Bello University, Nigeria, Department of Geomatics, Faculty of Environmental Design Samaru, Zaria, Kaduna state Abstract Digital elevation model (DEM) represents a very important geospatial data type in the analysis and modelling of different hydrological and ecological phenomenon which are required in preserving our immediate environment. DEMs are typically used to represent terrain relief and are particularly relevant for many applications such as soil erosion volume calculations, flood estimate, quantification of earth materials to be moved for channels, roads, dams, embankment etc. This study investigates the quality (in terms of elevation accuracy and relative altitudinal differences) of two publicly available elevation model datasets over parts of Northern Nigeria: (i) the 3 arc second Shuttle Radar Topography Mission (SRTM) ver4.1 from CGIAR-CSI; and (ii) the 1 arc second Advanced Space borne Thermal Emission and Reflection Radiometer Global − DEM (ASTER-GDEM) ver1 from NASA/METI. The main features of these datasets are reported from a geodetic point of view. This study represents a follow up to Isioye and Obarafo, 2010 and Isioye et al., 2012, because it is believed that the significant advances in terms of resolution and coverage made by ASTER GDEM justify the need for a new evaluation of elevation data over the study area. The quality of the two elevation models was assessed in two ways: (i) a comprehensive model-to-model comparison was carried out over the study area, providing insight into random and systematic errors among the elevation data, (ii) external validation was carried out based on GPS control points (GCPs). Two test sites identified as “mountainous” and “flat” terrain in Kajuru/Kaduna and Zaria respectively were used within the study area, results of the correlation test among the two elevation data sets and the 55 GCPs show that ASTER is slightly better correlated in the mountainous terrain than SRTM while SRTM showed a significantly stronger correlation in the flat terrain than ASTER-GDEM on the 58 GCPs used for the site. The overall absolute average vertical errors of ASTER-GDEM are 18,93 ±2,85 m, 16,36 ±2,14 m, while the STRM have 12,52 ±3,25 m, 3,17 ±1,17 m for the Kajuru/Kaduna and Zaria sites respectively. Keywords ASTER-GDEM, SRTM, GPS, digital elevation model (DEM), slope and aspect

Introduction and background

Digital elevation models (DEM) provide basic information on heights of the Earth’s surface and features upon it. The specific terms digital terrain model (DTM) and digital surface model (DSM) are often used to specify the surface objects described by an elevation model. A DTM usually refers the physical surface of the Earth, i.e., it gives elevations of the bare ground (terrain). On the other hand, a DSM describes the upper surface of the landscape. It includes the heights of vegetation, buildings and other surface features, and only gives elevations of the terrain in areas where there is little or no ground cover. DEMs have become an important data source for a range of applications in Earth and environmental sciences. Examples of applications for elevation data are numerous, such as gravity field modeling, hydrological studies, topographic cartography, ortho-rectification of aerial imagery, flood simulation and many more. Generally, DEM datasets can be obtained from range of techniques, such as ground survey e.g., [1], airborne photogrammetric imagery e.g., [2], airborne laser scanning (lidar) e.g., [3], radar altimetry e.g., [4] and interferometric synthetic aperture radar (InSAR) e.g., [5]. Quite often, DEMs are constructed from data sourced from several of these methods and are thus of variable quality e.g., [4, 6, and 7].

Since a number of applications may rely solely on SRTM and/or ASTER DEMs, it is important to assess the quality of these data, i.e., how well does the DEM approximate the shape of the Earth’s surface? Quality of elevation data is commonly expressed in terms of vertical accuracy. It can be determined using comparison data that should be based on accurate and independent methods, such as (terrestrial) topographic surveys, airborne laser scanning or photogrammetric techniques, allowing truly external and independent validation but in the course of this research, the (terrestrial) topographic surveys are being carried out. Another issue affecting the quality of space-based DEMs is the presence of systematic error patterns. For example, this can include artificial structures that are systematically too high or low and therefore not representative of the terrain’s surface. Heights of forest regions or buildings, which are often included in space-collected DEM data (i.e., a DSM), represent an error source for applications exclusively interested in elevations of the terrain (i.e., a DTM). This study is aimed at comparing and validating (in terms of elevation accuracy) SRTM and ASTER Global Digital Elevation Model (GDEM) with GPS Points. The quality of the models is then assessed in two ways. A comprehensive

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model-to-model comparison is carried out over the study area, providing insight into random and systematic effects among the elevation data. External validation is carried out based on two sets of geodetic ground control points (GCPs). This study represents a follow up to [6 and 7], because it is believed that the significant advances in terms of resolution and coverage made by ASTER GDEM justify a new evaluation of elevation data over the study area.

