Landslides are a worldwide occurring hazard that can produce economic impact and even fatalities. The collection and monitoring of data regarding active landslides are important for predicting future landslides in that region, and is critical to minimize the losses caused. In the expanding metropolitan area of Cluj-Napoca, Romania, drastic changes of land use and increasement of construction zones represent a current evolution issue. The urban sprawl phenomenon imposed the expansion of the city limits and outside the old built-up area, and due to the hilly terrain and geomorphology, natural hazards such as landslides and erosion processes are susceptible to appearance or reactivation. The study incorporates interdisciplinary research composed of evaluation of a landslide susceptible hotspot located in an area of interest to the municipality by means of geodetic and topographic precise measurements, combined with the use of unmanned aerial vehicles (UAV) monitoring of surface movement and GIS spatial analysis. The data obtained in a span of over two years reveal that the investigated slope is subjected to a shallow active landslide of a few centimeters per year, and based on the 64 individual placed landmarks the highest displacement value was 67 mm. Through geomatic tools the exchange rate of the slope surface was evaluated with comprehensive volume calculations, such as displacement, erosion, and accumulation that illustrate a volume of material displaced of 107.2 m³ and the accumulated one of 55.7 m³. The results provide valuable insight into the complex landslide and erosion dynamics that are crucial when predicting future movements and prevention measures.

Slope failures and landslides cause economic damage and deaths worldwide. These losses can be minimized by integrating different methodologies, instruments, and data monitoring to predict future landslides. In the constantly growing metropolitan area of Cluj-Napoca, Romania, changes in land cover, land use, and build-up areas are an issue. The unprecedented urban sprawl pushed the city limits from the Somes River to hilly terrain prone to landslides and erosion. This study focuses on a landslide-prone area where a previous slope failure caused significant economic losses. It combines topo-geodetic measurements, UAV monitoring of surface displacement, GIS spatial analysis, ground-penetrating radar investigations, and geotechnical assessment. Two years of data show that the slope is undergoing surface erosion, with soil displacements of a few centimeters. Geodetic monitoring of the retaining wall’s control points indicates a small rotation. Coupled with georadar profile imaging showing changes in soil and rock layers with an uplift trend, it was deduced that the area suffers from a global instability. The findings provide valuable information about the dynamics of landslides and erosion for forecasting future movements and developing preventative strategies based on a new methodology that combines affordable and prevalent instrumentation and techniques.

The extent of wildfires cannot be easily mapped using field-based methods in areas with complex topography, and in those areas the use of remote sensing is an alternative. This study first obtained images from the Sentinel-2 satellites for the period 2015–2020 with the objective of applying multi-temporal spectral indices to assess areas burned in wildfires and prescribed fires in the Margalla Hills of Pakistan using the Google Earth Engine (GEE). Using those images, the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR), which are often used to assess the severity of fires, were calculated for wildfires and prescribed fires. For each satellite image, spectral indices values were extracted for the 5th, 20th, 40th, 60th, 80th and 95th percentiles of pixels of each burned area. Then, boxplots representing the distribution of these values were plotted for each satellite image to identify whether the regeneration time subsequent to a fire, also known as the burn scar, and the severity of the fire differed between the autumn and summer wildfires, and with prescribed fires. A statistical test revealed no differences for the regeneration time amongst the three categories of fires, but that the severity of summer wildfires was significantly different from that of prescribed fire, and this, for both indices. Second, SAR images were obtained from the Sentinel-1 mission for the same period as that of the optical imagery. A comparison of the response of 34 SAR variables with official data on wildfires and prescribed fires from the Capital Development Authority revealed that the 95^th percentile of the Normalized Signal Ratio (NSR p_95) was found to be the best variable to detect fire events, although only 50% of the fires were correctly detected. Nonetheless, when the occurrence of fire events according to the SAR variable NSR p_95 was compared to that from the two spectral indices, the SAR variable was found to correctly identify 95% of fire events. The SAR variable NSR p_95 is thus a suitable alternative to spectral indices to monitor the progress of wildfires and assess their severity when there are limitations to the use of optical images due to cloud coverage or smoke, for instance.

In light of population growth and climate change, groundwater is one of the most important water resources globally. Groundwater is crucial for sustaining many vital sectors in Syria, including industrial and agricultural sectors. However, groundwater exploitation has significantly escalated to meet different water needs especially in the post-war period and the earthquake disaster. Therefore, the goal was this study delineation of the groundwater potential zones (GPZs) by integrating the analytic hierarchy process (AHP) method in a geographic information systems (GIS) within the AlAlqerdaha river basin in western Syria. In this study, ten criteria were used to map the spatial distribution of GPZs, including slope, geomorphology, drainage density, land use/land cover (LU/LC), lineament density, lithology, rainfall, soil, curvature and topographic wetness index (TWI). GPZs map was validated by using the location of 74 wells and the Receiver Operating Characteristic Curve (ROC). The findings suggest that the study area is divided into five GPZs: very low, 21.39 km² (10.87%); low, 52.45 km² (26.65%); moderate, 65.64 km² (33.35%); high, 40.45 km² (20.55%) and very high, 16.90 km² (8.58%). High and very high zones mainly corresponded to the western regions of the study area. The conducted spatial modeling indicated that the AHP-based GPZs map showed a remarkably acceptable correlation with wells locations (AUC = 87.7%, n = 74), demonstrating the precision of the AHP–GIS as a rating method. The results of this study provide objective and constructive outputs that can help decision-makers to optimally manage groundwater resources in the post-war phase in Syria.