LiDAR for topographic mapping

The evaluation of the natural resource plays a decisive role in management and sustainable developmental planning. The study aims
to generate natural resource based maps of rural areas of the USA using remote sensing datasets such as Landsat and LiDAR to analyze
generated natural resources for developing digital elevation (DEM) and canopy height models (CHMs). Natural resource maps were generated
using Landsat image of the year 2010. The area statistics reveal that the tree class percent (23.21 %) was the second highest after fallow land
class (60.44 %) whereas shrubs and grass/agriculture was 6.59 % and 6.47 %, respectively. Later, LiDAR datasets for the same time were
used to generate DEM/surface models (DSM) and CHMs. Spatial analysis was done to attempt hypothetical queries pertaining to resource
management. Further, all the generated datasets from different sources including slope map, drainage map etc can be integrated in GIS
domain for effective decision making. Coarse resolution Landsat data can be effectively used to monitor natural resources up to micro level if
used skillfully in conjugation with rectified images. LiDAR datasets have huge potential to generate highly accurate DEM, DSM and CHMs. Such
accurate data will be informative for qualitative and quantitative assessment of various natural resources.

Knowledge of underwater topography is essential to the understanding of the organisation and distribution of archaeological sites along and in water bodies. Special attention has to be paid to intertidal and inshore zones where, due to sea-level rise, coastlines have changed and many former coastal sites are now submerged in shallow water. Mapping the detailed inshore topography is therefore important to reconstruct former coastlines, identify sunken archaeological structures and locate potential former harbour sites. However, until recently archaeology has lacked suitable methods to provide the required topographical data of shallow underwater bodies. Our research shows that airborne topo-bathymetric laser scanner systems are able to measure surfaces above and below the water table over large areas in high detail using very short and narrow green laser pulses, even revealing sunken archaeological structures in shallow water. Using an airborne laser scanner operating at a wavelength in the green visible spectrum (532 nm) two case study areas in different environmental settings (Kolone, Croatia, with clear sea water; Lake Keutschach, Austria, with turbid water) were scanned. In both cases, a digital model of the underwater topography with a planimetric resolution of a few decimeters was measured. While in the clear waters of Kolone penetration depth was up to 11 meters, turbid Lake Keutschach allowed only to document the upper 1.6 meters of its underwater topography. Our results demonstrate the potential of this technique to map submerged archaeological structures over large areas in high detail providing the possibility for systematic, large scale archaeological investigation of this environment.

[ESP] A partir de un trabajo de investigación del Grupo de Estudos para a Prehistoria do Noroeste Ibérico-Arqueoloxía, Antigüidade e Territorio sobre la Edad del Hierro en el ayuntamiento de A Estrada (Pontevedra), se planteó la necesidad de generar un catálogo lo más completo posible de castros conocidos. Para ello, se realizó un vaciado de las fichas de la Dirección Xeral de Patrimonio Cultural y de la bibliografía disponible. El listado obtenido era amplio, pero escaso en cuanto a las referencias o datos sobre los yacimientos; en ocasiones, incluso carecían de coordenadas o estas no se correspondían con el yacimiento. Con esta situación, era necesario realizar una prospección en campo para afinar el catálogo todo lo posible. Para facilitar el trabajo en campo, se recurrió a la tecnología LiDAR, ya que creíamos que con ella, las estructuras defensivas de los castros se apreciarían. Además, para conseguir una mayor resolución, para ver los yacimientos con la mayor claridad posible, se emplearon mapas con 5 m de resolución y con 1 m de resolución. Mediante el uso de esta tecnología, pudimos detectar tres casuísticas. Existen castros que pueden ser localizados en el mapa con 5 m de resolución, mientras que otros necesitan del mapa de 1 m de resolución para que se vean sus elementos defensivos. Por último, hay una serie de yacimientos que no se aprecian en ninguno de los mapas. Esta situación puede deberse a la naturaleza de sus elementos defensivos, a un mal estado de conservación o a una catalogación errónea. [ENG] From a research work of the Grupo de Estudos para a Prehistoria do Noroeste Ibérico-Arqueoloxía, Antigüidade e Territorio on the Iron Age in the municipality of A Estrada (Pontevedra), rose the need to create a catalog as complete as possible of known castros. For this, we used the inventory of the Dirección Xeral de Patrimonio Cultural and the available bibliography. The list obtained was extensive, but limited regarding references or data fields; sometimes they even lacked coordinates or did not correspond to the site. In this situation, it was necessary to perform a field survey to refine the catalog. In order to simplify the fieldwork, we used LiDAR technology because it was believed that the defensive structures of the hillforts would be visible. Moreover, to achieve a higher resolution, in order to see the sites as clearly as possible, maps with 5 m resolution and 1 m resolution were used. With this technology, we could detect three casuistries. There are some forts that can be located on the map with 5 m resolution, while others need the map of 1 m resolution for their defensive elements to be detectable. Finally, there are a number of sites which were not seen in any of the maps. This may be due to the nature of their defensive elements, a poor conservation or incorrect documentation.

