High concentration of charcoal hearth remains as legacy of historical ferrous metallurgy in southern Poland

Rutkiewicz, Paweł; Malik, Ireneusz; Wistuba, Małgorzata; Osika, Aleksandra

doi:10.1016/j.quaint.2019.04.015

Cited by 44 publications

(39 citation statements)

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“…The number of charcoal hearth remains identified during the previous study (Rutkiewicz et al 2019), indicates that charcoal burning had a very large impact in changing of the forest plant communities in the study areas over past centuries. In fact, the whole surface of the Mała Panew River basin is covered with numerous remains of charcoal hearths.…”

Section: Change In Forest Areas As a Results Of Charcoal Burning And Tmentioning

confidence: 88%

“…In previous research on the catchment area selected, the Mała Panew River, as many as 166,356 charcoal hearth remains were identified in an area of 902 km 2 . To date, this is the only confirmed case in Europe, and even in the world, of the occurrence of such a high concentration of remains of charcoal hearths over a relatively large area (Rutkiewicz et al 2019). Nevertheless, continuous research on charcoal hearth remains reveals their high density both on smaller and large surfaces, e.g.…”

Section: Analysis Of the Images From Lidar Datamentioning

confidence: 84%

“…2). There were from 4 to 9 hollows with a diameter of 2-3 m around the central elevation (Rutkiewicz et al 2019). In this study, the research area was reduced to just two sites located in the upper part of the Mała Panew River basin ( Fig.…”

Section: Analysis Of the Images From Lidar Datamentioning

confidence: 99%

“…Nelle 2003, Deforce et al 2013, Knapp et al 2015, Dupin et al 2017, Hazell et al 2017, Ludemann et al 2017, Py-Saragaglia et al 2017. Research on charcoal hearth remains and historical charcoal burning has also been carried out in Poland (Rutkiewicz et al 2019). However, a study permitting a broader recognition of the species used for charcoal burning and investigating the environmental effects of this type of activity has not yet been conducted.…”

Section: Introductionmentioning

confidence: 99%

“…However, a study permitting a broader recognition of the species used for charcoal burning and investigating the environmental effects of this type of activity has not yet been conducted. The valley of the Mała Panew River was selected for study because a large number of charcoal hearth remains were identified within it during pilot studies (Rutkiewicz et al 2019). The main aim of this study was the reconstruction of the environmental changes (identifiable at this stage of research) that resulted from large-scale charcoal production for the needs of historical water-powered metallurgy in selected sites in the Mała Panew basin.…”

Section: Introductionmentioning

confidence: 99%

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Environmental effects of historical charcoal burning associated with water-powered ferrous metallurgy (Mała Panew basin, southern Poland)

Rutkiewicz¹,

Malik²

2019

geol

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The main aim of this study was the reconstruction of the environmental changes (identifiable at this stage of research) resulting from large-scale charcoal production for the needs of historical water-powered metallurgy in selected sites in the Mała Panew basin. The identification of the remains of charcoal hearths was carried out by analysing shaded relief models. Shaded relief models were created from data from Airborne Laser Scanning (LIDAR). In order to verify the charcoal hearth remains identified in digital images, ground proofing was carried out. The charcoal hearth remains were subjected to sampling. Fragments of charcoal were extracted from the samples, which were then sent for analysis to identify tree species. In order to determine the age of chosen charcoal hearth remains, 10 charcoal pieces were submitted for radiocarbon dating. The following taxa were identified: Scots pine (Pinus sylvestris), alder (Alnus sp.), birch (Betula sp.), oak (Quercus sp.), Norway spruce / larch (Picea abies / Larix sp.), Silver fir (cf. Abies alba) and ash (Fraxinus excelsior). The taxa identified are dominated by Scots pine (56%). This research demonstrates that valuable wood of deciduous species might have been overexploited at the initial stage of metallurgical production and very quickly exhausted, being replaced by fast-growing coniferous species. The excessive exploitation of the forests might have had negative environmental effects such as the transformation/modification of the species composition of the forest cover, significant deforestation of exploited areas, intensification of floods or the initiation of aeolian transport of sands. All the charcoal hearth remains investigated date to the period from 1677 to 1957 AD.