Study area The scope of this study covers some areas within the Northern part of Nigeria. Two sites were chosen based on their relative characteristics of flat and mountainous terrain. The sites are located in Zaria and Kajuru local government areas. Zaria, which was selected as a test site for the flat terrain has met the criteria because of its altitudinal difference of 640 − 685 m, the site is bounded by longitude 7°30’E to 8°00’E of the Greenwich Meridian and latitude 11°00’N to 11°30’N of the Equator with standard topographic map sheet name and number: Zaria; 102 at a scale of 1:100 000. While Kajuru which was selected as a test site for the mountainous terrain has met the criteria because of its altitudinal difference of 594 − 697 m bounded by longitude 7°15’E to 7°45’E of the Greenwich Meridian and latitude 10°15’N to 10°45’N of the equator with standard topographic map sheet name and number: Kaduna And Environs at a scale of 1:100 000. This study is limited to comparison and validation of the ASTER GDEM and SRTM over the selected terrains in the region. A total of 55 and 58 GPS Controls Points (GCPs) were marked and observed in the Kajuru and Zaria sites, respectively. Fig. 1 depicts the study area.

Fig. 1: Map of Nigeria showing the project area.

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Materials and methods

The steps involved in the achievements of this task are shown in the diagram (Fig. 2). These steps comprise three main task levels. The first level involves the data acquisition, the second task level is divided into based on the type of data used; these involve analysing absolute vertical errors and also assessments of topographic characteristics while the third step involves the statistical analysis, results and data representation.

Fig. 2: Schematic diagram of methodology.

Data description and data acquisition Advanced Spaceborne Thermal Emission and Reflection Radiometer GDEM (ASTER GDEM) Advance Spaceborne Thermal Emission Radiometer (ASTER) is an advance multispectral imaging instrument built by METI and operates on the NASA Terra platform. Images are acquired in 14 spectral bands using three separate telescopes and sensor systems. These include three visible and near-infrared (VNIR) bands with a spatial resolution of 15 m, six short-wave-infrared (SWIR) bands with a spatial resolution of 30 m, and five thermal infrared (TIR) bands that have a spatial resolution of 90 m. VNIR Band3 also is acquired using a backward-looking telescope, thus providing along-track stereo coverage from which high-quality digital elevation models (DEMs) are generated as one of a suite of ASTER standard data products. ASTER DEM standard data products are produced with 30 m postings, and have Z accuracies generally between 10 m and 25 m root mean square error (RMSE) [8]. The production of the ASTER GDEM involved automated processing of the entire 1.5-million-scene ASTER archive, including stereo-correlation to produce 1 264 118 individual scene-based ASTER DEMs, cloud masking to remove cloudy pixels, stacking all scene-based DEMs, removing residual bad values and outliers, averaging selected data to create final pixel values, and then correcting residual anomalies before partitioning the data into 1° x 1°tiles.

The seamless data set with voids filled in is available at the website of Consultative Group for International Agriculture Research Consortium for Spatial Information (CGIAR-CSI) via www.gdem.aster.ersdac.or.jp/search.jsp ASTER GDEM data (Figs. 3 and 13) covering the research areas of interest were acquired and downloaded from the seamless dataset website. The downloaded data was masked and reprojected from geographical to Universal Traverse Mercator (UTM) Zone 32N in WGS 84 Datum for absolute vertical error assessment in comparison with GPS GCPs and then, also reprojected to Universal Traverse Mercator (UTM Zone 32) coordinate system in the Minna Datum for topographic characteristics comparison with the topographic map. ASTER GDEM data was converted from raster into a point dataset with attribute table storing elevation values. Thus, each point replicated raster pixel. These point data was used to find the respective GPS GCPs on the ASTER GDEM for absolute vertical assessment. Triangular irregular network (TIN) (Figs. 11 and 21) of the datasets was also produced with topographic characteristics such as Slope (Figs. 7 and 17) and Aspect (Figs. 9 and 19) were created using ArcInfo 9.3 software.

