Detecting Cultural Remains in Boreal Forests in Sweden Using Airborne Laser Scanning Data of Different Resolutions

Norstedt, Gudrun; Axelsson, Anna‐Lena; Laudon, Hjalmar; Östlund, Lars

doi:10.1080/00934690.2019.1677424

Cited by 16 publications

(9 citation statements)

References 18 publications

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“…The study compared the national ALS data set with a density of 1.1-1.3 points/m 2 (the density in the specific area) with a data set with an average of 13 points/m 2 . The DTM grid used 0.4 m for the higher-resolution data and 0.7 for the lower-resolution data [68]. Unsurprisingly, the higher-resolution data exhibited greater detection success concerning certain types of sites, such as charcoal kilns and tar production sites, as proved by the earlier tests in Norway mentioned above.…”

Section: Identifying Mapping and Documenting Cultural Featuresmentioning

confidence: 90%

“…Unsurprisingly, the higher-resolution data exhibited greater detection success concerning certain types of sites, such as charcoal kilns and tar production sites, as proved by the earlier tests in Norway mentioned above. Some features, like subtle ruins from dwellings, were rather difficult to identify successfully even with the higher-resolution data, while in the lower-resolution data they were almost unrecognizable [68]. Studies of this kind are interesting, but it is important to recognize that the transfer value to other geographical areas is limited because the outcome is dependent on a series of parameters, such as period of flight, local topography and vegetation.…”

Section: Identifying Mapping and Documenting Cultural Featuresmentioning

confidence: 99%

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Employment, Utilization, and Development of Airborne Laser Scanning in Fenno-Scandinavian Archaeology—A Review

Risbøl

Langhammer

Mauritsen³

et al. 2020

Remote Sensing

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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.

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Section: Identifying Mapping and Documenting Cultural Featuresmentioning

confidence: 90%

Section: Identifying Mapping and Documenting Cultural Featuresmentioning

confidence: 99%

Employment, Utilization, and Development of Airborne Laser Scanning in Fenno-Scandinavian Archaeology—A Review

Risbøl

Langhammer

Mauritsen³

et al. 2020

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…A comparison of datasets at 0.7 and 2 pnts/m 2 with a UAV dataset at 22 ground pnts/m 2 showed little improvement in detection success [56]. Similarly, a comparison of a 0.5 pnt/m 2 dataset with a 13 pnts/m 2 dataset showed that the accuracy of archaeological interpretation was significantly better with the latter [57]. Some ongoing studies in Finland demonstrated stark improvement and numerous new features observed when comparing a 2 m DEM with 0.02 m and 0.1 m DEMs [58].…”

Section: Optimal Dfm Resolutionmentioning

confidence: 96%

Airborne LiDAR-Derived Digital Elevation Model for Archaeology

2021

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The use of topographic airborne LiDAR data has become an essential part of archaeological prospection, and the need for an archaeology-specific data processing workflow is well known. It is therefore surprising that little attention has been paid to the key element of processing: an archaeology-specific DEM. Accordingly, the aim of this paper is to describe an archaeology-specific DEM in detail, provide a tool for its automatic precision assessment, and determine the appropriate grid resolution. We define an archaeology-specific DEM as a subtype of DEM, which is interpolated from ground points, buildings, and four morphological types of archaeological features. We introduce a confidence map (QGIS plug-in) that assigns a confidence level to each grid cell. This is primarily used to attach a confidence level to each archaeological feature, which is useful for detecting data bias in archaeological interpretation. Confidence mapping is also an effective tool for identifying the optimal grid resolution for specific datasets. Beyond archaeological applications, the confidence map provides clear criteria for segmentation, which is one of the unsolved problems of DEM interpolation. All of these are important steps towards the general methodological maturity of airborne LiDAR in archaeology, which is our ultimate goal.

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“…The associated increased fuzziness of archaeological features, as well as the decreased detection rate as seen from the "copied interpretation" seem to align with the results of a study in the boreal forest. There, the authors argue that the mean ground point density of about 5 pts/m 2 is sufficient to identify vast majority of archaeological features [50]. While such point density comprises a threshold below which the detectability of archaeological features falls notably overall, a denser point cloud can help to investigate the details of the recorded features.…”

Section: The Visibility Of Archaeological Featuresmentioning

confidence: 99%

The Impact of Vegetation on the Visibility of Archaeological Features in Airborne Laser Scanning Datasets from Different Acquisition Dates

2022

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Digital elevation models derived from airborne laser scanning have found worldwide application in archaeology and other disciplines. A key feature that makes these models so valuable lies in their capacity to represent micro-relief features indicating traces of past human activity. While detection of these often faint traces in vegetated areas benefits from maximum leaf-off conditions during data acquisition, countrywide collection of data must make compromises and often cannot take place in the most appropriate seasons. In this paper, we identify the impact of leaf-on conditions on the distribution of ground returns and present what types of archaeological objects might remain unnoticeable if the flight date is outside the desirable time window. Comparing five ALS data acquisition campaigns from both leaf-off (April and November) and leaf-on conditions (May and June), we demonstrate how foliage affects the morphology of relief features as recorded in ALS derivatives, and we identify other effects on archaeological interpretation caused by changing vegetation conditions. The results encourage evaluation of countrywide general-purpose data for their applicability in archaeology.

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Detecting Cultural Remains in Boreal Forests in Sweden Using Airborne Laser Scanning Data of Different Resolutions

Cited by 16 publications

References 18 publications

Employment, Utilization, and Development of Airborne Laser Scanning in Fenno-Scandinavian Archaeology—A Review

Employment, Utilization, and Development of Airborne Laser Scanning in Fenno-Scandinavian Archaeology—A Review

Airborne LiDAR-Derived Digital Elevation Model for Archaeology

The Impact of Vegetation on the Visibility of Archaeological Features in Airborne Laser Scanning Datasets from Different Acquisition Dates

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