Editing Shadow marks (section)

== Remote sensing applications ==
Shadow marks, as elevation-dependent surface indicators, play a central role in archaeological surveys by visually exposing buried or [[eroded]] structures.<ref name=":7">{{Cite journal |last=Neubauer |first=Wolfgang |date=January 2001 |title=Images of the invisible-prospection methods for the documentation of threatened archaeological sites |url=http://link.springer.com/10.1007/s001140000192 |journal=Naturwissenschaften |language=en |volume=88 |issue=1 |pages=13–24 |doi=10.1007/s001140000192 |pmid=11261352 |bibcode=2001NW.....88...13N |issn=0028-1042}}</ref> While their visibility largely depends on lighting—previously discussed—they are especially effective in identifying fortifications and earthworks, particularly in pre-modern agricultural landscapes where terrain alterations are preserved.<ref name=":0" /><ref name=":3" /><ref name=":4" />[[File:Kite aerial photo the site of Ogilface Castle, Woodend, West Lothian in low sunlight.jpg|thumbnail|right|Kite aerial photo of the site of Ogilface Castle, Woodend, West Lothian in low sunlight]][[Aerial photography]] has been the primary method of recording shadow marks, particularly in early 20th-century archaeological explorations.<ref name=":7" /><ref>{{Cite journal |last=Verhoeven |first=Geert |date=2017-09-14 |title=Are We There Yet? A Review and Assessment of Archaeological Passive Airborne Optical Imaging Approaches in the Light of Landscape Archaeology |journal=Geosciences |language=en |volume=7 |issue=3 |page=86 |doi=10.3390/geosciences7030086 |doi-access=free |bibcode=2017Geosc...7...86V |issn=2076-3263}}</ref> Early archaeologists recorded shadow marks via images captured manually in the early morning or evening to highlight the contrast of landscape changes using a traditional camera or aerial photography.<ref name=":7" /> Technology in remote sensing has improved this process by developing high-resolution satellite imagery, surveying with drones, and complimentary surveys using airborne [[Lidar|Light Detection and Ranging]] (LiDAR).<ref name=":8" /> LiDAR has been a significant advancement in the detection of shadow marks, as its main contribution is the ability to generate a [[Digital Terrain Model]] (DTM) that highlights slight variations in the topography that were previously hidden because of dense vegetation.<ref name=":7" />

=== Case studies ===
Real-world case studies demonstrate the practical value of shadow marks in archaeological detection. For instance, aerial surveys over [[Maiden Castle, Dorset|Maiden Castle]] in England revealed complex fortification structures through shadow-enhanced topography.<ref>{{Cite journal |last=Bewley |first=Robert H. |date=2003 |title=Aerial survey for archaeology |url=https://onlinelibrary.wiley.com/doi/10.1046/j.0031-868X.2003.00023.x |journal=The Photogrammetric Record |language=en |volume=18 |issue=104 |pages=273–292 |doi=10.1046/j.0031-868X.2003.00023.x |bibcode=2003PgRec..18..273B |issn=1477-9730}}</ref>  Similarly, in China, [[Synthetic-aperture radar|SAR]] imagery successfully detected shadow patterns of buried city walls beneath agricultural fields.<ref name=":15" />

These examples highlight how shadow marks often provide the first visual cue of subsurface features—especially when crop and soil marks offer limited information.<ref name=":9">{{Cite book |last=Wilson |first=David Raoul |url=https://archive.org/details/airphotointerpre0000wils/mode/2up |title=Air photo interpretation for archaeologists |date=1982 |publisher=New York : St. Martin's Press |others=Internet Archive |isbn=978-0-312-01527-5 |pages=27–69}}</ref><ref name=":1" />  Shadow marks are the most informative when they are used along with other [[remote sensing]] methodologies.<ref name=":9" /><ref name=":10">{{Cite journal |last1=Del Pozo |first1=S. |last2=Rodríguez-Gonzálvez |first2=P. |last3=Sánchez-Aparicio |first3=L. J. |last4=Muñoz-Nieto |first4=A. |last5=Hernández-López |first5=D. |last6=Felipe-García |first6=B. |last7=González-Aguilera |first7=D. |date=2017-08-18 |title=Multispectral Imaging in Cultural Heritage Conservation |url=https://isprs-archives.copernicus.org/articles/XLII-2-W5/155/2017/ |journal=The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |language=English |volume=XLII-2-W5 |pages=155–162 |doi=10.5194/isprs-archives-XLII-2-W5-155-2017 |doi-access=free |bibcode=2017ISPAr62W5..155D |issn=1682-1750}}</ref> When combined with other forms of remote sensing, shadow marks help triangulate archaeological interpretations through complementary visual, biological, and physical indicators.<ref name=":9" />