Over the last fifteen years, the use of LiDAR (Light Detection and Ranging) technology has greatly expanded the boundaries of archaeological prospection, especially in regions where specific ground conditions (particularly vegetation) make direct survey and field walking difficult or impossible. But what are the limits of this ‘new’ approach to archaeological survey? In this paper, our aim is not to assess the ability of high-resolution LIDAR altimetry to identify or locate new archaeological sites, as this ability has been sufficiently demonstrated, but to test the extent to which data resolution and algorithm accuracy allow for identifications and characterizations of specific features and architectural elements of matching or superior quality to that already achieved by other means, such as fieldwalking or air photography. To this end, we examine a case study set in the later prehistory of Iberia. Based on data made public by the Spanish government, we have produced LiDAR plans for a cluster of 36 Copper Age (c. 3200-2200 BCE) and Bronze Age (c. 2200-850 BCE) settlements located in western Sierra Morena (SW Spain) for which previous documentation existed in the form plans, photographs and written descriptions. Although limitations in raw data accuracy and changes in land-use made it impossible to obtain high-quality plans for about half of those sites, satisfactory results, improving previously existing records, were obtained for the other half. These are promising results, opening up an entirely new avenue for the detection, surveying, inventorying and analysis of settlements dating to similar periods located in European regions for which no previous records exist.

Settlement research in the Maya lowlands has struggled to reconcile its goals to model a tropical forest civilization in ecological terms with the logistical constraints imposed by the forest itself. In this paper, we argue that the methodological challenges facing settlement research in this tropical lowland setting limited researchers’ confidence in the representativeness of their data, nudging the discipline toward community-scale analysis and away from quantitative macro-scale settlement pattern research. As a result, many basic facts of human geography have remained unsettled. These challenges can now be overcome thanks to advances in remote sensing. Here, we use lidar derived settlement and topographic data from the Corona-Achiotal region of northwestern Guatemala to develop a settlement suitability model that reveals patterns in the distribution of archaeological remains vis-à-vis landforms. Applying this model to a much larger published settlement dataset, we demonstrate how it is not only widely applicable in the interior Maya Lowlands, but also capable of identifying historical contingencies in the distribution of settlement, namely the crowding of less-suitable areas of the landscape, linked to urban densification.

Tell Iẓṭabba is located close to the modern town of Beth Sheʾan (Israel), and was where the Seleucid foundation of the later Decapolis city of Nysa-Scythopolis was established in the early 2nd century BCE. As a result, the site is of major importance for studying Hellenization processes in the Levant. This paper presents the results of magnetic prospections carried out on Tell Iẓṭabba (East) in February 2019, as part of a broader German-Israeli research collaboration aimed at high-resolution archaeological investigations of the site and its settlement history. After discussing the methods used, some preliminary conclusions are drawn about the extent of surface cover, with speculation on the nature of the remains, as suggested by the survey data. The authors conclude that while earlier, limited excavations have suggested that the urban design was that of a town laid out according to an orthogonal plan, these current results suggests that the town plan was in fact oriented according to the natural topography and only partially followed an orthogonal system.

Die spätantike Langmauer umschloss auf ca. 73 km Gesamtlänge ein etwa 232 km² großes Areal nördlich von Trier. Die Studie verdeutlicht das Potenzial der kombinierten Auswertung von historischen Karten und LiDAR-Daten für die weitere Erforschung dieses Bodendenkmals.

This paper presents the possibilities for using an unmanned aerial system for evaluation of the condition of levees. The unmanned aerial system is equipped with two types of sensor. One is an ultra-light laser scanner, integrated with a GNSS receiver and an INS system; the other sensor is a digital camera that acquires data with stereoscopic coverage. Sensors have been mounted on the multirotor, unmanned platform the Hawk Moth, constructed by MSP company. LiDAR data and images of levees the length of several hundred metres were acquired during testing of the platform. Flights were performed in several variants. Control points measured with the use of the GNSS technique were considered as reference data. The obtained results are presented in this paper; the methodology of processing the acquired LiDAR data, which increase in accuracy when low accuracy of the navigation systems occurs as a result of systematic errors, is also discussed. The Iterative Closest Point (ICP) algorithm, as well as measurements of control points, were used to georeference the LiDAR data. Final accuracy in the order of centimetres was obtained for generation of the digital terrain model. The final products of the proposed UAV data processing are digital elevation models, an orthophotomap and colour point clouds. The authors conclude that such a platform offers wide possibilities for low-budget flights to deliver the data, which may compete with typical direct surveying measurements performed during monitoring of such objects. However, the biggest advantage is the density and continuity of data, which allows for detection of changes in objects being monitored.

