Experimental Verification of the Possibility of Using Lidar Data from a Forested Area in Archeology (original) (raw)
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Lidar: practical applications in the woodland environment
"Whilst the majority of the day’s speakers are approaching this subject from an archaeological perspective it is worth reflecting that internationally archaeology constitutes a relatively minor end use of the technology. Lidar has a wide variety of applications ranging from flood risk mapping and coastal erosion analysis to canopy modelling and transportation planning. Lidar data can yield a large amount of valuable data for the woodland manager. The spatial and multi-dimensional nature of lidar is a key component of the value to land managers, but equally the manipulation and processing of that data can yield a wide range of information particularly in the GIS environment. There are three processed data sets that are of principal use to the woodland manager, Digital Surface Model (DSM), Digital Terrain Model (DTM) and the Canopy Height Model (CHM). DSMs are useful as mapping tools for identifying changes in crop data and complement existing aerial photographs. CHMs are essentially pure tree height data that can be symbolised on elevation without the confounding factor of underlying terrain. This allows for a clearer analysis of crop type differentiation, height structure and canopy porosity. It can also be used for determining canopy height and differences in growth rates. In relation to the management of the historic environment and the management of woodlands lidar can augment existing sources of information in operational planning and long term management planning. Operational planning is the management of forestry operations on the ground. Lidar is particularly useful here in identifying features of potential archaeological significance that are previously unknown, or of uncertain extent. This is a ‘feature-based’ approach that seeks to conserve individual features from potentially damaging operations. In management planning a deeper understanding of the distribution of features across the landscape will be required. This may be particularly applicable in extensive forest areas where there is a historical paucity of archaeological information. In such cases the emergence of patterns of historical development may provide cues for future management of the woodland resource. For the small woodland owner the expense of acquiring bespoke lidar data may be prohibitive and pre-flown data may be an attractive proposition. Data for much of England is widely available but it is important to be aware of the limitations of such data which may come in a variety of resolutions and formats. Lidar should be regarded as technology that facilitates woodland management rather than constrains it. With regard to historic environment surveys, being able to identify features of potential archaeological significance is the first step to avoiding its destruction through ignorance, neglect or oversight. In this respect, lidar surveys for archaeological purposes should be regarded as the beginning of a process of refinement and focus of resources possibly in liaison with County Archaeology Services and woodland management staff."
Archaeological applications using airborne laser scanning (ALS) are increasing in number. Since the production of ALS-derived digital terrain models (DTM) involves a considerable amount of money, most applications use general purpose ALS data, which are usually cheaper and sometimes even provided for free for scientific applications. The main problem that comes with this kind of data is the frequent lack of meta-information. The archaeologist often does not get the information about original point density, time of flight, instrument used, type of flying platform, filter and DTM generation procedure etc. Therefore, ALS becomes a kind of “black box”, where the derived DTM is used without further knowledge about underlying technology, algorithms, and metadata. Consequently, there is a certain risk that the data used will not be suitable for the archaeological application. Based on the experience of a two-year project “LiDAR-Supported Archaeological Prospection in Woodland”, the paper will give a review on archaeological ALS, explain its the basic process, demonstrate its potential for landscape archaeology especially in densely forested areas, and draw the attention to some critical parameters of ALS, which should be known to the user. Finally, further issues, which need to be solved in near future, are discussed.
, 2017. An integrated airborne laser scanning approach to forest management and cultural heritage issues: a case study at Porolissum, Romania. Ann. For. Res. 60(1): _-_. Abstract. This paper explores the opportunities that arise where forest ecosystem management and cultural heritage monuments protection converge. The case study area for our analysis was the landscape surrounding the Moigrad-Porolissum Archaeological site. We emphasize that an Airborne Laser Scanning (ALS or LiDAR-Light Detection and Ranging) approach to both forest management and cultural heritage conservation is an outstanding tool, assisting policy-makers and conservationists in decision making for integrated planning and management of the environment. LiDAR-derived surface models enabled a synoptic, never-seen-before view of the ancient Roman frontiers defensive systems while also revealing the present forest road network. The thorough and accurate road inventory data are very useful for updating and modifying forest base maps and registries and also for identifying the priority sectors for archaeological discharge. The ability to identify and determine optimal routes for forest management and to locate previously unmapped ancient archaeological remains aids in reducing costs and creating operational efficiencies as well as in complying with the legislation and avoiding infringements. The potential of LiDAR to demonstrate the long-term and comprehensive human impact on wooded areas is discussed. We identified a significant historical landscape change, consisting of a deforestation period, spanning over more than 160 years, during the Roman Period in Dacia (106-271 AD). The transdisciplinary analysis of the LiDAR data provides the base for combining knowledge from archaeology, forestry and environmental history in order to achieve a thorough analysis of the landscape changes and history. In the " nature versus culture " dichotomy, the landscape, outfield areas and forests are primarily perceived as nature, while in reality they are often heavily marked by human impact. LiDAR offers an efficient method for broadening our knowledge regarding the character and extent of human interaction with landscapes – forested or otherwise.
