scholarly journals The application of Airborne Laser Scaning for identifying old lignite workings – case study: the mine “Borussia” near Ośno Lubuskie (Western Poland)

2018 ◽  
Vol 36 ◽  
pp. 02002 ◽  
Author(s):  
Agnieszka Gontaszewska-Piekarz ◽  
Maria Mrówczyńska

The paper presents the possibilities of using data obtained by airborne laser scanning for identifying areas where lignite used to be mined. The technology of airborne laser scanning presented in the paper as and its results have a vast potential in terms of identifying local terrain deformations. The paper also presents the history of lignite mining in the region of Ośno Lubuskie (the north-west of Ziemia Lubuska - western Poland). It describes underground mining in complicated geological conditions (glaciotectonic deformations). The paper is supplemented with historical maps showing the locations of the mines

2020 ◽  
Vol 12 (9) ◽  
pp. 1411 ◽  
Author(s):  
Ole Risbøl ◽  
Daniel Langhammer ◽  
Esben Schlosser Mauritsen ◽  
Oula Seitsonen

This paper gives a presentation of how airborne laser scanning (ALS) has been adopted in archaeology in the North over the period 2005–2019. Almost two decades have passed since ALS first emerged as a potential tool to add to the archaeologist’s toolbox. Soon after, it attracted the attention of researchers within archaeological communities engaged with remote sensing in the Fenno-Scandinavian region. The first archaeological ALS projects gave immediate good results and led to further use, research, and development through new projects that followed various tracks. The bulk of the research and development focused on studying how well-suited ALS is for identifying, mapping, and documenting archaeological features in outfield land, mainly in forested areas. The poor situation in terms of lack of information on archaeological records in outfield areas has been challenging for research and especially for cultural heritage management for a long period of time. Consequently, an obvious direction was to study how ALS-based mapping of cultural features in forests could help to improve the survey situation. This led to various statistical analyses and studies covering research questions related to for instance effects on detection success of laser pulse density, and the size and shape of the targeted features. Substantial research has also been devoted to the development and assessment of semi-automatic detection of archaeological features based on the use of algorithms. This has been studied as an alternative approach to human desk-based visual analyses and interpretations of ALS data. This approach has considerable potential for detecting sites over large regions such as the vast roadless and unbuilt wilderness regions of northern Fennoscandia, and has proven highly successful. In addition, the current review presents how ALS has been employed for monitoring purposes and for landscape studies, including how it can influence landscape understanding. Finally, the most recent advance within ALS research and development has been discussed: testing of the use of drones for data acquisition. In conclusion, aspects related to the utilization of ALS in archaeological research and cultural heritage management are summarized and discussed, together with thoughts about future perspectives.


2014 ◽  
Vol 72 (1) ◽  
pp. 47-56 ◽  
Author(s):  
Andreas Barth ◽  
Johan J. Möller ◽  
Lars Wilhelmsson ◽  
John Arlinger ◽  
Rikard Hedberg ◽  
...  

Author(s):  
J.-M. Monnet ◽  
C. Ginzler ◽  
J.-C. Clivaz

Airborne laser scanning (ALS) remote sensing data are now available for entire countries such as Switzerland. Methods for the estimation of forest parameters from ALS have been intensively investigated in the past years. However, the implementation of a forest mapping workflow based on available data at a regional level still remains challenging. A case study was implemented in the Canton of Valais (Switzerland). The national ALS dataset and field data of the Swiss National Forest Inventory were used to calibrate estimation models for mean and maximum height, basal area, stem density, mean diameter and stem volume. When stratification was performed based on ALS acquisition settings and geographical criteria, satisfactory prediction models were obtained for volume (R<sup>2</sup> = 0.61 with a root mean square error of 47 %) and basal area (respectively 0.51 and 45 %) while height variables had an error lower than 19%. This case study shows that the use of nationwide ALS and field datasets for forest resources mapping is cost efficient, but additional investigations are required to handle the limitations of the input data and optimize the accuracy.


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