Comparison of Semi Automatic DTM From Image Matching With DTM From Lidar

Abstract

ABSTRACT:Nowadays DTM LIDAR was used extensively for generating contour line in Topographic Map. This method is very superior compared to traditionally stereomodel compilation from aerial images that consume large resource of human operator and very time consuming. Since the improvement of computer vision and digital image processing, it is possible to generate point cloud DSM from aerial images using image matching algorithm. It is also possible to classify point cloud DSM to DTM using the same technique with LIDAR classification and producing DTM which is comparable to DTM LIDAR. This research will study the accuracy difference of both DTMs and the result of DTM in several different condition including urban area and forest area, flat terrain and mountainous terrain, also time calculation for mass production Topographic Map. From statistical data, both methods are able to produce 1:5.000 Topographic Map scale.

A model of spatial location: New data for the Gor River megalithic landscape (Spain) from LiDAR technology and field survey

“…LiDAR uses a pulsed laser beam sent from an aircraft to the ground surface (Chen, 2007; Shan & Aparajithan, 2005). This light is sent and received several times in order to generate a point cloud of the terrain that allows to know its geography in detail by measuring the time that the laser takes to return to the aircraft (Csanyi & Charles, 2007; Kraus & Pfeifer, 2001). Every point in the point cloud is georeferenced by its XYZ coordinates, and it is also classified according to the type of layer that reflected the laser pulse.…”

Comparison of the strip- and block-wise aerial triangulation using different exterior orientation parameters weights

“…Over the past decade, a notable improvement occurred in the field of generating DTM and DSM by photogrammetric image-matching (Jensen and Mathews 2016). The vertical accuracy of photogrammetric DSM is less than ALS's (airborne laser scanning) DTM (Hodgson et al 2003, Rahmayudi and Rizaldy 2016, Simpson et al 2017. ALS point cloud vertical accuracy is usually reported at approximately 1 ~ 20 cm (Ballhorn et al 2009, Estornell et al 2011, Reddy et al 2015, Konecny et al 2016.…”

Digital Deforestation: Comparing Automated Approaches to the Production of Digital Terrain Models (DTMs) in Agisoft Metashape

“…Geometric filters normally used for the processing of ALS data are often applied to IBM data as well [39,40]. Examples of this include the use of algorithms such as the fast Fourier transform [41], cloth simulation filtering [42,43], and a TIN-based filtering approach [38,[44][45][46]. These geometric algorithms are frequently applied using specialized point cloud filtration software tools such as LASGround [46], TerraSolid [45], or LP360 [44].…”

“…Examples of this include the use of algorithms such as the fast Fourier transform [41], cloth simulation filtering [42,43], and a TIN-based filtering approach [38,[44][45][46]. These geometric algorithms are frequently applied using specialized point cloud filtration software tools such as LASGround [46], TerraSolid [45], or LP360 [44]. IBM point clouds can also be classified based on the use of RGB and NIR imagery to identify the spectral signature of points, either through the use of an NDVI threshold [38,47,48] or a machine learning-based classification [47].…”