Editing Shadow marks (section)

=== 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" />