scholarly journals On evaluation of the digital terrain model generated from the LiDAR data of Lithuanian territory

2014 ◽  
Author(s):  
Dominykas Šlikas ◽  
Aušra Kalantaitė ◽  
Boleslovas Krikštaponis ◽  
Eimuntas Kazimieras Paršeliūnas ◽  
Rosita Birvydienė
Keyword(s):  
Digital Terrain Model ◽  
Lidar Data ◽  
Terrain Model ◽  
Digital Terrain

scholarly journals ACCURACY ASSESSMENT OF LIDAR-DERIVED DIGITAL TERRAIN MODEL (DTM) WITH DIFFERENT SLOPE AND CANOPY COVER IN TROPICAL FOREST REGION

2015 ◽  
Vol II-2/W2 ◽  
pp. 183-189 ◽  
Author(s):  
M. R. M. Salleh ◽  
Z. Ismail ◽  
M. Z. A. Rahman
Keyword(s):  
Tropical Forest ◽  
Digital Terrain Model ◽  
Canopy Cover ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Terrain Model ◽  
Digital Terrain ◽  
Terrain Slope ◽  
Airborne Lidar Data

Airborne Light Detection and Ranging (LiDAR) technology has been widely used recent years especially in generating high accuracy of Digital Terrain Model (DTM). High density and good quality of airborne LiDAR data promises a high quality of DTM. This study focussing on the analysing the error associated with the density of vegetation cover (canopy cover) and terrain slope in a LiDAR derived-DTM value in a tropical forest environment in Bentong, State of Pahang, Malaysia. Airborne LiDAR data were collected can be consider as low density captured by Reigl system mounted on an aircraft. The ground filtering procedure use adaptive triangulation irregular network (ATIN) algorithm technique in producing ground points. Next, the ground control points (GCPs) used in generating the reference DTM and these DTM was used for slope classification and the point clouds belong to non-ground are then used in determining the relative percentage of canopy cover. The results show that terrain slope has high correlation for both study area (0.993 and 0.870) with the RMSE of the LiDAR-derived DTM. This is similar to canopy cover where high value of correlation (0.989 and 0.924) obtained. This indicates that the accuracy of airborne LiDAR-derived DTM is significantly affected by terrain slope and canopy caver of study area.

scholarly journals The use of modern technologies in the surveying field

2021 ◽  
Vol 342 ◽  
pp. 02016
Author(s):  
Lucian Octavian Dragomir ◽  
Roxana Claudia Herbei ◽  
Mihai Valentin Herbei
Keyword(s):  
Aerial Photography ◽  
Laser Scanning ◽  
Spatial Information ◽  
Digital Terrain Model ◽  
Support Network ◽  
Lidar Data ◽  
Terrain Model ◽  
Digital Terrain ◽  
Data Realization ◽  
Modern Technologies

In order to achieve or complete the 1: 1.000 scale situation plan and the digital terrain model for the Timişoara - Sibiu highway section, and given the difficult access conditions in the project area, it was decided to use photogrammetric techniques for extraction of spatial information needed for mapping. In order to achieve the mapping requirements at a scale of 1: 1.000, the following activities were performed: Realization of the geodetic support network; Realization of the aerial photography project; Making pre-marking points in areas without clear details or other location possibilities; Simultaneous aerial photography of sub-blocks at different flight heights to ensure a 12 cm pixel and simultaneous laser scanning with LiDAR system; Identification of marking and pre-marking points on the subblock frames; Performing GPS measurements to determine the coordinates of landmarks and photogrammetric pre-marking; LIDAR data processing using permanent GPS stations to obtain coordinates in the ETRS89 system and transform them into the STEREO70 system and Black Sea reference plan 75; Calibration of LIDAR data; Filtering LIDAR data; Realization of aerotriangulation on subblocks or bands; Stereo restitution of planimetric and altimetric details for 1: 1.000 scale (3D mode); Transforming 3D plans into 2D plans; Editing and elaborating topographic plans.

scholarly journals Automatic LIDAR building segmentation based on DGCNN and euclidean clustering

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Ahmad Gamal ◽  
Ari Wibisono ◽  
Satrio Bagus Wicaksono ◽  
Muhammad Alvin Abyan ◽  
Nur Hamid ◽  
...  
Keyword(s):  
Digital Terrain Model ◽  
Primary Source ◽  
Surface Model ◽  
Lidar Data ◽  
Dynamic Graph ◽  
Urban And Regional Planning ◽  
Terrain Model ◽  
Digital Terrain ◽  
Digital Elevation ◽  
Elevation Model

AbstractThere has been growing demand for 3D modeling from earth observations, especially for purposes of urban and regional planning and management. The results of 3D observations has slowly become the primary source of data in terms of policy determination and infrastructure planning. In this research, we presented an automatic building segmentation method that directly uses LIDAR data. Previous works have utilized the CNN method to automatically segment buildings. However, the existing body of works have relied heavily on the conversion of LIDAR data into Digital Terrain Model (DTM), Digital Surface Model (DSM), or Digital Elevation Model (DEM) formats. Those formats required conversion of LIDAR data into raster images, which poses challenges to the evaluation of building volumes. In this paper, we collected LIDAR data with unmanned aerial vehicle and directly segmented buildings utilizing the said LIDAR data. We utilized a Dynamic Graph Convolutional Neural Network (DGCNN) algorithm to separate buildings and vegetation. We then utilized Euclidean Clustering to segment each building. We found that the combination of these methods are superior to prior works in the field, with accuracy up to 95.57% and an Intersection Over Union (IOU) score of 0.85.

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