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Shuttle Radar Topographic Mission (SRTM) The Shuttle Radar Topography Mission is an international project spearheaded by the US National Geospatial-Intelligence Agency (NGA) and the US National Aeronautics and Space Administration (NASA) has provided digital elevation model (DEMs) for over 80% of the globe. The SRTM data is available as 3 arc second (approx. 90 m resolution) DEMs. The elevation models are arranged into tiles, each covering one degree of latitude and one degree of longitude, named according to their south western corners. It follows that it stretches from 45°N 6°E to 46°N 7°E and from 45°S 6°W to 44°S 5°W. The resolution of the cells of the source data is one arc second, but 1" (approx. 30 m) data have only been released over United States territory; for the rest of the world, only three-arc-second (approx. 90 m) data are available. Each one arc second tile has 3601 rows, each consisting of 3601 16 bit bigendian cells. The dimensions of the three-arc-second tiles are 1201 x 1201. The vertical errors of the DEMs reported to be less than 16 m. The data currently distributed contains “no- data” holes where water or heavy shadow prevented the quantification of elevation. These are generally small holes, which nevertheless render the data less useful, especially in fields of hydrological modeling. The DEM files of SRTM have been mosaiced into a seamless near-global coverage (up to 60° north and south), and are available for download as 5° x 5° tiles, in geographic coordinate system –WGS84 datum. These files are available for download in both Arc-Info ASCII format of GeoTiff, for easy use in most GIS and remote sensing software applications. In addition a binary data mask file is available for download, allowing users to identify the areas within each DEM which has been interpolated [9].

Meanwhile SRTM data produced a number of voids due to lack of contrast in the radar image, a methodology based on spatial filtering was developed to correct this phenomenon [10]. [Consultative Group for International Agriculture Research Consortium for Spatial Information (CGIAR-CSI) via http://srtm.csi.cgiar.org/. SRTM DEM (Fig. 2.1 and Fig. 2.11)]. The same procedure was carried out for the re-projection, the topographic comparison, conversion from raster to point, each point replicated raster pixels, absolute vertical assessment of the SRTM, Triangular irregular network (TIN) (Figs. 12 and 22) of the datasets was also produced with topographic characteristics such as Slope (Figs. 8 and 18) and Aspect (Figs. 10 and 20) were created using ArcInfo 9.3 software.

DEMs datasets over Kaduna/Kajuru The 1" ASTER GDEM, and the 3" SRTM and, all of which cover Kaduna test site for the mountainous terrain, provide elevation data in regularly spaced grids of geographical coordinates. Generally, they contain physically meaningful height data on the Earth’s topographic form. To a rough approximation, the heights systems in which the satellites imageries conform to, is the ellipsoidal height system.

Fig. 3: ASTER GDEM for Kaduna/Kajuru.

Fig. 4: ASTER GDEM for Kaduna/Kajuru.

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Fig. 5: Contour of ASTER- GDEM for Kaduna/Kajuru .

Fig. 6: Contour of SRTM for Kaduna/Kajuru.

Fig. 7: Slope of ASTER-GDEM for Kaduna/Kajuru.

Fig. 8: Slope of SRTM for Kaduna/Kajuru.

Fig. 9: Aspect of ASTER-GDEM for Kaduna/Kajuru.

Fig. 10: Aspect of SRTM for Kaduna/Kajuru.

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Fig. 11: TIN of ASTER-GDEM for Kaduna/Kajuru.

Fig. 12: TIN of SRTM for Kaduna/Kajuru.

DEMs datasets over Zaria The 1" ASTER GDEM, and the 3" SRTM and, all of which cover Zaria test site for the flat terrain, provide elevation data in regularly spaced grids of geographical coordinates. Generally, they contain physically meaningful height data on the Earth’s topographic form. To a rough approximation, the heights systems in which the satellites imageries conform to, is the ellipsoidal height system.

Fig. 13: ASTER GDEM for Zaria.

Fig. 15: Contours of ASTER GDEM for Zaria.

Fig. 14: SRTM DEM for Zaria.

Fig. 16: Contour of SRTM for Zaria.

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Topographic contour DEM Topographic contour maps covering the areas were acquired, vectorised (Figs. 23 and 24), spot heights were extracted and reprojected to Universal Traverse Mercator projection (UTM Zone 32) system in Minna Datum. Spot heights that were extracted were used to create a triangular irregular network (TIN) which was used to generate aspect and slope.

Fig. 19: Aspect of ASTER GDEM for Zaria.

Fig. 17: Slope of ASTER GDEM for Zaria.

Fig. 21: TIN of ASTER GDEM for Zaria.

Fig. 20: Aspect of SRTM for Zaria.

Fig. 18: Slope of SRTM for Zaria.

Fig. 22: TIN of SRTM for Zaria.