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Section: Change In Forest Areas As a Results Of Charcoal Burning And Tmentioning

confidence: 88%

Section: Analysis Of the Images From Lidar Datamentioning

confidence: 84%

Section: Analysis Of the Images From Lidar Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Environmental effects of historical charcoal burning associated with water-powered ferrous metallurgy (Mała Panew basin, southern Poland)

Rutkiewicz¹,

Malik²

2019

geol

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A modified Mask region‐based convolutional neural network approach for the automated detection of archaeological sites on high‐resolution light detection and ranging‐derived digital elevation models in the North German Lowland

Bonhage

Eltaher

Raab

et al. 2021

Archaeological Prospection

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Due to complicated backgrounds and unclear target orientation, automated object detection is difficult in the field of archaeology. Most of the current convolutional neural network (CNN) object-oriented detection techniques are based on a faster region-based CNN (R-CNN) and other one-stage detectors that often lack adequate processing speeds and detection accuracies. Recently, the two-stage detector Mask R-CNN technique achieved impressive results in object detection and instance segmentation problems and was successfully applied in the analysis of archaeological airborne laser scanning (ALS) data. In this study, we outline a modified Mask R-CNN technique that reliably and efficiently detects relict charcoal hearth (RCH) sites on light detection and ranging (LiDAR) data-based digital elevation models (DEMs).Using image augmentation and image preprocessing steps combined with the deep learning-based adaptive gradient method with a dynamic bound on the learning rate (AdaBound) optimization technique, we could improve the model's accuracy and significantly reduce its training time. We use DEMs based on high-resolution LiDAR data and the visualization for archaeological topography (VAT) technique that give images with a very strong contrast of the terrain and the outline of the sites of interest in the North German Lowland. Therefore, the model can identify RCH sites with an average recall of 83% and an average precision of 87%. Techniques such as the modified Mask R-CNN method outlined here will help to greatly improve our knowledge about archaeological site densities in the realm of historical charcoal production and past human-landscape interactions. This method provides an accurate, time-efficient and bias-free large-scale site mapping option not only for the North German Lowland but potentially for other landscapes as well.

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Automated large‐scale mapping and analysis of relict charcoal hearths in Connecticut (USA) using a Deep Learning YOLOv4 framework

Vaart

Bonhage

Schneider

et al. 2022

Archaeological Prospection

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In the past decade, numerous studies have successfully mapped thousands of former charcoal production sites (also called relict charcoal hearths) manually using digital elevation model (DEM) data from various forested areas in Europe and the north‐eastern USA. The presence of these sites causes significant changes in the soil physical and chemical properties, referred to as legacy effects, due to high amounts of charcoal that remain in the soils. The overwhelming amount of charcoal hearths found in landscapes necessitates the use of automated methods to map and analyse these landforms. We present a novel approach based on open source data and software, to automatically detect relict charcoal hearths in large‐scale LiDAR datasets (visualized with Simple Local Relief Model). In addition, the approach simultaneously provides both general as well as domain‐specific information, which can be used to further study legacy effects. Different versions of the methodology were fine‐tuned on data from north‐western Connecticut and subsequently tested on two different areas in Connecticut. The results show that these perform adequate, with F1‐scores ranging between 0.21 and 0.76, although additional post‐processing was needed to deal with variations in LiDAR quality. After testing, the best performing version of the prediction model (with an average F1‐score of 0.56) was applied on the entire state of Connecticut. The results show a clear overlap with the known distribution of charcoal hearths in the state, while new concentrations were found as well. This shows the usability of the approach on large‐scale datasets, even when the terrain and LiDAR quality varies.

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High concentration of charcoal hearth remains as legacy of historical ferrous metallurgy in southern Poland

Cited by 44 publications

References 44 publications

Environmental effects of historical charcoal burning associated with water-powered ferrous metallurgy (Mała Panew basin, southern Poland)

Environmental effects of historical charcoal burning associated with water-powered ferrous metallurgy (Mała Panew basin, southern Poland)

A modified Mask region‐based convolutional neural network approach for the automated detection of archaeological sites on high‐resolution light detection and ranging‐derived digital elevation models in the North German Lowland

Automated large‐scale mapping and analysis of relict charcoal hearths in Connecticut (USA) using a Deep Learning YOLOv4 framework

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