In the Wadi Biskra arid and semiarid areas, sustainable development is restricted by land degradation processes such as secondary salinization of soils. Being an important high-quality date production region of Algeria, this area needs continuous monitoring of desertification indicators, hence highly exposed to climate-related risks. Given the limited access to field data, appropriate methods were assessed for the identification and change detection of salt-affected areas, involving image interpretation and automated classifications employing Landsat imagery, ancillary and multisource ground truth data. First, a visual photointerpretation study of the land cover and land use classes was undergone according to acknowledged methodologies. Second, two automated classification approaches were developed: a customized decision tree classification (DTC) and an unsupervised one applied to the principal components of Knepper ratios composite. Five indices were employed in the DTC construction, among which also is a salinity index. The diachronic analysis was undergone for the 1984 to 2015 images (including seasonal approach), being supported by the interpreted land cover/land use map for error estimation. Considering also biophysical and socioeconomic data, comprehensive results are discussed. One of the most important aspects that emerged was that the accelerated expansion of agricultural land in the last three decades has led and continues to contribute to a secondary salinization of soils.

Aeolian processes in drylands often transcend into sand encroachment, a common form of land degradation. Highly reflective desert features, hence sandy areas, often cause spectral confusion, and mapping through remote sensing techniques can be challenging. This work aims at designing an efficient classification method that minimises spectral confusion of desert features, hence two types of sandy areas. Moreover, we employ land cover (LC) change detection over the last 30 years. The extraction and spatiotemporal variations of LC and sand encroachment areas in the Dahar-Jeffara Medenine site (southeastern Tunisia) are assessed by employing Landsat imagery (1984 and 2014), a 30 m digital elevation model of Shuttle Radar Topography Mission (SRTMGL 1 arc second), field data and X-ray diffraction analyses of sand samples. Five new spectral indices were designed and employed in a Decision Tree (DT) classifier for the extraction of 11 LC classes, including two different types of sandy areas. The DT map yielded an overall accuracy of around 89%. Change detection results showed substantial change in several landscape components and an increase of sand units by 29% within the Jeffara-Medenine plain over the last three decades. Geomorphological observations and multi-temporal, spectral and mineral analyses indicate a main, possible in-situ source area of sand.

Oasis agroecosystems monitoring plays a significant role in the economic development, sustainable management, and policy-making of arid and Saharan regions. The aims of this study are to analyze the spatiotemporal changes of oasis vegetation and discuss possible driving forces of changes. This analysis employed field and ancillary data, geographic information system, Landsat imagery, and remote-sensing techniques. Minimum noise fraction is used for endmembers extraction, and spectral mixture analysis is applied to each image to extract vegetation fraction, which is used as an indicator of change. Change detection is performed in six oases in south-eastern Morocco over eight separate periods from 1984 to 2017 using Landsat data. The pattern of the spatiotemporal changes in vegetation cover is analyzed using time- and space-oriented change detection algorithms. Results indicate that the Mezguita, Tinzouline, and Ternata oases had an evenly distributed and constant expansion during the last three decades (of ∼41.35 % ), whereas the oases of Fezouata and Ktaoua presented low expansion and randomly distributed change (∼29 % ). However, the vegetation cover of M’Hamid oasis decreased by 23% over the studied period. The results show that spectral mixture analysis yields high accuracies for oasis vegetation extraction in arid areas and accounts for mixed pixel issues. The results are discussed considering also climate and socioeconomic factors, showing that the driving forces of these dynamics are primarily anthropogenic.

In this paper, we report on the first project on the promotion of urban geoheritage in Cagliari, the capital of the Autonomous Region of Sardinia (Italy). We briefly address the history of geo-palaeontological research in the city area and outline the main phases of development in the history of Cagliari’s geo-palaeontological museum. Geotourism is an efficient method of bringing geosciences to a wider audience. For this project, we compiled a geoitinerary of the main lithotypes and fossils present within the urban territory. Miocene lithotypes are the most important materials in the edification of the Cagliari’s old town, and in the past, the quarrying activity favoured the geology knowledge of the area. The presence of abandoned quarries and natural outcrops in parks, public gardens, on the nearby coastline, and also of fossils exposed in ashlars of historic buildings, made Cagliari an excellent example to valorise the geo-palaeontological heritage using geotourism. This project showcases the importance of knowledge transfer and non-technical communication methods by converting highly technical aspects into accessible and engaging information dissemination to a wide range of audience types, including non-specialised ones.