scholarly journals UAV LiDAR Survey for Archaeological Documentation in Chiapas, Mexico

2021 ◽  
Vol 13 (23) ◽  
pp. 4731
Author(s):  
Whittaker Schroder ◽  
Timothy Murtha ◽  
Charles Golden ◽  
Andrew K. Scherer ◽  
Eben N. Broadbent ◽  
...  
Keyword(s):  
Land Use ◽  
High Precision ◽  
Landscape Change ◽  
Laser Scanning ◽  
Cultural Landscapes ◽  
Lidar Data ◽  
Airborne Laser ◽  
Extensive Documentation ◽  
Natural Landscapes

Airborne laser scanning has proven useful for rapid and extensive documentation of historic cultural landscapes after years of applications mapping natural landscapes and the built environment. The recent integration of unoccupied aerial vehicles (UAVs) with LiDAR systems is potentially transformative and offers complementary data for mapping targeted areas with high precision and systematic study of coupled natural and human systems. We report the results of data capture, analysis, and processing of UAV LiDAR data collected in the Maya Lowlands of Chiapas, Mexico in 2019 for a comparative landscape study. Six areas of archaeological settlement and long-term land-use reflecting a diversity of environments, land cover, and archaeological features were studied. These missions were characterized by areas that were variably forested, rugged, or flat, and included pre-Hispanic settlements and agrarian landscapes. Our study confirms that UAV LiDAR systems have great potential for broader application in high-precision archaeological mapping applications. We also conclude that these studies offer an important opportunity for multi-disciplinary collaboration. UAV LiDAR offers high-precision information that is not only useful for mapping archaeological features, but also provides critical information about long-term land use and landscape change in the context of archaeological resources.

scholarly journals A Model Study of Building Seismic Damage Information Extraction and Analysis on Ground-Based LiDAR Data

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Fan Yang ◽  
Xintao Wen ◽  
Xiaoshan Wang ◽  
Xiaoli Li ◽  
Zhiqiang Li
Keyword(s):  
High Precision ◽  
Laser Scanning ◽  
Full Range ◽  
Scientific Basis ◽  
Building Damage ◽  
Vector Model ◽  
Lidar Data ◽  
Emergency Relief ◽  
Cloud Data ◽  
Ground Based Lidar

Earthquake disasters can have a serious impact on people’s lives and property, with damage to buildings being one of the main causes of death and injury. A rapid assessment of the extent of building damage is essential for emergency response management, rescue operations, and reconstruction. Terrestrial laser scanning technology can obtain high precision light detection and ranging (LiDAR) point cloud data of the target. The technology is widely used in various fields; however, the quantitative analysis of building seismic information is the focus and difficulty of ground-based LiDAR data analysis processing. This paper takes full advantage of the high-precision characteristics of ground-based LiDAR data. A triangular network vector model (TIN-shaped model) was created in conjunction with the alpha shapes algorithm, solving the problem of small, nonvisually identifiable postearthquake building damage feature extraction bias. The model measures the length, width, and depth of building cracks, extracts the amount of wall tilt deformation, and labels the deformation zone. The creation of this model can provide scientific basis and technical support for postearthquake emergency relief, assessment of damage to buildings, extraction of deformation characteristics of other structures (bridges, tunnels, dams, etc.), and seismic reinforcement of buildings. The research data in this paper were collected by the author’s research team in the first time after the 2013 Lushan earthquake and is one of the few sets of foundation of LiDAR data covering the full range of postearthquake building types in the region, with the data information mainly including different damage levels of different structural types of buildings. The modeling analysis of this data provides a scientific basis for establishing the earthquake damage matrix of buildings in the region.

scholarly journals Segmentation of LiDAR Data Using Multilevel Cube Code

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
So-Young Park ◽  
Dae Geon Lee ◽  
Eun Jin Yoo ◽  
Dong-Cheon Lee
Keyword(s):  
Spatial Data ◽  
Laser Scanning ◽  
Point Clouds ◽  
Airborne Laser Scanning ◽  
Lidar Data ◽  
Chain Code ◽  
Cloud Data ◽  
Airborne Laser ◽  
Wide Range ◽  
Scanning Systems