Canadian Journal of Remote Sensing, 2006
Tree height is an important variable in forest inventory programs but is typically time-consuming and costly to measure in the field using conventional techniques. Airborne light detection and ranging (lidar) provides individual tree height measurements that are highly correlated with field-derived measurements, but the imprecision of conventional field techniques does not allow for definitive assessments regarding the absolute accuracy of lidar tree height measurements and the relative influence of beam divergence setting (i.e., laser footprint size), species type, and digital terrain model (DTM) error on the accuracy of height measurements. In this study, we developed a methodology for acquiring accurate individual tree height measurements (<2 cm error) using a total station survey and used these measurements to establish the expected accuracy of lidar-and field-derived tree height measurements for two of the most ecologically and commercially significant species in western North America, Douglas-fir (Pseudotsuga menziesii) and ponderosa pine (Pinus ponderosa). Tree height measurements obtained from narrow-beam (0.33 m), high-density (6 points/m2) lidar were more accurate (mean error i: SD = -0.73 + 0.43 m) than those obtained from wide-beam (0.8 m) lidar (-1.12 0.56 m). Lidar-derived height measurements were more accurate for ponderosa pine (-0.43 i: 0.13 m) than for Douglas-fir (-1.05 i: 0.41 m) at the narrow beam setting. Although tree heights acquired using conventional field techniques (-0.27 2 0.27 m) were more accurate than those obtained using lidar (-0.73 i: 0.43 m for narrow beam setting), this difference will likely be offset by the wider coverage and cost efficiencies afforded by lidar-based forest survey.
Assessment of forest structure with airborne LiDAR and the effects of platform altitude
Remote Sensing of Environment, 2006
Airborne scanning LiDAR is a spatial technology increasingly used for forestry and environmental applications. However, the accuracy and coverage of LiDAR observations is highly dependent on both the extrinsic specifications of the LiDAR survey as well as the intrinsic effects such as the underlying forest structure. Extrinsic parameters which are set as part of the LiDAR survey include platform altitude, scan angle (half max. angle off nadir), and beam cross sectional diameter at the reflecting surface (referred to as footprint size). In this paper we investigate the effect of a number of these extrinsic parameters, including three different platform altitudes (1000, 2000, and 3000 m), two scan angles at 1000 m (10°and 15°h alf max. angle off nadir), and three footprint sizes (0.2, 0.4, and 0.6 m). The comparison was undertaken in eucalypt forests at three sites, varying in vegetation structure and topography within the Wedding Bells State Forest, Coffs Harbour, Australia. Results at the plot scale (40 × 90 m areas) indicate that tree heights computed from the 1000 m LiDAR data set (10°half max. angle off nadir) are well correlated with maximum plot heights (difference < 3 m) and field measured canopy volume (r 2 > 0.75, p < 0.001). Using normalised canopy height profiles (CHP) derived for sites, from data recorded at each altitude, we observed no significant difference between the relative distribution of LiDAR returns, indicating that platform altitude and footprint size have not had a major influence on CHP estimation. Interestingly, comparisons of first and last returns for individual pulses at increasing altitudes identified progressively fewer discrete first/last pulse combinations with more than 70% of pulses recorded as a single return at the highest altitude (3000 m). A possible hypothesis is that greater platform altitude and footprint size reduces the intensity of laser beam incident on a given surface area thus decreasing the probability of recording a last return above the noise threshold. Furthermore, tree scale analysis found a positive relationship between platform altitude and the underestimation of crown area and crown volume. The implications of this work for forest management are: (i) platform altitudes as high as 3000 m can be used to quantify the vertical distribution of phyto-elements, (ii) higher platform altitudes record a lower proportion of first/last return combinations that will further reduce the number of points available for forest structural assessment and development of digital elevation models, and (iii) for discrete LiDAR data, increasing platform altitude will record a lower frequency of returns per crown, resulting in larger underestimates of individual tree crown area and volume if standard algorithms are applied.