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Fig. 23: Vectorised map of Kaduna.

Fig. 24: Vectorised map of Zaria.

GPS ground control points data Among various methods of accuracy assessment, GPS survey provides the best way to map features on terrain with high accuracy. GPS GCPs data was collected along roads and some locations with specific topographic characteristic (i.e. hill, mountain, water bodies, etc.). The GPS GCPs data of Zaria was obtained from the Department of Geomatics, Ahmadu Bello University Zaria. Observations were precisely carried out with a pair of Sokkia Stratus GPS Systems. When surveying with GPS, the highest possible accuracy of collected data is usually achieved by using a carrier- phase tracking mode. One of the GCPs was used as base for the measurement of other new GCPs using Global Positioning System (GPS). The other point was used as a check point. The base station used in the survey was XSJ37 while the XSJ36 was used as a check point [7].

Kaduna Township and Kajuru hills were obtained from the Ministry of Land and Surveys, Kaduna State. With coordinates of high accuracy obtained with the use of a pair of LEICA GPS systems for observations over a period of time, before such GCPs could be establish making the primary control points in the state, with extreme western point KDCS455 and intermediate points such as; KDCS455T, 456T, 457T, 458T, 459T, with most eastern point KDCS457.T.A as a check. DEM validation and comparison Focusing on evaluating errors in the vertical coordinate (z), estimated as root mean square errors (RMSE) of z. The z coordinate is the only unconstrained value, since x and y coordinates were used to locate corresponding grid cells in all DEMs. Moreover, elevation is the point of interest in the study area because changes in surface elevation over terrain surfaces. The RMSE of z for the various interpolated methods was calculated with respect to evenly distributed spot elevations vectorised from topographic maps. The RMSE of z for the SRTM and ASTER DEM's was calculated with respect to GPS points obtained from the ground. Visualisation techniques (elevation contours aspects and slope maps) were used to examine the representation of topography in each DEM. Difference maps were constructed by subtracting the DEM from topographic data from both the ASTER and SRTM-derived DEMs on a cell-by-cell basis. We examined correlations between vertical differences and topographic characteristics (elevation, slope and aspect). Errors on the flat and rocky terrain (biases) were quantified by performing trend surface analyses on the difference maps. After removing the bias, examine the remaining elevation differences on rocky, forested and flat terrain areas to distinguish the level of these data sets using histograms, summary statistics of the height differences to evaluate their reliability. Result and discussion Data accuracy Table 1 shows statistical data for ASTER GDEM, SRTM and GPS data for Kaduna area, while Table 2 shows descriptive statistics for ASTER GDEM, SRTM and GPS data for Zaria area. Table 3 shows descriptive statistics for altitudinal discrepancy (absolute values) for ASTER GDEM, SRTM and TOPO data for the Kaduna while Table 4 shows descriptive statistics for altitudinal discrepancy (absolute values) for ASTER GDEM, SRTM and TOPO data for the Zaria. Results of t-tests confirm significant differences between data obtained by the ASTER GDEM and SRTM in the study areas using a CI of 95% and obtaining a ρ value for independent measures to be 1,68. Table 5 shows the t-test analysis of altitudinal discrepancies between ASTER GDEM and SRTM over GCPs measurements for Kaduna while

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Table 6 shows the t-test analysis of altitudinal discrepancies between ASTER GDEM and SRTM over GCPs measurements for Zaria. Standard error of the means of ASTER GDEM and SRTM data were found to be 2,8485 and 3,2469 respectively for the Kaduna study area while the standard error of the means of ASTER GDEM and SRTM data were found to be 2,1374 and 1,1662 respectively for the Zaria study area. Standard error of the means of TOPO data were found to be 3,7008 (Kaduna) and 1,5057 (Zaria). Parameters ASTER data SRTM data GPS data

Mean 641,346 647,873 660,447

SEM 6,0079 5,4656 8,4493

Variance 1985,23 1643,00 3926,44

Std. Dev. 44,556 40,534 62,661

Min 598 607 611

Max 780 776 836

Count 55 55 55

Table 1: Statistical data of GCPs, ASTER-GDEM and Table 2: Statistical data of GCPs, ASTER-GDEM and SRTM of Kaduna/Kajuru Site. SRTM of Zaria Site.

Table 3: Altitudinal discrepancies (absolute values) Table 4: Altitudinal discrepancies (absolute values) between elevation data and GCPs of Kaduna/Kajuru Site. between elevation data and GCPs of Zaria Site.

