scholarly journals Geometrically accurate time series of archived aerial images and airborne lidar data in a forest environment

Silva Fennica ◽  
2006 ◽  
Vol 40 (1) ◽  
Author(s):  
Ilkka Korpela
Keyword(s):  
Time Series ◽  
Airborne Lidar ◽  
Aerial Images ◽  
Lidar Data ◽  
Forest Environment ◽  
Airborne Lidar Data

scholarly journals Comparing the Performance of Ground Filtering Algorithms for Terrain Modeling in a Forest Environment Using Airborne LiDAR Data

2018 ◽  
Vol 25 (2) ◽  
Author(s):  
Carlos Alberto Silva ◽  
Carine Klauberg ◽  
Ângela Maria Klein Hentz ◽  
Ana Paula Dalla Corte ◽  
Uelison Ribeiro ◽  
...  
Keyword(s):  
Airborne Lidar ◽  
Lidar Data ◽  
Terrain Modeling ◽  
Forest Environment ◽  
Filtering Algorithms ◽  
Airborne Lidar Data

scholarly journals Between Land and Sea: An Airborne LiDAR Field Survey to Detect Ancient Sites in the Chekka Region/Lebanon Using Spatial Analyses

2020 ◽  
Vol 6 (1) ◽  
pp. 248-268
Author(s):  
Jakob Rom ◽  
Florian Haas ◽  
Manuel Stark ◽  
Fabian Dremel ◽  
Michael Becht ◽  
...  
Keyword(s):  
Mediterranean Coast ◽  
Airborne Lidar ◽  
Aerial Images ◽  
Lidar Data ◽  
Least Cost Path ◽  
Path Analyses ◽  
Preliminary Validation ◽  
Path System ◽  
Elevation Model ◽  
Airborne Lidar Data

AbstractThe interdisciplinary project “Between Land and Sea” combines geological, geomorphological and paleo-environmental approaches to identify archaeological remains of the Chekka region (Lebanon). In order to record the topography of this area, the first ever scientific airborne LiDAR data acquisition in Lebanon was conducted in autumn 2018. This work describes not only the acquisition and processing of the LiDAR data, but also the attempt to derive possible archaeological sites from the generated elevation model based on methods for spatial analysis. Using an “inverted mound” (iMound) algorithm, areas of possible settlement structures could be identified, which were classified regarding their probability of a possible ancient site using a deductive predictive model. A preliminary validation of some of the detected favoured areas using high-resolution aerial images has shown that the methods applied can provide hints to previously undiscovered sites. It was possible to identify probable ancient wall remains at several detected locations. In addition, least-cost path analyses were performed to reconstruct possible trade and transport routes from the Lebanon Mountains to the Mediterranean coast. The combination of the results of the iMound detection and classification as well as the calculated path system could point to the strategic location of the modern village of Kfar Hazir as a kind of traffic junction. Moreover, reconstructed main transport routes provide indications of heavily frequented roads and may form the basis for further investigations. To validate the results, upcoming field surveys will be realized on site.

scholarly journals REVISED PROGRESSIVE MORPHOLOGICAL METHOD FOR GROUND POINT CLASSIFICATION OF AIRBORNE LIDAR DATA

2019 ◽  
Vol 6 (1-2) ◽  
pp. 31-38 ◽  
Author(s):  
Mohd Radhie Mohd Salleh ◽  
Muhammad Zulkarnain Abd Rahman ◽  
Zamri Ismail ◽  
Mohd Faisal Abdul Khanan ◽  
Mohd Asraff Asmadi
Keyword(s):  
Survey Data ◽  
Digital Terrain Model ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Major Step ◽  
Forest Environment ◽  
Local Slope ◽  
Filtering Method ◽  
Ground Survey ◽  
Airborne Lidar Data

Airborne Light Detection and Ranging (LiDAR) has been very effectively used in collecting terrain information over different scales of area. Inevitably, filtering the non-ground returns is the major step of digital terrain model (DTM) generation and this step poses the greatest challenge especially for tropical forest environment which consists of steep undulating terrain and mostly covered by a relatively thick canopy density. The aim of this research is to assess the performance of the Progressive Morphological (PM) algorithm after the implementation of local slope value in the ground filtering process. The improvement on the PM filtering method was done by employing local slope values obtained either using initial filtering of airborne LiDAR data or ground survey data. The filtering process has been performed with recursive mode and it stops after the results of the filtering does not show any improvement and the DTM error larger than the previous iteration. The revised PM filtering method has decreasing pattern of DTM error with increasing filtering iterations with minimum ±0.520 m of RMSE value. The results also suggest that spatially distributed slope value applied in PM filtering algorithm either from LiDAR ground points or ground survey data is capable in preserving discontinuities of terrain and correctly remove non-terrain points especially in steep area.

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