Remote Sensing Final Project: Multispectral Image Analysis in Archaeological Applications.
Remote Sensing Final Project
Multispectral Image Analysis in
Archaeological Applications.
Tristan Haroldsen
University of West Florida
Photo Interpretation and Remote Sensing
Brian Fulfrost
12/4/2024
Introduction:
The consensus of Archaeologists is that we have discovered
and documented less than three percent of available Archaeological sites
worldwide. This is due in part to the remote nature of many sites, the ever-changing
landscape as well as numerous other factors. To cut through these factors
Archaeologists are implementing new and improving technologies in the field of
remote sensing to rediscover our collective past.
While the utilization of remote sensing technologies in the
field of archaeology is commonplace the implementation of aerial photogrammetry
as well as other remote sensing procedures is often made difficult due to thick
forest or vegetation that blankets the terrain. In such cases, technologies
such as LiDAR may be implemented to penetrate the thick forest canopy allowing
researchers to render detailed depictions of the forest floor once obscured by
the canopy.
This, however, is not without its challenges and limitations.
Due to the limited number of laser points which ultimately penetrate the forest
canopy many archaeological sites may be inaccurately classified simply as bare
ground rather than identified as an archaeological feature due to the region’s
topography and other mitigating circumstances.
In such instances I propose that it may be possible to
identify features or patterns of the vegetation itself to discern the location
of potential archaeological sites. For example, could multispectral imaging be
used to identify patterns in the vegetation such as its health, density, and or
species diversity to locate archaeological sites hidden beneath?
Case
Studies:
An analysis of archaeological literature does indicate that these techniques have been used successfully in similar contexts. For example, in a study of Crop Mark Analysis in Northwestern Iberia researchers utilized “multispectral imaging via Unmanned Aerial Systems (UAS) and digital image processing to identify archaeological sites obscured by complex vegetation in the Iberian Peninsula. Techniques such as NDVI and Principal Component Analysis (PCA) helped distinguish crop marks associated with ancient settlements from natural vegetation patterns.” (Peña-Villasenín et al., 2024)
Background:
Methods:
Note: Remote sensing imagery sources.
Filters
and Band indices (like NDVI)
Using
a multispectral image composite of the location and implementing a variety of filters
and band indices such as False Color Infrared and NDVI or Normalized Difference
Vegetation Index which are often utilized in forestry and agricultural
applications to assess crop health as well as vegetation density of an area we
can ascertain if any anomalies are present in the image.
False
Color IR which readily detects vegetation by visualizing colors outside of what
the human eye can detect and displaying it in shades of Red with dense or
healthy vegetation appearing darker and sparse of unhealthy vegetation
appearing lighter allows for a clear view of the vegetative health of the site
as seen below. Using this filter, it is easy to visualize the separation of
healthy forest and several deforested or sparkly forested areas surrounding the
site.
Upon careful inspection it is evident that several anomalies
can be seen within the image. Several square shaped growth patterns can be seen
within the central intersections of the Nohoch Mul causeway system (blue) as
well as the Coba system depicted (red) which may indicate potential structures
at these sites.
In order to collaborate these findings NDVI or the
Normalized Difference Vegetation Index which uses a multispectral image and
calculates the relation between the Red and Infrared Bands to assess the
photosynthetic capacity of vegetation can be used which allows researchers to
assess biomass, growth density and plant health allowing by displaying vegetation
on an index of 1 to -1 with bare ground displayed as 0 and water displayed as
-1 allowing for slight variations in photosynthetic properties to be identified.
In the map below healthy or dense vegetation is displayed as bright white while
unhealthy vegetation will be displayed as darkening shades of grey.
In this image we again can see that several anomalies are
present in the form of healthy vegetative growth appearing in square patterns
within the central intersections of the Nohoch Mul causeway system depicted in
on the map below in light blue which may indicate archaeological activity at
the location while also confirming the anomaly found within the Near Infrared
Image.
Unsupervised
Classifications.
By
utilizing the location of the anomaly identified and corroborated with both the
IR and the NDVI indices as a reference point it is then possible to isolate and
classify the location based on its specific spectral signature to identify any features
sharing that identical signature which may be difficult to discern using IR and
NDVI. By performing an Unsupervised Classification of the image, each pixel displayed
on the image is broken down into unique classifications allowing us to then isolate
the area of interest and display it in red alongside all other locations
emitting the same frequency ultimately providing us with the locations of all sites
on the map displaying those unique qualities.
On the
map below these locations are depicted in red and by doing so it becomes
obvious that many of these features do indeed align themselves with the various
causeway systems as well as fall within the estimated locations of the suburban
groups (pink) identified by archaeologists on the ground.
Ground
Truthing
While
ground truthing these locations requires boots on the ground in the form of
archaeological experts it is possible to implement high resolution aerial imagery
sourced from the Esri imagery basemap to get a closer look at the location perhaps
providing detail which may be unavailable with satellite imagery. Using these high
resolution arial images of the location it is evident that an obvious archaeological
anomaly is indeed located at the center of the Nohoche Mul Causeway System as seen
below providing us with some level of verification to our findings.
Results and Conclusion
In
conclusion it appears evident that through the usage of multispectral image
processing archaeological sites may be able to be identified based solely on
vegetation density and plant health. In the case of Coba, it appears that when
combined with the known locations of the Mayan causeways and by ground proofing
against known sites these processes provide reasonable evidence of structures
hidden underneath vegetative cover within out designated areas of interest.
While it is impossible to definitively identify
archaeological locations without traditional archaeological excavations,
multispectral image analysis can be a useful tool to visualize the probable
locations of sites and should be considered in specific instances such as those
detailed in this journal.
1) Peña-Villasenín, S., Gil-Docampo, M., & Ortiz-Sanz, J. (2024). Hidden archaeological remains in heterogeneous vegetation: A crop marks study in fortified settlements of northwestern Iberian Peninsula. Remote Sensing, 16(21), 3923. https://doi.org/10.3390/rs16213923
2) Atlas of Maya Archaeological Sites. Wayeb. (2017, December 6). https://www.wayeb.org/resources-links/wayeb-resources/wayeb-gis-atlas/#1511961556518-9b8a4bab-1001
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