|Paper title||Assessing desertification in southern Morocco using a Google Earth Engine-enabled Python approach|
|Form of presentation||Poster|
The impact of anthropogenic climate change and pressures on water resources will be significant in the oases of the Northern Sahara but there is a paucity of detailed records and a lack of knowledge of traditional water management approaches in the long term. Landscapes emerge through complex, interrelated natural and cultural processes and consequently encompass rich data pertaining to the long-term interactions between humans and their environments. Landscape heritage plays a crucial role in developing local identities and strengthening regional economic growth.
Remote sensing technologies are increasingly being recognised as effective tools for documenting and managing landscape heritage, especially when used in conjunction with archaeological data. However, proprietary software licenses limit access to broader community growth and implementation. Conversely, FOSS (free and open-source software) geospatial data and tools represent an invaluable alternative mitigating the need for software licensing and data acquisition, a critical barrier to broader participation. Freeware cloud computing services (e.g. Google Earth Engine - GEE) enable users to process data and create outputs without significant investment in the hardware infrastructure. GEE platform combines a multi-petabyte catalogue of geospatial datasets and provides a library of algorithms and a powerful application programming interface (API). The highest resolution available in GEE (up to 10 m/pixel) is offered by the Copernicus Sentinel-2 satellite constellation, which represents an invaluable free and open data source to support sustainable and cost-effective landscape monitoring. In this research, GEE has been employed via the Python API in Google Colaboratory (commonly referred to as “Colab”). This Python development environment in this research runs in the browser using Google Cloud. Python has proven to be the most compatible and versatile programming language as it supports multi-platform application development. Also, it is continuously improved thanks to the implementation of new libraries and modules.
The GEE-enabled Python approach used in this research aims to assess the desertification rate in the oasis-dominated area of the Ourzazate-Drâa-Tafilalet regions of Morocco. Desertification is an environmental problem worldwide and is one of the most decisive changing factors in the Moroccan landscape, especially in the oases in the south-eastern part of the country. This region is well known for its oasis agroecosystems and the earthen architectures of its Ksour and Kasbahs, where oases have been supplied by a combination of traditional water management systems including ‘seguia’ canals and ‘khattara’ (groundwater collecting tunnels). The survival of the unique and invaluable landscape heritage of the region is threatened by several factors such as the abandonment of traditional cultivation and farming systems, overgrazing and increased human pressure on land and water resources. In addition, the Sahara’s intense natural expansion is changing the landscape heritage of the region rapidly.
The free and open-source Copernicus Sentinel 2 dataset and freeware cloud computing offer considerable opportunities for landscape heritage stakeholders to monitor changes. In this paper, a complete FOSS cloud procedure was developed to map the degree of desertification in the Drâa-Tafilalet region between 2015 and 2021. The Python protocol calculates the spectral index and spectral decomposition techniques to determine the Desertification Degree Index (DDI) and visually assess the effect of climate change on the landscape heritage features in the area. This has been investigated and validated in the field through field visits, most recently in November 2021.
The development of FOSS-cloud procedures such as those described in this study could support the conservation and management of landscape heritage worldwide. In remote areas or where local heritage is threatened due to climate change or other factors, FOSS-cloud protocols could facilitate access to new data relating to landscape archaeology and heritage.