Shuttle Radar Topography Mission (SRTM) Elevation Data: A Contemporary Global Elevation Model for describing the topography in Zaria and its environs

Abstract

Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model (DEM) has created an unparallel data set of global elevations that is freely available for modeling and environmental applications. The global availability (almost 80% of the Earth surface) of
SRTM data provides baseline information for many type of the worldwide researches. This product presents a great value in the production of topographic map, analysis in ecology, accuracy of precise gravimetric geoid, agriculture, climatology, geology, pedology, geomorphology, environmental modeling, rainfall-runoff studies, landslide hazard zonation, seismic source modeling and hydrological modeling. However, overall assessment of the accuracy of this product requires additional regional studies involving ground truth control and accuracy verification methods with higher level of precision, such as the Global Positioning System (GPS). The study presented in this report is based on two independent datasets collected with GPS system and Topographic map. Statistical analysis included estimation of absolute errors. Data from the various dataset were analyzed independently and in combination. Differences in terrain enabled a good interpretation of results. The results of this study showed that absolute average vertical errors of the SRTM dataset is 5.586 ± 1.001m in Zaria (mean ± S.E.M.). This is significantly better than a standard SRTM accuracy value indicated in its specification (i.e. 16 m). The error values have strong correlation with slope and certain aspect values. The result show good contour and terrain harmonization at contour interval greater than 15m. It was recommended that SRTM dataset and other global elevation datasets be evaluated before put to use. Also, it was further recommended that the application of SRTM dataset in providing terrain correction for the Nigerian Gravimetric Geoid Model will help improve the accuracy of the model which is for now being questioned.