Light detection and ranging (LiDAR) data collected from airborne laser scanning systems are one of the major sources of spatial data. Airborne laser scanning systems have the capacity for rapid and direct acquisition of accurate 3D coordinates. Use of LiDAR data is increasing in various applications, such as topographic mapping, building and city modeling, biomass measurement, and disaster management. Segmentation is a crucial process in the extraction of meaningful information for applications such as 3D object modeling and surface reconstruction. Most LiDAR processing schemes are based on digital image processing and computer vision algorithms. This paper introduces a shape descriptor method for segmenting LiDAR point clouds using a “multilevel cube code” that is an extension of the 2D chain code to 3D space. The cube operator segments point clouds into roof surface patches, including superstructures, removes unnecessary objects, detects the boundaries of buildings, and determines model key points for building modeling. Both real and simulated LiDAR data were used to verify the proposed approach. The experiments demonstrated the feasibility of the method for segmenting LiDAR data from buildings with a wide range of roof types. The method was found to segment point cloud data effectively.

scholarly journals Landscape change in the Icelandic highland: A long-term record of the impacts of land use, climate and volcanism

2020 ◽  
Vol 240 ◽  
pp. 106363 ◽  
Author(s):  
Sigrún Dögg Eddudóttir ◽  
Egill Erlendsson ◽  
Guðrún Gísladóttir
Keyword(s):  
Land Use ◽  
Landscape Change

scholarly journals People have shaped most of terrestrial nature for at least 12,000 years

2021 ◽  
Vol 118 (17) ◽  
pp. e2023483118 ◽  
Author(s):  
Erle C. Ellis ◽  
Nicolas Gauthier ◽  
Kees Klein Goldewijk ◽  
Rebecca Bliege Bird ◽  
Nicole Boivin ◽  
...  
Keyword(s):  
Land Use ◽  
Cultural Landscapes ◽  
Spatially Explicit ◽  
Human Populations ◽  
Vertebrate Species ◽  
Biodiversity Crisis ◽  
Indigenous Lands ◽  
Tropical Woodlands ◽  
Land Use Practices

Archaeological and paleoecological evidence shows that by 10,000 BCE, all human societies employed varying degrees of ecologically transformative land use practices, including burning, hunting, species propagation, domestication, cultivation, and others that have left long-term legacies across the terrestrial biosphere. Yet, a lingering paradigm among natural scientists, conservationists, and policymakers is that human transformation of terrestrial nature is mostly recent and inherently destructive. Here, we use the most up-to-date, spatially explicit global reconstruction of historical human populations and land use to show that this paradigm is likely wrong. Even 12,000 y ago, nearly three quarters of Earth’s land was inhabited and therefore shaped by human societies, including more than 95% of temperate and 90% of tropical woodlands. Lands now characterized as “natural,” “intact,” and “wild” generally exhibit long histories of use, as do protected areas and Indigenous lands, and current global patterns of vertebrate species richness and key biodiversity areas are more strongly associated with past patterns of land use than with present ones in regional landscapes now characterized as natural. The current biodiversity crisis can seldom be explained by the loss of uninhabited wildlands, resulting instead from the appropriation, colonization, and intensifying use of the biodiverse cultural landscapes long shaped and sustained by prior societies. Recognizing this deep cultural connection with biodiversity will therefore be essential to resolve the crisis.

scholarly journals Aerolaserskaneerimise kasutamine metsakorralduse alusena

2020 ◽  
Vol 73 (1) ◽  
pp. 136-144
Author(s):  
Tauri Arumäe ◽  
Mait Lang
Keyword(s):  
Forest Inventory ◽  
Laser Scanning ◽  
Canopy Cover ◽  
Height Growth ◽  
Small Scale ◽  
Lidar Data ◽  
Strong Correlations ◽  
The Past ◽  
Airborne Laser ◽  
Continuous Forest

Abstract In this summary, we give an overview of the application of airborne laser scanning (ALS) data for predicting the main forest inventory variables in Estonia. When Estonia being one of the few countries with wall-to-wall ALS availability, the need for applicable models for Estonian forests was imminent. Over the past decade, different studies have been carried out to develop models for standing wood volume, forest height, canopy cover, canopy base height, and methods for monitoring height growth and detect small-scale harvests. The main findings showed strong correlations for all the studied parameters and different methods utilizing low-density lidar data for practical forest inventory purposes. Options for using repea ted ALS measurements for continuous forest inventory are discussed.

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