Archaeologists today are therefore placing an emphasis on a multiproxy approach. As researchers use shadow mark analysis paired with [[Lidar|LiDAR]] (topography), GPR (subsurface readings), and multispectral band analyses (landscape development); they categorize between anthropogenic and natural features.<ref>{{Cite journal |last=Bitelli |first=Gabriele |date=2012 |editor-last=Lasaponara |editor-first=Rosa |editor2-last=Masini |editor2-first=Nicola |title=Satellite Remote Sensing |url=https://link.springer.com/book/10.1007/978-90-481-8801-7 |journal=Remote Sensing and Digital Image Processing |volume=16 |language=en |pages=113–126 |doi=10.1007/978-90-481-8801-7 |isbn=978-90-481-8800-0 |issn=1567-3200}}</ref> As more data goes into [[Geographic information system|Geographic Information Systems]] (GIS), but shadow marks could also be placed in GIS, the spatial analysis of archaeological sites can improve predictive modeling and our ability to reconstruct cultural landscapes.<ref>{{Cite book |last=Cowley |first=Dave |url=https://www.academia.edu/6730535 |title=Remote Sensing for Archaeological Heritage Management |date=2011-01-01 |isbn=978-963-9911-20-8 |pages=43–58}}</ref> Shadow marks will remain important - even if they are a relatively low technology - in the expanding toolbox of remote sensing archaeology.<ref name=":7" />

=== Limitations and solutions ===
While shadow marks can enhance the visibility of ancient features under ideal lighting conditions, they are also highly susceptible to environmental interference.<ref name=":2" /> Cloud shadows, uneven terrain, vegetation, and surface modifications—such as roads or ploughing—can all distort or obscure shadow patterns, making interpretation less reliable.<ref name=":2" /><ref name=":1" /> These limitations necessitate the use of advanced remote sensing techniques and multi-sensor methodologies.<ref name=":1" /> Passive optical imaging via aerial technology has also improved shadow mark interpretation.<ref name=":8" /> [[Multispectral imaging|Multispectral]] and [[Hyperspectral imaging|hyper-spectral imaging]] makes it possible to filter some atmospheric interferences, such as cloud shadows or remove them and preserve archaeological patterns, as it does compensate for shadow marks on the earth’s surface when recording sunlight and manipulating shadows.<ref>{{Cite journal |last=Verhoeven |first=Geert |date=2017-09-14 |title=Are We There Yet? A Review and Assessment of Archaeological Passive Airborne Optical Imaging Approaches in the Light of Landscape Archaeology |journal=Geosciences |language=en |volume=7 |issue=3 |pages=12–17 |doi=10.3390/geosciences7030086 |doi-access=free |bibcode=2017Geosc...7...86V |issn=2076-3263}}</ref> A multispectral light dome also allows archaeologists to simulate sun angles for interpreting shadow marks in digital reconstructions.<ref name=":6" /> In addition, synthetic lighting simulations can be developed to create shadow conditions artificially, which gives archaeologists the potential capabilities to manipulate digital terrain features that may not be possible in situ.<ref name=":12">{{Cite journal |last1=Hubert |first1=Mara |last2=Krömker |first2=Susanne |date=2017 |title=Visual Computing for Archaeological Artifacts with Integral Invariant Filters in 3D |url=https://diglib.eg.org/server/api/core/bitstreams/25baea81-03f8-4a5a-a8b0-679a5ccc02f2/content |journal=GCH Conference Proceedings |pages=2–7}}</ref>