Table 5: T-test analysis of altitudinal discrepancies Table 6: T-test analysis of altitudinal discrepancies (mean values) between ASTER and STRM (mean values) between ASTER and STRM over over GCPs in Kaduna. GCPs in Zaria.

Parameters ASTER data SRTM data TOPO data

Mean 20,0240 13,4968 9,4136

SEM 2,9071 3,3738 3,7008

Std. Dev. 21,5592 25,0206 27,4462

Min -4,0850 -4,6550 -31,3330

Max 82,7770 86,594 80,702

Count 55 55 55

Parameters ASTER data SRTM data TOPO data

Mean 16,3596 3,1699 2,9175

SEM 2,1374 1,1662 1,5057

Std. Dev. 16,2776 8,8815 11,4674

Min -11,0470 -9,5020 -17,9960

Max 57,6310 41,7050 41,5570

Count 58 58 58

95% Confidence interval of the difference

Parameters ASTER data SRTM data

Mean 18,9297 12,5159

SEM 2,8485 3,2469

Mean Diff. 18,8797 12,4659

Test 6,6280 3,8393

Sig. (2-tailed) 1,32E-8 3,12E-4

Lower 13,1758 5,9641

Upper 24,5837 18,9678

ρ value independent measures t-test: ≤1,68

95% Confidence interval of the difference

Parameters ASTER data SRTM data

Mean 16,3596 3,1699

SEM 2,1374 1,1662

Mean Diff. 16,3096 3,1199

Test 7,6307 2,6753

Sig. (2-tailed) 9,73E-3 6,19E-2

Lower 12,0296 0,7846

Upper 20,5896 5,4552

ρ value independent measures t-test: ≤1,68

Parameters ASTER data SRTM data GPS data

Mean 652,948 666,13879 669,3078

SEM 1,5155 1,4610 1,7468

Variance 133,2078 123,8052 176,9613

Std. Dev. 11,5416 11,1268 13,3027

Min 625 642 643,498

Max 678 680 696,705

Count 58 58 58

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Correlation analysis of the datasets

The Pearson’s correlation coefficient test was conducted to ascertain the strength of the linear relationship between the different sets of data and the reference GCPs; this was carried out on both test sites. The correlation analysis test examines each pair of measurement variables to determine whether the two measurement variables tend to move together − that is, whether large values of one variable tend to be associated with large values of the other (positive correlation), whether small values of one variable tend to be associated with large values of the other (negative correlation), or whether values of both variables tend to be unrelated (correlation near 0 (zero)). The value of any correlation coefficient must be between -1 and +1 inclusive. The correlation is statistically significant at the 0,01 level – a 99% degree of confidence. For the Kaduna test (Table 7), the correlation analysis of SRTM and ASTER at which of the datasets closely meets GCPs we can see that ASTER has a slight advantage with value of 0,975466 against SRTM with a value 0,973147. While in the Zaria test (Table 8), the same correlation analysis was carried out and it can be seen that SRTM has exhibited a significant difference in value of 0,749532 against ASTER with value of 0,147223. The test shows that ASTER is reliable in Kaduna (mountainous terrain) while SRTM is more reliable in Zaria (flat terrain).

Slope and aspect influence on ASTER GDEM and SRTM data Slope of the terrain were classified into six classes, also visual comparison revealed significant differences in slope values greater than 20° between ASTER and SRTM in Kaduna, and it was noted that ASTER has more slopes values in the area while SRTM showed less slope values which makes ASTER a significant factor in terms of distribution of the slope meanwhile in the direct comparison between ASTER and SRTM of Zaria the slope values less than 10° are more represented in SRTM which shows a lower inclination and a more precise representation of the ground than ASTER showing more slope values that are greater than 10°. Aspect of the terrain was classified into six classes and found to have influence on the direction of the slope on both data. The highest magnitude of errors was observed for measurements made on slopes facing north (N) and northwest (NW) on both data with a value of ±7°. Correspondingly, ASTER and SRTM measurements underestimated elevations of slopes facing NW and overestimated elevations of slopes facing N for both Kaduna and Zaria. These correlate to the direction of flight path for both space-borne vehicles.

