A new article led by Landscape Archaeology Research Group (GIAP) of the Catalan Institute of Classical Archaeology (ICAC) presents an integrated workflow that combines Big Earth Data and spatial analysis in Google Earth Engine to provide an efficient tool for the multi-temporal detection and monitoring of heritage at risk. Agustín Lobo, Geosciences Barcelona (GEO3BCN-CSIC) researcher, has contributed to the design of the method to detect agricultural fields nearby cultural heritage sites from time series of satellite images.
The algorithm uses the latest Sentinel-2 satellite imagery, and it employs average bands of spectral indexes to map the yearly occurrence of crops in areas that have been recently transformed into new agricultural fields. The workflow integrates the multi-temporal mapping of land cover change with the automated evaluation and assessment of the impact of agricultural encroachment within protective buffer zones.
The first implementation of the algorithm has been tested in the Cholistan Desert in eastern Pakistan. “The study area is home to hundreds of archaeological mounds dating back to the Indus Civilization. As with many other drylands elsewhere, the recent development of irrigation schemes threatens the preservation and visibility of many archaeological locations and such new developments were often largely undetected”, ICAC team said.
According to the article, the application of AgriExp has revealed a widespread land transformation of desert rangelands from 2018 onwards. In 2020 only, dozens of mounds were encroached and partially levelled, and today at least 50% of the known mounds in the region present some degree of affectation by recent irrigation developments.
The published algorithm represents a step forward in standardizing satellite-based outputs to systematically and continuously monitor long- to short-term threats and hazards to heritage sites. The implementation of AgriExp does not require advanced computational skills or data pre-processing. As such it has potential not only for academic use, but also for heritage agencies and practitioners, in particular for those professionals working in drylands where pedestrian or in situ monitoring of damage is not always possible and hundreds of archaeological and historical sites still remain unprotected.
This piece of information has been originally written by GIAP team
Spanish version | Catalan version
Conesa, F. C., Orengo, H. A., Lobo, A., & Petrie, C. A. (2023). An Algorithm to Detect Endangered Cultural Heritage by Agricultural Expansion in Drylands at a Global Scale. In Remote Sensing (Vol. 15, Issue 1). https://doi.org/10.3390/rs15010053
