Flights into the past: full-waveform airborne laser scanning data for archaeological investigation

Lasaponara, Rosa; Coluzzi, Rosa; Masini, Nicola

doi:10.1016/j.jas.2010.10.003

Cited by 53 publications

(32 citation statements)

References 10 publications

(19 reference statements)

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“…The raw data points were imported into the Terrascan software environment, subdivided into 25 ha tiles and passed through a data processing chain developed specifically for archaeological applications of lidar in forest environments (12). The workflow was designed to minimize the errors caused by close canopy and dense understory and maximize the definition of microtopographic relief.…”

Section: Methodsmentioning

confidence: 99%

“…Lidar provides an unparalleled ability to penetrate dense vegetation cover and map archaeological remains on the forest floor. It can uncover and map microtopographic relief that otherwise cannot be discerned without very costly and labor-intensive programs of ground survey (12). Lidar technology has recently matured to the point where it has become cost effective for archaeologists to undertake bespoke data acquisitions at landscape scale, even while capturing topographic variation with sufficient accuracy and precision to identify archaeological features of only a few centimeters in size (13,14).…”

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confidence: 99%

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Uncovering archaeological landscapes at Angkor using lidar

Evans

Fletcher

Pottier

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

279

209

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Previous archaeological mapping work on the successive medieval capitals of the Khmer Empire located at Angkor, in northwest Cambodia (∼9th to 15th centuries in the Common Era, C.E.), has identified it as the largest settlement complex of the preindustrial world, and yet crucial areas have remained unmapped, in particular the ceremonial centers and their surroundings, where dense forest obscures the traces of the civilization that typically remain in evidence in surface topography. Here we describe the use of airborne laser scanning (lidar) technology to create high-precision digital elevation models of the ground surface beneath the vegetation cover. We identify an entire, previously undocumented, formally planned urban landscape into which the major temples such as Angkor Wat were integrated. Beyond these newly identified urban landscapes, the lidar data reveal anthropogenic changes to the landscape on a vast scale and lend further weight to an emerging consensus that infrastructural complexity, unsustainable modes of subsistence, and climate variation were crucial factors in the decline of the classical Khmer civilization.Southeast Asia | urbanism | sustainability | resilience | water management

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Uncovering archaeological landscapes at Angkor using lidar

Evans

Fletcher

Pottier

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

279

209

View full text Add to dashboard Cite

show abstract

“…We must improve the density of the LiDAR point cloud and obtain more knowledge of archaeological remains in the study area to extract and identify more remains using the algorithm. Although full-wave LiDAR can be used to extract more points under vegetation [5,6], the point density should be determined based on the specific archaeological remains. The associated technology is not the key problem; a lack of historical information and records hinders such studies.…”

Section: Discussionmentioning

confidence: 99%

“…During the past 50 years, aerial photos and satellite images have been the most common remote sensing data sources used in the field of archaeological identification, investigation, and surveying [1][2][3]. Visible spectral, infrared, and multispectral remote sensing are the most common remote sensing approaches, and have been used extensively to identify targets linked to the presence of archaeological earthworks and remains [3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

A Microtopographic Feature Analysis-Based LiDAR Data Processing Approach for the Identification of Chu Tombs

Wang

et al. 2017

Remote Sensing

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Most of the cultural sites hidden under dense vegetation in the mountains of China have been destroyed. In this paper, we present a microtopographic feature analysis (MFA)-based Light Detection and Ranging (LiDAR) data processing approach and an archaeological pattern-oriented point cloud segmentation (APoPCS) algorithm that we developed for the classification of archaeological objects and terrain points and the detection of archaeological remains. The archaeological features and patterns are interpreted and extracted from LiDAR point cloud data to construct an archaeological object pattern database. A microtopographic factor is calculated based on the archaeological object patterns, and this factor converts the massive point cloud data into a raster feature image. A fuzzy clustering algorithm based on the archaeological object patterns is presented for raster feature image segmentation and the detection of archaeological remains. Using the proposed approach, we investigated four typical areas with different types of Chu tombs in Central China, which had dense vegetation and high population densities. Our research results show that the proposed LiDAR data processing approach can identify archaeological remains from large-volume and massive LiDAR data, as well as in areas with dense vegetation and trees. The studies of different archaeological object patterns are important for improving the robustness of the proposed APoPCS algorithm for the extraction of archaeological remains.

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“…Finally, the authors suggested that despite the great potential of LiDAR in archaeology, the use of ALS data encounters serious challenges and still requires specific research, addressed to both (i) pre-processing (filtering and classification) to obtain detailed DTM and also to (ii) the post-processing to extract information (pattern extraction, classification). This challenge has been partially addressed by Coluzzi et al (2010) who defined the data processing chain along with the threshold-based algorithm for the classification of ground and non-ground points and for the detection of archaeological remains. The classification of laser data was performed using a strategy based on a set of "filtrations of the filtrate" (for more detail see section 4).…”

Section: Italymentioning

confidence: 99%