Ancient lowland Maya complexity as revealed by airborne laser scanning of northern Guatemala

Science ◽  
2018 ◽  
Vol 361 (6409) ◽  
pp. eaau0137 ◽  
Author(s):  
Marcello A. Canuto ◽  
Francisco Estrada-Belli ◽  
Thomas G. Garrison ◽  
Stephen D. Houston ◽  
Mary Jane Acuña ◽  
...  

Lowland Maya civilization flourished in the tropical region of the Yucatan peninsula and environs for more than 2500 years (~1000 BCE to 1500 CE). Known for its sophistication in writing, art, architecture, astronomy, and mathematics, Maya civilization still poses questions about the nature of its cities and surrounding populations because of its location in an inaccessible forest. In 2016, an aerial lidar survey across 2144 square kilometers of northern Guatemala mapped natural terrain and archaeological features over several distinct areas. We present results from these data, revealing interconnected urban settlement and landscapes with extensive infrastructural development. Studied through a joint international effort of interdisciplinary teams sharing protocols, this lidar survey compels a reevaluation of Maya demography, agriculture, and political economy and suggests future avenues of field research.

2021 ◽  
Vol 6 (1-2) ◽  
pp. 159-176
Author(s):  
Filip Prekop ◽  
Petr Krištuf

This paper presents a new hillfort site which is situated on top of „Čerťák“ Hill (651 m n. m.), Sovolusky municipality, Karlovy Vary district. It has been identified with the help of a digital terrain model based on Airborne Laser Scanning (LiDAR). Two separate lines of stone ramparts have been confirmed on top of the Čerťák Hill, formed by a significant right bank meander in the upper course of the river Střela. The inner area reaches 1.4 ha and the external enclosed area spreads to 2.3 ha. Subsequent field research yielded a collection of more than 500 pottery fragments from the Late Hallstatt period. The dispersion of finds shows relatively intensive settlement. The paper also discusses other sites in the surrounding region which date to the same period. The Hallstatt settlement seems to have been a structurally connected complex in the presented area.


2011 ◽  
Vol 5 (3) ◽  
pp. 196-208 ◽  
Author(s):  
D. F. Laefer ◽  
T. Hinks ◽  
H. Carr ◽  
L. Truong-Hong

2021 ◽  
Vol 13 (4) ◽  
pp. 1917
Author(s):  
Alma Elizabeth Thuestad ◽  
Ole Risbøl ◽  
Jan Ingolf Kleppe ◽  
Stine Barlindhaug ◽  
Elin Rose Myrvoll

What can remote sensing contribute to archaeological surveying in subarctic and arctic landscapes? The pros and cons of remote sensing data vary as do areas of utilization and methodological approaches. We assessed the applicability of remote sensing for archaeological surveying of northern landscapes using airborne laser scanning (LiDAR) and satellite and aerial images to map archaeological features as a basis for (a) assessing the pros and cons of the different approaches and (b) assessing the potential detection rate of remote sensing. Interpretation of images and a LiDAR-based bare-earth digital terrain model (DTM) was based on visual analyses aided by processing and visualizing techniques. 368 features were identified in the aerial images, 437 in the satellite images and 1186 in the DTM. LiDAR yielded the better result, especially for hunting pits. Image data proved suitable for dwellings and settlement sites. Feature characteristics proved a key factor for detectability, both in LiDAR and image data. This study has shown that LiDAR and remote sensing image data are highly applicable for archaeological surveying in northern landscapes. It showed that a multi-sensor approach contributes to high detection rates. Our results have improved the inventory of archaeological sites in a non-destructive and minimally invasive manner.


