BULLDOZER: AN AUTOMATIC SELF-DRIVEN LARGE SCALE DTM EXTRACTION METHOD FROM DIGITAL SURFACE MODEL

Abstract. This study presents a Digital Terrain Model extraction method called Bulldozer. The only required input of Bulldozer is Surface generated from any sensors (usually optical or LIDAR) with kind software. After reviewing both the initial DrapCloth algorithm (Zhang et al., 2016) and its multi scale implementation (Leotta 2019), some issues have been highlighted when extracting DTM stereo satellite images such as lost ground adhesion under rising terrain areas, appearance sinks due to correlation computing DSM finally lack scalability processing large data. has developed tackle all these proposes full automatic scalable pipeline composed pre-processing step clean noisy DSMs by detecting smoothing disturbed based on modified stick post-processing smooth sharp sinks. solved using tiling strategy definition stability margin that ensures identical results those obtained if whole would processed at once in memory. As result, outperforms concurrent respect runtime execution while providing high quality DTMs over various types landscapes.