Abstract
Satellite imagery has had limited application in the analysis of pre-colonial settlement archaeology in the Caribbean; visible evidence of wooden structures perishes quickly in tropical climates. Only slight topographic modifications remain, typically associated with middens. Nonetheless, surface scatters, as well as the soil characteristics they produce, can serve as quantifiable indicators of an archaeological site, detectable by analyzing remote sensing imagery. A variety of pre-processed, very diverse data sets went through a process of image registration, with the intention to combine multispectral bands to feed two different semi-automatic direct detection algorithms: a posterior probability, and a frequentist approach. Two 5 × 5 km2 areas in the northwestern Dominican Republic with diverse environments, having sufficient imagery coverage, and a representative number of known indigenous site locations, served each for one approach. Buffers around the locations of known sites, as well as areas with no likely archaeological evidence were used as samples. The resulting maps offer quantifiable statistical outcomes of locations with similar pixel value combinations as the identified sites, indicating higher probability of archaeological evidence. These still very experimental and rather unvalidated trials, as they have not been subsequently groundtruthed, show variable potential of this method in diverse environments.
Highlights
The fascination with feature identification and mapping of geometric archaeological alignments by means of remote sensing is as old as the first appearance of aerial photos [1,2,3]
This approach had been successfully applied elsewhere and involved using known sites and alleged non-sites to build a binary classifier where each cell was assigned a posterior probability of being an archaeological site
Considering the entered data sets, known sites were mostly located in the mangrove forest and on hilltops or slopes, while non-sites were distributed over the complete data set, the results showed a positive outcome, coloring similar locations in deep red (Figure 5)
Summary
The fascination with feature identification and mapping of geometric archaeological alignments by means of remote sensing is as old as the first appearance of aerial photos [1,2,3]. Throughout the last centuries, it has advanced significantly, leading to new archaeological discoveries using imagery from satellites and drones [4,5]. Automatic approaches in pattern recognition have become common, often based on computer algorithms adopted from other disciplines [7,8,9,10], and tested for archaeological purposes to detect color [11,12], changes in topography [13,14] or different reflection patterns [15]. A different challenge is the identification of non-geometric archaeological features with more amorphous shape and structure. Without any clear geometry they pose a special problem, as the most
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