Trying to break new ground in aerial archaeology

Aerial reconnaissance continues to be a vital tool for landscape-oriented archaeological research. Although a variety of remote sensing platforms operate within the earth’s atmosphere, the majority of aerial archaeological information is still derived from oblique photographs collected during observer-directed reconnaissance flights, a prospection approach which has dominated archaeological aerial survey for the past century. The resulting highly biased imagery is generally catalogued in sub-optimal (spatial) databases, if at all, after which a small selection of images is orthorectified and interpreted. For decades, this has been the standard approach. Although many innovations, including digital cameras, inertial units, photogrammetry and computer vision algorithms, geographic(al) information systems and computing power have emerged, their potential has not yet been fully exploited in order to re-invent and highly optimise this crucial branch of landscape archaeology. The authors argue that a fundamental change is needed to transform the way aerial archaeologists approach data acquisition and image processing. By addressing the very core concepts of geographically biased aerial archaeological photographs and proposing new imaging technologies, data handling methods and processing procedures, this paper gives a personal opinion on how the methodological components of aerial archaeology, and specifically aerial archaeological photography, should evolve during the next decade if developing a more reliable record of our past is to be our central aim. In this paper, a possible practical solution is illustrated by outlining a turnkey aerial prospection system for total coverage survey together with a semi-automated back-end pipeline that takes care of photograph correction and image enhancement as well as the management and interpretative mapping of the resulting data products. In this way, the proposed system addresses one of many bias issues in archaeological research: the bias we impart to the visual record as a result of selective coverage. While the total coverage approach outlined here may not altogether eliminate survey bias, it can vastly increase the amount of useful information captured during a single reconnaissance flight while mitigating the discriminating effects of observer-based, on-the-fly target selection. Furthermore, the information contained in this paper should make it clear that with current technology it is feasible to do so. This can radically alter the basis for aerial prospection and move landscape archaeology forward, beyond the inherently biased patterns that are currently created by airborne archaeological prospection

“BIG DATA” EN PROSPECCIÓN ARQUEOLÓGICA DEL PAISAJE

[EN] While traditionally archaeological research has mainly been focused on individual cultural heritage monuments or distinct archaeological sites, the Austrian based Ludwig Boltzmann Institute for Archaeological Prospection and Virtual Archaeology goes beyond the limitations of discrete sites in order to understand their archaeological context. This is achieved by investigating the space in-between the sites, studying entire archaeological landscapes from the level of individual postholes to the mapping of numerous square kilometres. This large-scale, high-resolution, multi-method prospection approach leads to enormous digital datasets counting many terabytes of data that until recently were technically not manageable. Novel programs and methods of data management had to be developed for data acquisition, processing and archaeological interpretation, in order to permit the extraction of the desired information from the very big amount of data. The analysis of the generated datasets is conducted with the help of semi-automatic algorithms within complex three-, or even four-dimensional geographical information systems. The outcome of landscape archaeological prospection surveys is visually communicated to the scientific community as well as to the general public and stakeholders. In many cases, a visualization of the scientific result and archaeological interpretations can be a powerful and suitable tool to illustrate and communicate even complex contexts to a wide audience. This paper briefly presents the great potential offered by a combination of large-scale non-invasive archaeological prospection methods and standardized workflows for the integration of big data, its interpretation and visualization. The proposed approach provides a context for buried archaeology across entire archaeological landscapes, changing our understanding of known monuments. We address the overcome and remaining challenges with the help of examples taken from outstanding landscape archaeological prospection case studies.[ES] Aunque tradicionalmente la investigación arqueológica ha estado fundamentalmente centrada en monumentos y yacimientos arqueológicos de forma individual, el Ludwig Boltzmann Institute for Archaeological Prospection and Virtual Archaeology (Austria) va más allá de los límites de yacimientos particulares con el objetivo de entender su contexto arqueológico. Esto es conseguido mediante la investigación del espacio entre yacimientos y estudiando paisajes arqueológicos completos yendo desde un hoyo de poste hasta el mapeado de varios kilómetros cuadrados. El enfoque de prospección multi-metodológico a gran escala y de alta resolución conduce hacia un enorme conjunto de datos digital que incluye varios Terabytes de información los cuales no habían podido ser manipulados hasta hace poco debido a limitaciones tecnológicas. Por consiguiente, nuevos programas y métodos de gestión de datos han sido diseñados para la adquisición y procesado de datos así como interpretación arqueológica para así permitir la extracción de la información deseada desde estos enormes bancos de datos. El análisis de estos conjuntos de datos generados es llevado a cabo a través de análisis de sistemas de información geográfica tridimensionales e incluso cuatridimensionales. El resultado de la prospección de paisajes arqueológicos es transferido de forma visual a la comunididad científica así como al gran público e interesados en la materia. En muchos casos una visualización de los resultados científicos e interpretaciones arqueológicas puede ser una herramienta más poderosa y adecuada para ilustrar y comunicar contextos arqueológicos complejos a un público mayor. Este artículo presenta de forma breve el gran potencial ofrecido por la combinación de métodos de prospección arqueológica de gran resolución a gran escala y unos flujos de trabajo estandarizados para integración, interpretación y visualización de datos. La estrategía propuesta proporciona un contexto para restos arqueológicos enmarcados en paisajes arqueológicos que viene a cambiar nuestra forma de entender monumentos ya conocidos. Pretendemos también superar los desafios que quedan con la ayuda de ejemplos sacados de excepcionales paisajes arqueológicos que son nuestros estudios de caso a prospectar.Torrejón Valdelomar, J.; Wallner, M.; Trinks, I.; Kucera, M.; Luznik, N.; Löcker, K.; Neubauer, W. (2016). BIG DATA IN LANDSCAPE ARCHAEOLOGICAL PROSPECTION. En 8th International congress on archaeology, computer graphics, cultural heritage and innovation. Editorial Universitat Politècnica de València. 238-246. https://doi.org/10.4995/arqueologica8.2015.4200OCS23824

