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.... Show moreSatellite 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. Show less
The (slow) emergence of semi-automated or supervised detection techniques to identify anthropogenic objects in archaeological prospection using remote sensing data has received a mixed reception... Show moreThe (slow) emergence of semi-automated or supervised detection techniques to identify anthropogenic objects in archaeological prospection using remote sensing data has received a mixed reception during the past decade. Critics have stressed the superiority of human vision and the irreplaceability of human judgement in recognising archaeological traces, perceiving a threat that will undermine professional expertise and that archaeological experience and knowledge could be written out of the interpretative process (e.g. Hanson 2008, 2010; Palmer & Cowley 2010; Parcak 2009). Uneasiness amongst some archaeologists of losing control, even partially, of the interpretation process certainly seems to be a significant factor in criticisms, citing the undeniable fact that archaeological remains (or proxies for those remains) can assume a near-unlimited assortment of shapes, sizes and spectral properties. It is argued that only the human observer can deal with such complexity. Thus, while increasingly automated and supervised procedures for object detection and recognition and processing are flourishing in a variety of fields (e.g. medical imaging, facial recognition, cartography, navigation, surveillance; Szeliski 2011), their application to archaeological and, more generally, cultural landscapes is still in its infancy. However, as a number of published works (see References and General Reading List) and ongoing research demonstrate there are major benefits in developing this broad agenda. This paper provides a general review of the issues from a synergistic rather than competitive perspective, highlighting opportunities and discussing challenges. It also summarises a session on Computer vision vs human perception in remote sensing image analysis: time to move on held at the 44th Computer Applications and Quantitative Methods in Archaeology Conference (CAA 2016 Oslo 'Exploring Oceans of Data') that had a similar objective. Show less
The applications of automated object detection in remote sensing archaeology have grown considerably in the last few years. This reading list has been compiled as a contribution to consolidating... Show moreThe applications of automated object detection in remote sensing archaeology have grown considerably in the last few years. This reading list has been compiled as a contribution to consolidating current perspectives at September 2016, and in support of the preceding paper on the broader issues of human and computer vision in archaeological prospection (Traviglia et al.). Show less
Environmentally imposed selection pressures are well known to shape animal signals. Changes in these signals can result in recognition mismatches between individuals living in different habitats,... Show moreEnvironmentally imposed selection pressures are well known to shape animal signals. Changes in these signals can result in recognition mismatches between individuals living in different habitats, leading to reproductive divergence and speciation. For example, numerous studies have shown that differences in avian song may be a potent prezygotic isolating mechanism. Typically, however, detailed studies of environmental pressures on variation in animal behavior have been conducted only at small spatial scales. Here, we use remote‐sensing data to predict animal behavior, in this case, bird song, across vast spatial scales. We use remotely sensed data to predict the song characteristics of the little greenbul (Andropadus virens), a widely distributed African passerine, found across secondary and mature rainforest habitats and the rainforest‐savanna ecotone. Satellite data that captured ecosystem structure and function explained up to 66% of the variation in song characteristics. Song differences observed across habitats, including those between human‐altered and mature rainforest, have the potential to lead to reproductive divergence, and highlight the impacts that both natural and anthropogenic change may have on natural populations. Our approach offers a novel means to examine the ecological correlates of animal behavior across large geographic areas with potential applications to both evolutionary and conservation biology. Show less