LiDAR and its role in understanding the historic landscape of Savernake Forest
Wiltshire Archaeological and Natural History Magazine, 2009
LiDAR (Light Detection and Ranging) is an aerial surveying technique that enables the creation of a digital surface model of the land. This is achieved through the saturation of the landscape by a high density of airborne ‘eye safe’ laser pulses. The time it takes for the reflected light from each pulse to return to the onboard computer is measured and the distance then calculated. This enables the creation of millions of three dimensional co-ordinates that can be joined to create a model of the surface below. Computer processing of the data can be applied to digitally remove any trees present to reveal the underlying terrain. In the woodland environment, LiDAR surveys are useful in disclosing landscape and earthwork features that are difficult to detect by using more traditional field or aerial survey techniques. A LiDAR survey of Savernake was carried out in 2006 on behalf of the Forestry Commission and has revealed a large number of previously unrecorded features of archaeological potential. These include a number of earthworks, field systems, other boundary banks, lynchets and route-ways. Comparison with known features suggests that a number are ancient in origin but other earthworks within Savernake were created over a long period of time, up to and including World War II. The landscape that is revealed by LiDAR casts new light on the historic uses of ancient woodland and forests suggesting extensive use and exploitation from prehistory until the present day. Despite the apparent success of the survey, it should be noted that LiDAR is indiscriminate and a number of features identified may be of modern origin, or given an appearance of solidity when in fact they are due to changes in vegetation. Any project involving LiDAR should be regarded as the beginning of a process of survey rather than an end result.
Assessing forest metrics with a ground-based scanning lidar
Canadian Journal of Forest Research-revue Canadienne De Recherche Forestiere, 2004
A ground-based scanning lidar (light detection and ranging) system was evaluated to assess its potential utility for tree-level forest mensuration data extraction. Ground-based-lidar and field-mensuration data were collected for two forest plots: one located within a red pine (Pinus resinosa Ait.) plantation and another in a mixed deciduous stand dominated by sugar maple (Acer saccharum Marsh.). Five lidar point cloud scans were collected from different vantage points for each plot over a 6-h period on 5 July 2002 using an Optech Inc. ILRIS-3D laser imager. Fieldvalidation data were collected manually over several days during the same time period. Parameters that were measured in the field or derived from manual field measures included (i) stem location, (ii) tree height, (iii) stem diameter at breast height (DBH), (iv) stem density, and (v) timber volume. These measures were then compared with those derived from the ILRIS-3D data (i.e., the lidar point cloud data). It was found that all parameters could be measured or derived from the data collected by the ground-based lidar system. There was a slight systematic underestimation of mean tree height resulting from canopy shadow effects and suboptimal scan sampling distribution. Timber volume estimates for both plots were within 7% of manually derived estimates. Tree height and DBH parameters have the potential for objective measurement or derivation with little manual intervention. However, locating and counting trees within the lidar point cloud, particularly in the multitiered deciduous plot, required the assistance of field-validation data and some subjective interpretation. Overall, ground-based lidar demonstrates promise for objective and consistent forest metric assessment, but work is needed to refine and develop automatic feature identification and data extraction techniques.
Article Airborne LiDAR for the Detection of Archaeological Vegetation Marks Using Biomass as a Proxy
2015
In arable landscapes, the airborne detection of archaeological features is often reliant on using the properties of the vegetation cover as a proxy for sub-surface features in the soil. Under the right conditions, the formation of vegetation marks allows archaeologists to identify and interpret archaeological features. Using airborne Laser Scanning, based on the principles of Light Detection and Ranging (LiDAR) to detect these marks is challenging, particularly given the difficulties of resolving subtle changes in a low and homogeneous crop with these sensors. In this paper, an experimental approach is adopted to explore how these marks could be detected as variations in canopy biomass using both range and full waveform LiDAR data. Although some detection was achieved using metrics of the full waveform data, it is the novel multi-temporal method of using discrete return data to detect and characterise archaeological vegetation marks that is offered for further consideration. This method was demonstrated to be applicable over a range of capture conditions, including soils deemed as difficult (i.e., clays and other heavy soils), and should increase the certainty of detection when employed in the increasingly multi-sensor approaches to heritage prospection and management.