RESEARCH ARTICLE Dense DSM and DTM Point Cloud Generation Using CARTOSAT-2E Satellite Images for High-Resolution Applications V. S. S. N. Gopala Krishna Pendyala 1 • Hemantha Kumar Kalluri 2 • C. V. Rao 1 Received: 21 March 2019 / Accepted: 20 September 2019 Ó Indian Society of Remote Sensing 2019 Abstract The primary objective of this study is to provide a methodology to generate a dense point cloud of digital surface model (DSM) and digital terrain model (DTM) from 0.6 m GSD stereo images acquired by CARTOSAT-2E satellite of the Indian Space Research Organization. These products are required for many high-resolution applications such as mapping of watersheds and watercourses; river flood modeling; analysis of flood depth, landslide, forest structure, and individual trees; design of highway and canal alignment. The proposed method consists of several processes such as orienting the stereo images, DEM point cloud extraction using the semi-global matching, and DSM to DTM filtering. The stereo model is built by performing aero triangulation and block adjustment using the ground control points. The semi-global matching algo- rithm is used on the epipolar images to generate the DSM in the form of dense point cloud corresponding to one height point for each pixel. The planimetric and height accuracies are evaluated using orthoimages and DSM and found to be within 3-pixel (* 2 m) range. A method for extracting DTM by ground point filtering, to discriminate the probable ground points and the non-ground points, is provided by using discrete cosine transformation interpolation. This robust method uses a weight function to differentiate the noise points from the ground points. The overall classification efficiency kappa (j) value averages at 0.92 for ground point classification/DTM extraction. The results of benchmarking of the GPS-aided GEO augmented navigation GPS receiver by operating it over IGS station, in static mode for collecting the checkpoints, also are presented. Keywords High-resolution satellite Á Dense point cloud Á Semi-global matching Á Digital surface model Á Digital terrain model Á Discrete cosine transform Á GAGAN Introduction Digital elevation model (DEM) represents the elevation of land surface referenced to a particular datum recorded in digital form. DEM, often employed as a generic term for digital surface model (DSM) or digital terrain model (DTM), is widely used as input data for terrain-related visualization and modeling applications (Jacobsen 2013). The surface heights derived from the ground reflectance include the vegetation and building features and are termed as a digital surface model (DSM). The surface of the bare earth is represented as a digital terrain model (DTM) and derived from DSM by filtering out vegetation and human- made objects (Arundel et al. 2015; Copernicus 2017). The character of the DEM is represented by two major indi- cators: (1) horizontal spacing/posting and (2) the absolute vertical accuracy (Copernicus 2017). Many global DEMs such as SRTM DEM, Aster GDEM, and CARTODEM are freely available (Jacobsen 2013) with the horizontal posting of 30 m and vertical accuracies ranging from 7 to 20 m. Commercial DEMs such as SPOT DEM, worldDEM, and VRICON are also available with varied postings from 5 m and vertical accuracy of 2 to 5 m (Copernicus 2017). This posting and accuracy are sufficient to meet the applications related to natural resource man- agement, environmental impact assessment, visibility & V. S. S. N. Gopala Krishna Pendyala gopalakrishna_pvssn@nrsc.gov.in 1 National Remote Sensing Centre, Hyderabad, Telangana, India 2 Department of Computer Science and Engineering, Vignan’s Foundation for Science Technology and Research, Vadlamudi, Andhra Pradesh, India 123 Journal of the Indian Society of Remote Sensing https://doi.org/10.1007/s12524-019-01051-0