Applications of remote sensing to estuarine management : Final report and annual report number 7

Remote sensing techniques have been applied to problems in estuarine management in the seventh and final year of a NASA grant. A chromaticity technique for multi-date Landsat measurement of suspended sediment has been verified and made operational, and applied to sedimentation analysis of the ·Bay of Fundy Tidal Power Project. Dye-buoy photogrannnetry has been used to measure currents at depth and analyze suspended sediment plumes from hydraulic · dredging. Wetland permit sites and beach erosion site\u27s have been evaluated with aerial photography. Submerged aquatic vegetation has been mapped with tide- and wind-synchronized color photography. Virginia state resource monitoring needs have led to implementation of Landsat data p.rocessing capability for joint work with NASA Goddard on demonstration projects. This final report contains summaries and tables of the projects and activities of the Remote Sensing Center over the past seven years

Use of remote sensing for land use policy formulation

Progress in studies for using remotely sensed data for assessing crop stress and in crop estimation is reported. The estimation of acreage of small forested areas in the southern lower peninsula of Michigan using LANDSAT data is evaluated. Damage to small grains caused by the cereal leaf beetle was assessed through remote sensing. The remote detection of X-disease of peach and cherry trees and of fire blight of pear and apple trees was investigated. The reliability of improving on standard methods of crop production estimation was demonstrated. Areas of virus infestation in vineyards and blueberry fields in western and southwestern Michigan were identified. The installation and systems integration of a microcomputer system for processing and making available remotely sensed data are described

Literature review of the remote sensing of natural resources

Abstracts of 596 documents related to remote sensors or the remote sensing of natural resources by satellite, aircraft, or ground-based stations are presented. Topics covered include general theory, geology and hydrology, agriculture and forestry, marine sciences, urban land use, and instrumentation. Recent documents not yet cited in any of the seven information sources used for the compilation are summarized. An author/key word index is provided

Digital fault mapping and spatial attribute analysis of basement-influenced oblique extension in Passive margin settings