The use of topographic airborne LiDAR data has become an essential part of archaeological prospection. However, as a step towards theoretically aware, impactful, and reproducible research, a more rigorous and transparent method of data processing is required. To this end, we set out to create a processing pipeline for archaeology-specific point cloud processing and derivation of products that are optimized for general-purpose data. The proposed pipeline improves on ground and building point cloud classification. The main area of innovation in the proposed pipeline is raster grid interpolation. We have improved the state-of-the-art by introducing a hybrid interpolation technique that combines inverse distance weighting with a triangulated irregular network with linear interpolation. State-of-the-art solutions for enhanced visualizations are included and essential metadata and paradata are also generated. In addition, we have introduced a QGIS plug-in that implements the pipeline as a one-step process. It reduces the manual workload by 75 to 90 percent and requires no special skills other than a general familiarity with the QGIS environment. It is intended that the pipeline and tool will contribute to the white-boxing of archaeology-specific airborne LiDAR data processing. In discussion, the role of data processing in the knowledge production process is explored.

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.

The Airborne Laser Scanning (ALS) technology has been implemented in operational forest inventories in a number of countries. At the same time, as a cost-effective alternative to ALS, Digital Aerial Photogrammetry (PHM), based on aerial images, has been widely used for the past 10 years. Recently, PHM based on Unmanned Aerial Vehicle (UAV) has attracted great attention as well. Compared to ALS, PHM is unable to penetrate the forest canopy and, ultimately, to derive an accurate Digital Terrain Model (DTM), which is necessary to normalize point clouds or Digital Surface Models (DSMs). Many countries worldwide, including Croatia, still rely on PHM, as they do not have complete DTM coverage by ALS (DTMALS). The aim of this study is to investigate if the official Croatian DTM generated from PHM (DTMPHM) can be used for data normalization of UAV-based Digital Surface Model (DSMUAV) and estimating plot-level mean tree height (HL) in lowland pedunculate oak forests. For that purpose, HL estimated from DSMUAV normalized with DTMPHM and with DTMALS were generated and compared as well as validated against field measurements. Additionally, elevation errors in DTMPHM were detected and eliminated, and the improvement by using corrected DTMPHM (DTMPHMc) was evaluated. Small, almost negligible variations in the results of the leave-oneout cross-validation were observed between HL estimated using proposed methods. Compared to field data, the relative root mean square error (RMSE%) values of HL estimated from DSMUAV normalized with DTMALS, DTMPHM, and DTMPHMc were 5.10%, 5.14%, and 5.16%, respectively. The results revealed that in the absence of DTMALS, the existing official Croatian DTM could be readily used in remote sensing based forest inventory of lowland forest areas. It can be noted that DTMPHMc did not improve the accuracy of HL estimates because the gross errors mainly occurred outside of the study plots. However, since the existence of the gross errors in Croatian DTMPHM has been confirmed by several studies, it is recommended to detect and eliminate them prior to using the DTMPHM in forest inventory.

This paper presents the geomorphological evolution of larger slide generated by the 1960 earthquake, which dammed the San Pedro River, which was known locally as "Taco" 3. First, a geological and geomorphological characterization of the slide was made for years 1960 and 2010. After a comparative analysis between two topographic profiles obtained of Davis and Karzúlovic (1961), and two profiles derived from altimetry detail information from a survey conducted with LIDAR technology by 2010. It is further proposed by applying a diffusion equation, a representative rate of erosion for the Upper San Pedro River over the last 50 years. The results of this work together with the analysis of other historical evidence of landslides triggered by earthquakes, such as occurred in 1575, represent a valuable information for future of a paleosismolgical research of the Upper San Pedro River.

Settlement research in the Maya lowlands has struggled to reconcile its goals to model a tropical forest civilization in ecological terms with the logistical constraints imposed by the forest itself. In this paper, we argue that the methodological challenges facing settlement research in this tropical lowland setting limited researchers’ confidence in the representativeness of their data, nudging the discipline toward community-scale analysis and away from quantitative macro-scale settlement pattern research. As a result, many basic facts of human geography have remained unsettled. These challenges can now be overcome thanks to advances in remote sensing. Here, we use lidar-derived settlement and topographic data from the Corona-Achiotal region of northwestern Guatemala to develop a settlement suitability model that reveals patterns in the distribution of archaeological remains vis-a-vis landforms. Applying this model to a much larger published settlement dataset, we demonstrate how...