A Google Earth Engine-enabled Python approach for the identification of anthropogenic palaeo-landscape features

The necessity of sustainable development for landscapes has emerged as an important theme in recent decades. Current methods take a holistic approach to landscape heritage and promote interdisciplinary dialogue facilitate complementary management strategies. With the socio-economic values “natural” “cultural” increasingly recognised worldwide, remote sensing tools are being used more recording heritage. The advent freeware cloud computing services enabled significant improvements research allowing rapid exploration processing satellite imagery such Landsat Copernicus Sentinel datasets. This represents one first applications Google Earth Engine (GEE) Python application programming interface (API) studies historic landscapes. complete free open-source software (FOSS) protocol proposed here consists code script developed Colab, which could be adapted replicated different areas world. A multi-temporal been adopted investigate potential Sentinel-2 detect buried hydrological anthropogenic features along with spectral index decomposition analysis. protocol's effectiveness identifying palaeo-riverscape tested Po Plain (N Italy).