2021 ◽  
Vol 491 ◽  
pp. 119225
Author(s):  
Einari Heinaro ◽  
Topi Tanhuanpää ◽  
Tuomas Yrttimaa ◽  
Markus Holopainen ◽  
Mikko Vastaranta

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1864
Author(s):  
Peter Mewis

The effect of vegetation in hydraulic computations can be significant. This effect is important for flood computations. Today, the necessary terrain information for flood computations is obtained by airborne laser scanning techniques. The quality and density of the airborne laser scanning information allows for more extensive use of these data in flow computations. In this paper, known methods are improved and combined into a new simple and objective procedure to estimate the hydraulic resistance of vegetation on the flow in the field. State-of-the-art airborne laser scanner information is explored to estimate the vegetation density. The laser scanning information provides the base for the calculation of the vegetation density parameter ωp using the Beer–Lambert law. In a second step, the vegetation density is employed in a flow model to appropriately account for vegetation resistance. The use of this vegetation parameter is superior to the common method of accounting for the vegetation resistance in the bed resistance parameter for bed roughness. The proposed procedure utilizes newly available information and is demonstrated in an example. The obtained values fit very well with the values obtained in the literature. Moreover, the obtained information is very detailed. In the results, the effect of vegetation is estimated objectively without the assignment of typical values. Moreover, a more structured flow field is computed with the flood around denser vegetation, such as groups of bushes. A further thorough study based on observed flow resistance is needed.


2020 ◽  
Vol 12 (1) ◽  
pp. 1185-1199
Author(s):  
Mirosław Kamiński

AbstractThe research area is located on the boundary between two Paleozoic structural units: the Radom–Kraśnik Block and the Mazovian–Lublin Basin in the southeastern Poland. The tectonic structures are separated by the Ursynów–Kazimierz Dolny fault zone. The digital terrain model obtained by the ALS (Airborne Laser Scanning) method was used. Classification and filtration of an elevation point cloud were performed. Then, from the elevation points representing only surfaces, a digital terrain model was generated. The model was used to visually interpret the course of topolineaments and their automatic extraction from DTM. Two topolineament systems, trending NE–SW and NW–SE, were interpreted. Using the kernel density algorithm, topolineament density models were generated. Using the Empirical Bayesian Kriging, a thickness model of quaternary deposits was generated. A relationship was observed between the course of topolineaments and the distribution and thickness of Quaternary formations. The topolineaments were compared with fault directions marked on tectonic maps of the Paleozoic and Mesozoic. Data validation showed consistency between topolineaments and tectonic faults. The obtained results are encouraging for further research.


Author(s):  
Jorgen Wallerman ◽  
Kenneth Nystrom ◽  
Mats Nilsson ◽  
Peder Axensten ◽  
Mikael Egberth ◽  
...  

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Johannes Schumacher ◽  
Marius Hauglin ◽  
Rasmus Astrup ◽  
Johannes Breidenbach

Abstract Background The age of forest stands is critical information for forest management and conservation, for example for growth modelling, timing of management activities and harvesting, or decisions about protection areas. However, area-wide information about forest stand age often does not exist. In this study, we developed regression models for large-scale area-wide prediction of age in Norwegian forests. For model development we used more than 4800 plots of the Norwegian National Forest Inventory (NFI) distributed over Norway between latitudes 58° and 65° N in an 18.2 Mha study area. Predictor variables were based on airborne laser scanning (ALS), Sentinel-2, and existing public map data. We performed model validation on an independent data set consisting of 63 spruce stands with known age. Results The best modelling strategy was to fit independent linear regression models to each observed site index (SI) level and using a SI prediction map in the application of the models. The most important predictor variable was an upper percentile of the ALS heights, and root mean squared errors (RMSEs) ranged between 3 and 31 years (6% to 26%) for SI-specific models, and 21 years (25%) on average. Mean deviance (MD) ranged between − 1 and 3 years. The models improved with increasing SI and the RMSEs were largest for low SI stands older than 100 years. Using a mapped SI, which is required for practical applications, RMSE and MD on plot level ranged from 19 to 56 years (29% to 53%), and 5 to 37 years (5% to 31%), respectively. For the validation stands, the RMSE and MD were 12 (22%) and 2 years (3%), respectively. Conclusions Tree height estimated from airborne laser scanning and predicted site index were the most important variables in the models describing age. Overall, we obtained good results, especially for stands with high SI. The models could be considered for practical applications, although we see considerable potential for improvements if better SI maps were available.


Sign in / Sign up

Export Citation Format

Share Document