In this study, the quality of the DEM acquired by the ASTER and SRTM was evaluated through comparison with GPS readings and cartographically derived DEMs for both study areas. Comparison was carried out analysing the difference in elevation, relative altitudinal differences and slope angle. These are the analyses deduced from the project: Both slope and aspect characteristics of the terrain have significant impact on accuracy of SRTM data. Comparisons particularly suffer on terrains with slope values higher than 20° in Kaduna and slopes less than10° in Zaria. Aspect of the terrain shows that the highest magnitude of errors was observed for measurements made on slopes facing north (N) and northwest (NW) on both data with a value of ±7° and there was an equal representation of aspect on ASTER and SRTM for both Kaduna and Zaria study area.

The results of accuracy assessment also depend on the number of GPS observations per one stack unit of Raster data. The more availability of GPS readings, the higher the accuracy of the final estimation will be. However, implementation of this approach requires special planning of GPS surveys and considerable additional resources, and was not within the scope of the present study

Pearson correlation test for Kaduna

GCPs

GCPs Pearson correlation 1

SRTM Pearson correlation 0,973147

ASTER Pearson correlation 0,975466

**. Correlation is significant at the 0,01 level (2-tailed). Number of test values = 55. Table 7: Correlation test for Kaduna test.

Pearson correlation test for Zaria

GCPs

GCPs Pearson correlation 1

SRTM Pearson correlation 0,749532

ASTER Pearson correlation 0,147223

**. Correlation is significant at the 0,01 level (2-tailed). Number of test values = 58. Table 8: Correlation test for Zaria test.

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Concluding remarks This study has investigated the validity of two digital elevation models, CGIAR-CSI SRTM ver4.1 and NASA/METI ASTER GDEM ver1 over Kaduna and Zaria, all of which are available free of charge. The basic characteristics of the models were described, comparisons between the two models drawn, and accuracy estimates by means of comparisons against GCPs derived. All models have strengths and weaknesses, which can be summarised as follows: The CGIAR-CSI SRTM ver4.1 elevation data observations come at a 3" resolution. It performs better in the model-to-model comparisons and in the comparisons with GCPs. However, this good result is possibly related to the fact that our GCPs are located in rather relatively flat terrain while in the mountainous areas terrain its results were underemphasised. The ASTER GDEM ver1 elevation data set constructed from optical stereo imagery is provided at a very high grid resolution of 1". The model contains artificial error patterns (stripes and cloud anomalies), which is why METI/NASA consider it to be research-grade only. Moreover, the ASTER elevation showed the low accuracy in the GCPs comparison in the flat terrain but has an improved accuracy in the mountainous terrain. However, this agrees with the formally stated accuracy range of ASTER. ASTER GDEM and SRTM should be viewed as “experimental” or “research grade.” However, ASTER GDEM and SRTM can be used because its potential benefits outweigh its flaws and because the work of the user can help lead to an improved ASTER GDEM and SRTM in the future. Notwithstanding, ASTER GDEM proves to be a prospective mapping tool for mapping of mountainous terrain and SRTM DEM for relatively flat terrain, it is highly recommended that it is not to be used for mapping purpose in Nigeria because of the conflict of differences in vertical datum. For better comparison results to be obtained the Nigerian geoidal data sets, must be up to date.

References

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elevation models over Australia and external validation using ERS-1 satellite radar altimetry, Australian Journal of Earth Sciences 50(2): 157-168. doi: 10.1046/j.1440- 0952.2003.00982.x, 2003.

[5] R.F. Hanssen: Radar interferometry: Data Interpretation and error analysis. Springer, New York, 2001. [6] O.A. Isioye, P.D. Jobin, and T.T. Youngu: An assessment of Digital Elevation Models (DEMs) from

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[7] O.A. Isioye and E.O. Obarafo: Shuttle Radar Topography Mission (SRTM) Elevation data: A contemporary Global Elevation Model for describing the topography of Zaria and its environs. Ife Research Publications on geography (IRPG), Vol. 9, No.1 pp. 221-245, 2010.

[8] ASTER Validation Team. ASTER global DEM validation summary report. Published by the ASTER GDEM Validation Team: METI, NASA and USGS in cooperation with NGA and other colloborators. June 2009, 28 pages. Available online: https://lpdaac.usgs.gov (accessed on 28.07.2009).

[9] T.G. Farr and. M. Kobrick: Shuttle Radar Topography Mission produces a wealth of data, Amer. Geophys. Union Eos, v. 81, pp. 583-585, 2000.

[10] P.L. Guth: “Geomorphometric comparison of ASTER DEM and SRTM”. Join Symposium of ISPRS Technical Commission IV, Orlando, FL, p. 10, 2010.

Contact Olalekan Adekunle Isioye, Ahmadu Bello University, lekkyside4u@yahoo.com