Exploiting satellite SAR for archaeological prospection and heritage site protection

Optical and Synthetic Aperture Radar (SAR) remote sensing has a long history of use and reached a good level of maturity in archaeological and cultural heritage applications, yet further advances are viable through the exploitation of novel sensor data and imaging modes, big data and high-performance computing, advanced and automated analysis methods. This paper showcases the main research avenues in this field, with a focus on archaeological prospection and heritage site protection. Six demonstration use-cases with a wealth of heritage asset types (e.g. excavated and still buried archaeological features, standing monuments, natural reserves, burial mounds, paleo-channels) and respective scientific research objectives are presented: the Ostia-Portus area and the wider Province of Rome (Italy), the city of Wuhan and the Jiuzhaigou National Park (China), and the Siberian “Valley of the Kings” (Russia). Input data encompass both archive and newly tasked medium to very high-resolution imagery acquired over the last decade from satellite (e.g. Copernicus Sentinels and ESA Third Party Missions) and aerial (e.g. Unmanned Aerial Vehicles, UAV) platforms, as well as field-based evidence and ground truth, auxiliary topographic data, Digital Elevation Models (DEM), and monitoring data from geodetic campaigns and networks. The novel results achieved for the use-cases contribute to the discussion on the advantages and limitations of optical and SAR-based archaeological and heritage applications aimed to detect buried and sub-surface archaeological assets across rural and semi-vegetated landscapes, identify threats to cultural heritage assets due to ground instability and urban development in large metropolises, and monitor post-disaster impacts in natural reserves

Integrating Remote Sensing and Geophysics for Exploring Early Nomadic Funerary Architecture in the “Siberian Valley of the Kings”

This article analyses the architecture of the Early Iron Age royal burial mound Tunnug 1 in the “Siberian Valley of the Kings” in Tuva Republic, Russia. This large monument is paramount for the archaeological exploration of the early Scythian period in the Eurasian steppes, but environmental parameters make research on site difficult and require the application of a diversity of methods. We thus integrate WorldView-2 and ALOS-2 remote sensing data, geoelectric resistivity and geomagnetic survey results, photogrammetry-based DEMs, and ortho-photographs, as well as excavation in order to explore different aspects of the funerary architecture of this early nomadic monument. We find that the large royal tomb comprises of a complex internal structure of radial features and chambers, and a rich periphery of funerary and ritual structures. Geomagnetometry proved to be the most effective approach for a detailed evaluation of the funerary architecture in our case. The parallel application of several surveying methods is advisable since dataset comparison is indispensable for providing context

Sar Simulatio N Based Change Detectio N With High-Reso Lutio N Sar Images In Urban Enviro Nments

C mbined pr cessing using different sens r types, i .e. f r applicati ns like change detecti n, require s a g d ge-referencing. Furtherm re the individual sens r pr perties have t b e taken int acc unt. SAR systems are side-l king and run-time systems. They suffer fr m cclusi ns and ambiguities especially in urban areas. Additi nally lay ver and shad w effe cts disturb the ge-referencing f SAR images in urban areas, which is a prerequisite f r a successful change detecti n. An impr ved g e-referencing can be achieved by simulating 3D-city m dels r street dat asets using a SAR simulat r and c mparing the simul ated image t the real image. C rresp ndences between simulated and real image can be used f r ge-referencing the image accrding t the c rdinates f the 3D-city m del r street dataset. The ge-refere nced dataset can afterwards be used f r change dete cti n analysis. SAR images represent a side-view f the three dimensi nal w rl d. An aut mated change detecti n using SAR images sh uld take this fact int c nsiderati n and theref re sh uld use 3D-m dels as reference f r the change-detecti n. These m dels a re simulated and the simulated image is c mpared t the ge-referenced i mage, revealing changes between the simulated m del and the real image. 1. INTRO DUCTIO The urban envir nment is f the utm st imp rtance f r human s ciety. I n 2001, ar und 50% f the human p pulati n lived in cities and these numbers are still rising, especially in less develped c untries (UNCHS, 2001). The dense placement f buildings in cities requires a g d res luti n f the re m te sensing systems, t distinguish between the neighb uring bu ildings. M dern high-res luti n airb rne SAR systems reach very high res luti ns up t 10cm (Ender & Brenner, 2003) and are theref re usea..