Oblique extension and passive margin segmentation may be attributed to the influence of basement structures. Pre-existing fabrics exert a strong control on the overall rift geometry in extensional settings, and can lead to the development of complex fault patterns, obliquely extending segments, deformation partitioning and transfer zones. In offshore settings, the nature of basement structure cannot easily be determined from seismic data, and onshore studies are increasingly used to assess basement controls. A digital mapping methodology GAVA (Geospatial Acquisition Visualisation and Analysis) has been developed to integrate regional- to outcrop-scale data. Digital field mapping methods using DGPS, Laser-Rangefinder and field-GIS are used to map faults to a dm- to mscale accuracy by collecting spatial co-ordinates on a handheld computer whilst traversing along or across the exposed fault systems. Benefits of digital mapping include: more rapid data collection and analysis; all data geospatially located and stored in a digital database; GIS-based analysis and visualisation techniques; digital data format enables direct comparison with fault arrays interpreted from seismic data. The GAVA workflow has been used to investigate three case studies on the North Atlantic Passive Margin: 1) NW Scotland; 2) Lofoten, NW Norway; and 3) Davis Strait, West Greenland. Each case study combines regional onshore and offshore mapping, using remote sensing and seismic interpretation, with detailed outcrop mapping of onshore fault exposures. Fault attributes (e.g. fault orientation, kinematics, fault linkage, fault-rock, overprinting relationships) observed at individual localities were collected in a GIS database. Kinematic fault analysis was carried out using strain inversion techniques at various scales. Spatial analysis was carried out using ArcGIS to identify relationships between various structures, while 3-D models were constructed in order to visualise these relationships over several orders of magnitude. Results show that the complexity of rifted margins may be linked to changes in the obliquity of pre-existing structures relative to the regional extension vector. However, direct reactivation of structures need not always occur. The influence of pre-existing structures may also lead to localized variations in stress/strain orientations, which if analyzed in isolation can indicate extension non-parallel to regional stresses. Therefore, spatial analysis and studies across a range of scales is essential when analyzing such zones. Digital (GIS) mapping methods are an ideal may to carry out such studies, although further development of analysis and visualisation tools for geosciences is required in the field of GIS

Coastal Biophysical Inventory Database for the Point Reyes National Seashore

The Coastal Biophysical Inventory Database is the repository of the data gathered from a rapid assessment of approximately 161 km of the intertidal habitat managed by the Point Reyes National Seashore and Golden Gate National Recreation Area. The Coastal Biophysical Inventory Database is modeled after the “Alaska Coastal Resources Inventory and Mapping Database” and CoastWalker program of Glacier Bay National Park and Preserve. The protocol and database were adapted for this effort to represent the features of the Point Reyes National Seashore and Golden Gate National Recreation Area located along the northern central coast of California. The database is an integration of spatial data and observation data entered and browsed through an interface designed to complement the methods of the observation protocol. The Coastal Biophysical Inventory (CBI) and Mapping Protocol is the methodology to collect and store repeatable observations of the intertidal zone to create a baseline of information useful for resource management and potentially assist damage assessment in the event of an oil spill. The inventory contributes to the knowledge needed for the conservation of coastal resources managed in the public’s trust. The Coastal Biophysical Inventory Database is a Microsoft Access 2003 format relational database with a customized data entry interface programmed in Microsoft Access Visual Basic for Applications. The interface facilitates the entry, storage and relation of substrate, biology, photographs, and other field observations. Data can be browsed or queried using query tools common to the Microsoft Access software or using custom spatial query tools built into the interface with ESRI MapObjects LT 2.0 ActiveX COM objects. The Coastal Biophysical Inventory’s GIS data set is useful for collecting, analyzing and reporting field observations about the intertidal zone. The GIS data set is linked to the observation data set through a unique number, the Segment ID, by using the relate tools found in ArcGIS (9.2-10). The Segment ID is a non-repeating number that references a section of coastline that is delineated by the type and form of the substrate observed. The Segment ID allows connection to the biological observations and other observation records such as photos or the original data sheets. Through ArcGIS connections to the observation database using the Segment ID, summaries of biodiversity or habitat can be made by location. The Coastal Biophysical Inventory has completed its initial goals to assess the coastline of two National Parks. The data set collected provides a snapshot of information and the database allows for future observations to be recorded. It provides coastal resource managers a broad insight and orientation to the intertidal resources managed by the National Park Service