Drone technology opens the door to major changes and opportunities in our society. But this technology, like many others, needs to be administered and regulated to prevent potential harm to the public. Therefore, national and local governments around the world established regulations for operating drones, which bans drone use from specific locations or limits their operation to qualified drone pilots only. This study reviews the types of restrictions on drone use that are specified in federal drone regulations for the US, the UK, and France, and in state regulations for the US. The study also maps restricted areas and assesses compliance with these regulations by analyzing the spatial contribution patterns to three crowd-sourced drone portals, namely SkyPixel, Flickr, and DroneSpot, relative to restricted areas. The analysis is performed both at the national level and at the state/regional level within each of the three countries, where statistical tests are conducted to compare compliance rates between the three drone portals. This study provides new insight into drone users’ awareness of and compliance with drone regulations. This can help governments to tailor information campaigns for increased awareness of drone regulations among drone users and to determine where increased control and enforcement of drone regulations is necessary.

Since the introduction of drones to the mass market for private users, drone pilots have started to share geo-tagged aerial photos and videos on a variety of drone platforms. This study compares the spatio-temporal contribution patterns of georeferenced drone-based images and videos between three crowd-sourcing platforms, namely Dronestagram, Travelwithdrone, and Flickr. The comparison addresses aspects of spatial accuracy, geographic coverage, contribution inequality, power-law approximations of different contribution characteristics, and negative binomial multilevel regression models that identify man-made and natural features, socio-economic factors, and land use categories that are associated with image and video contribution numbers. This study provides new insight into the abundance of drone-based image and video contributions around the globe, helps to determine which drone platform is best suited to find drone media for a specific location, and discusses a few potential applications that could benefit from crowd-sourced drone imagery and videos.

This study intends to develop a GIS–AHP integrated framework to identify and analyze potential ecotourism routes between Jeddah and Alula, a corridor rich in ecological and cultural resources in Saudi Arabia. The research employed an integrated GIS and AHP methodology applying four criteria: ecological, cultural, infrastructural, and socio-economic. The AHP provided a systematic method for allocating weights to criteria through expert assessment, while GIS facilitated the spatial analysis, standardization, and integration of diverse information into a unified suitability map. The results reveal considerable regional heterogeneity in ecotourism suitability along the corridor. Highland areas near Alula and Al-Madinah showed high suitability due to the favorable climate, vegetation, and scenic aspects, while arid interior zones were mostly low-suited. The regions surrounding Jeddah, Yanbu, and Alula prospered from significant cultural and infrastructural accessibility. Overall, 21.4% of the land and 19.6% of road parts were categorized as highly appropriate for ecotourism. The integrated model indicates that ecotourism route planning can be enhanced by integrating environmental sensitivity with infrastructural availability. The findings expand the theoretical and practical discussion on spatial decision-making in sustainable tourism, offering a comprehensive, reliable approach for identifying potential ecotourism routes.

Designing sustainable pedestrian infrastructure in hyper-arid cultural landscapes requires balancing visitor experience, heritage protection, and environmental constraints. This study develops a statistically grounded model for planning sustainable walking trails in Al-Ula, Saudi Arabia, using multi-spectral remote sensing data integrated with expert-based evaluation. A GIS-based Multi-Criteria Decision-Making (MCDM) framework was applied to assess topographic slope, vegetation cover (NDVI), built-up density (NDBI), Land Surface Temperature (LST), and solar exposure. Indicator weights were validated through a three-round Delphi survey involving fifteen experts. The results indicate strong consensus among experts, identifying LST (21%) and slope (20%) as the most influential determinants of trail suitability in desert environments. These findings highlight the critical role of thermal stress in shaping safe and sustainable pedestrian mobility in hot climates. The optimized 44.5 km trail network, classified into three difficulty levels, improves energetic efficiency by reducing caloric expenditure by 24% compared to conventional routing. In addition, the proposed network has the potential to reduce carbon emissions associated with heritage-related travel by approximately 75% through modal shift from vehicles to walking. The framework provides a practical decision-support tool for planners seeking to develop low-carbon, climate-responsive tourism infrastructure aligned with the objectives of Saudi Arabia’s Vision 2030.

Mangrove ecosystems provide critical coastal protection, biodiversity support, and carbon storage, yet they remain vulnerable to degradation caused by coastal development, pollution, and climate-related pressures. This study monitors mangrove dynamics in Al-Birk, Asir Region, Saudi Arabia, using Google Earth Engine (GEE), multi-temporal Landsat imagery, spectral indices, and Random Forest (RF) classification. Landsat imagery from 2016 to 2021 was processed to derive NDVI, MSAVI2, EVI, and NDWI, and supervised RF classification was applied to map annual mangrove extent and associated land-cover classes. The RF classifier achieved an overall accuracy of 92.5% and a Kappa coefficient of 0.89. Results indicate that classified mangrove extent increased from approximately 1069 ha in 2016 to 1540 ha in 2021, representing a net gain of 471 ha and a 44% increase over the study period. A localized decline was detected between 2020 and 2021, indicating spatially uneven vegetation dynamics. The findings provide a spatial baseline for monitoring mangrove change and supporting coastal conservation planning in Saudi Arabia. While the detected expansion is temporally consistent with ongoing restoration initiatives, the study does not establish direct causality between policy interventions and observed spatial changes.