Special Issue "Remote Sensing of Archaeology"
Deadline for manuscript submissions: 30 November 2021.
Interests: remote sensing; near-surface geophysical methods; quantitative methods; agent-based modeling; evolutionary archaeology
Interests: near-surface applied geophysics; UAV-based remote sensing; geoarchaeology; GIS statistical and physical modeling
Recent advances in remote sensing instrumentation, data availability, and processing methods are revolutionizing the discipline of archaeology. The development of machine algorithms for data processing combined with an increasingly diverse array of ground-based instruments and low-cost, lightweight sensors mounted on intelligent unmanned aerial vehicles (UAVs) has greatly enabled our ability to conduct archaeological prospection, allowing entire landscapes to be efficiently and non-invasively documented in a fraction of the time it would take to laboriously survey and destructively excavate areas of the archaeological record. Archaeological remote sensing, traditionally used to simply guide excavation strategy and constrain site formation hypotheses, is now moving beyond prospection and into areas in which remote sensing studies can directly contribute to the study of human behavior, social organization, and cultural changes through time and across space.
With this Special Issue, we seek innovative contributions on state-of-the-art archaeological remote sensing research that addresses recent advances in these broad areas: data acquisition, including the use of unmanned autonomous systems; novel measurement concepts/sensor technologies; advanced and automated data processing, including object-based image analysis, machine and deep learning, and modeling; quantitative data interpretation, including information fusion from multiple sensors and geostatistical methods; near-surface geophysics; cultural and heritage resource stewardship, preservation, and management; aerial and satellite-based remote sensing; integrative approaches combining geoarchaeology ground verification and remote sensing to iteratively improve the efficiency of invasive research. Review papers, case studies, and best-practice examples are welcome. We encourage submissions from a broad remote sensing perspective, including space-based satellite-based remote sensing all the way down to barely remote near-surface geophysics.
Dr. Carl Philipp Lipo
Dr. Timothy S de Smet
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Machine learning
- Object-based image analysis
- Unmanned aerial vehicles
- Near-surface geophysics
- Information fusion
- Archaeological prospection
- Landscape archaeology
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
1. Title: Sensing the Past: Perspectives on Remote Sensing from Coastal California
author list: Gabriel Sanchez, et, al.
Brief Description: This paper summarizes recent work along the central coast of California that employs remote sensing to preserve a record of cultural resources threatened by coastal erosion (LIDAR) and geophysical methods (ground penetrating radar, magnetometry, and resistivity) to identify archaeological deposits, minimize impacts on sensitive cultural resources, and provide tribal and state collaborators with a suite of data before proceeding with archaeological excavations.
2. Novel approach to sharpening the GPR images of historical graves at Cape Canaveral, FL
Author list: Downs, Christine, Rogers, Jaime, Collins, Lori, Doering, Travis and Penders, Thomas
Due to its non-invasive approach, rapid data acquisition, and real-time data viewing, ground-penetrating radar (GPR) has long been considered an ideal geophysical method for archaeological applications. The technique offers high spatial resolution, but extracting a sharp image of the subsurface remains a challenge, which is particularly necessary when identifying the locations of graves. Here we present the effectiveness of singular value decomposition (SVD) to remove unwanted components in the GPR image in order to improve subsequent processing algorithms such as migration. SVD is shown to be an efficient method of removing the direct wave, horizontal banding, and vertical ringing over mean trace subtraction (a.k.a. background removal) and bandpass/fk-filtering. GPR images filtered with the SVD method yield more distinct diffraction patterns, which produce clearer point anomalies. Depth slices from GPR data collected as a grid and filtered with SVD show higher resolution in plane view as well. These findings suggest SVD to be a preferred filtering scheme over more traditional processing steps for data over point-like targets such as those expected in archaeological settings.