The environment and seasonal factors can still influence shadow marks, as archaeologists work in areas with frequent cloud cover or shifts in shadow angle of periodical archaeological features.<ref name=":0" /><ref name=":7" /> Likewise, although perfect air and vegetation conditions may be present, modern infrastructure, roads, and contemporary urban development may also distort or compact the shadow marks footprints, making interpretation increasingly difficult.<ref>{{Cite journal |last=Verhoeven |first=Geert |date=2017-09-14 |title=Are We There Yet? A Review and Assessment of Archaeological Passive Airborne Optical Imaging Approaches in the Light of Landscape Archaeology |journal=Geosciences |language=en |volume=7 |issue=3 |pages=9–12 |doi=10.3390/geosciences7030086 |doi-access=free |bibcode=2017Geosc...7...86V |issn=2076-3263}}</ref> To address these, archaeologists now routinely use an integrated methodology, utilizing shadow-marked analysis alongside [[ground-penetrating radar]] (GPR) and [[Geomorphology|geomorphological]] survey applications to verify their past interpretations.<ref name=":7" /> These much-relied-upon interdisciplinary techniques and methodologies provide higher accuracy in the census of archaeological sites and ultimately verify the power of shadow marks in remote sensing applications for archaeology.<ref name=":7" />

In recent applications, spectral indices (such as band ratios and [[Normalized difference vegetation index|NDVI]]) have been used to diminish contrived impacts of cloud shadows, which obscure archaeological features including both crop marks and moist marks.<ref name=":1" /> These indices help counteract not only atmospheric effects, such as cloud interference, but also transient natural shadows that can originate from vegetation growth or passing weather systems.<ref name=":1" /> Using these approaches can improve the visibility of less visible circular marks, including those that result from buried ditches.

In addition, [[Synthetic-aperture radar|synthetic aperture radar]] (SAR) technology—particularly using [[COSMO-SkyMed]] X-band data—has demonstrated the potential to improve the identification of shadow marks under challenging environmental conditions.<ref name=":11">{{Cite journal |last1=Chen |first1=Fulong |last2=Masini |first2=Nicola |last3=Yang |first3=Ruixia |last4=Milillo |first4=Pietro |last5=Feng |first5=Dexian |last6=Lasaponara |first6=Rosa |date=2014-12-23 |title=A Space View of Radar Archaeological Marks: First Applications of COSMO-SkyMed X-Band Data |journal=Remote Sensing |language=en |volume=7 |issue=1 |pages=28–46 |doi=10.3390/rs70100024 |doi-access=free |bibcode=2014RemS....7...24C |issn=2072-4292}}</ref> When SAR data is layered with optical imagery, the combined approach significantly enhances detection reliability—particularly in arid or densely vegetated regions where optical methods alone are insufficient.<ref name=":2" /> Using both multi-temporal averaging and single-date enhancements (including speckle filtering and morphological processing), they sought to improve detection of microrelief marks and structures below the surface.<ref name=":11" /> Two advantages included that:

# Noise can (and was) suppressed while effectively preserving weak signals associated with archeological features or treatments;
# [[Radar]] imaging for sub-surface analysis can complement existing optical methods (and in some situations, exceed optical methods) when visibility is constrained.<ref name=":11" /><ref name=":10" />

Future studies of shadow optics will likely include imaging in real-time adaptive conditions, where agents (e.g., sensors) are tuned by an AI to adjust quickly to the conditions of light.<ref>{{Cite journal |last1=Huang |first1=Xiang |last2=Uffelman |first2=Erich |last3=Cossairt |first3=Oliver |last4=Walton |first4=Marc |last5=Katsaggelos |first5=Aggelos K. |date=September 2016 |title=Computational Imaging for Cultural Heritage: Recent developments in spectral imaging, 3-D surface measurement, image relighting, and X-ray mapping |url=https://ieeexplore.ieee.org/document/7560020 |journal=IEEE Signal Processing Magazine |volume=33 |issue=5 |pages=130–138 |doi=10.1109/MSP.2016.2581847 |bibcode=2016ISPM...33..130H |issn=1558-0792}}</ref> Hyperspectral imaging and improvements in LiDAR will increase the accurate classification of shadows and reduce false positives and errors. Merging physics outcomes and imaging methods will continue to the limits and interpreting shadow marks effectively as a critical framework of remote sensing and archaeologically detecting earth-based sites and features.<ref name=":5" />