Discernibility of Burial Mounds in High-Resolution X-Band SAR Images for Archaeological Prospections in the Altai Mountains

The Altai Mountains are a heritage-rich archaeological landscape with monuments in almost every valley. Modern nation state borders dissect the region and limit archaeological landscape analysis to intra-national areas of interest. Remote sensing can help to overcome these limitations. Due to its high precision, Synthetic Aperture Radar (SAR) data can be a very useful tool for supporting archaeological prospections, but compared to optical imagery, the detectability of sites of archaeological interest is limited. We analyzed the limitations of SAR using TerraSAR-X images in different modes. Based on ground truth, the discernibility of burial mounds was analyzed in different SAR acquisition modes. We show that very-high-resolution TerraSAR-X staring spotlight images are very well suited for the task, with >75% of the larger mounds being discernible, while in images with a lower spatial resolution only a few large sites can be detected, at rates below 50%

Potentials and Limitations of SAR Image Simulators - A Comparative Study of Three Simulation Approaches

Various applications, like for instance algorithm design, mission planning, geo-referencing, change detection, Automatic Target Recognition (ATR) or SAR data analysis, rely on simulated synthetic aperture radar (SAR) images. However, there are different SAR simulation techniques with different advantages and disadvantages. Depending on the needs of a certain application, a suitable SAR simulation technique has to be used. This paper compares three SAR image simulation approaches, RaySAR, CohRaS®, and SARViz, showing their similarities and differences. RaySAR and CohRaS® are two ray tracing based SAR image simulators. RaySAR is based on the open-source software POV-Ray, while CohRaS® is developed as SAR simulator from scratch. The third simulator, SARViz, is a real-time SAR simulator based on the rasterization approach. The geometrical features of the three simulators are compared and the differences and different applications are analyzed

Scientometric Full-Text Analysis of Papers Published in Remote Sensing between 2009 and 2021

Covering the full texts of all papers published in MDPI’s Remote Sensing between 2009 and 2021, in-depth scientometric analyses were conducted. Trends in publications show an increase in the overall number of papers. A relative increase in papers using SAR sensors and a relative decrease in papers using optical remote sensing can also be seen. The full-text analyses reveal distinctive styles and writing patterns for papers from different sub-fields of remote sensing and for different countries and even cities. While a slight increase in the readability of abstracts is detected over time, the overall readability of papers is decreasing. Institutional co-authorship analysis reveals the ongoing ‘scientific decoupling’ between China and the USA in remote sensing. Using scientometric full-text analysis, current trends and developments are revealed

EVENT-DRIVEN CHANGE-DETECTION IN URBAN ENVIRONMENTS USING SAR ABSTRACT:

SAR sensors are able to operate under nearly all weather conditions, at daylight or in the night. This is especially beneficial for event-driven applications, like time-critical change-detection for disaster management. Unfortunately, SAR systems suffer from occlusions and ambiguities, especially in urban areas. Additionally, due to layover and foreshortening effects, the geo-referencing of SAR images, which is a prerequisite for a change detection, is problematic in urban areas. The initial geo-referencing of the SAR data can be automatically improved using street vectors. By comparing image chips from the SAR image, to the transformed street data, correspondences can be found, which can be used for geo-referencing. Change-detection, combining newly acquired SAR images with other types of data, should use 3D-groundtruth, due to the side-looking property of SAR sensors. The result of the SAR simulation, based on 3D-data, is compared to the real SAR image. It is possible to even use simple models and assumptions for the simulation, like for example lambertian reflection. 1