To enhance the understanding of aeolian landforms and their processes, the assessment of origin, migration and evolution of newly-born sand dunes is vital. In this regard, Lake Urmia, in NW Iran, was considered as a representative case study, given that it has lost approximately two-thirds of its water volume in the past two decades and, consequently, the newly-born sand ridges and sand dunes on its western shores were formed. The emerging sand dunes are located close to the villages, adjacent to the agricultural and farmlands, international transit road, and industrial zone, encompassing the whole area. The present study aims to assess the sand dunes’ origin and their migration both in speed and direction in the past decade.To understand the questions above, remote sensing techniques and in-field studies were coupled. Therefore, wind data from the closest meteorological station were employed to calculate the wind rose, drift potential (DP), the resultant drift potential (RDP), and the resultant drift direction (RDD) across the region. Change detection techniques using high-resolution satellite images were chosen to detect the migration rate and morpho-dynamic changes of Lake Urmia sand dunes. To classify the geomorphological features and land uses in the region, a hybrid supervised classification approach including a customised decision tree classifier was used to distinguish sand dune units from other signatures. Using the minimum bounding geometry method, feature classes were created. These feature classes represent the length, width, and orientation of sand dunes, retrieved after the image classification process. Also, fieldwork surveying was carried out on the sixteen sand dunes in different periods to measure the morphological and evolutionary changes. As the wind results show, the trend of DP parameters between the years 2006-2009 and the years 2015-2020, the percentage of wind speeds above the threshold velocity (V>Vt%) to DP has significant gaps, suggestive of weaker winds in those periods. However, between the years 2009-2015, the V>Vt% and DP values are corresponding and coequal. This indicates that the most erosive and shifting winds are between 2009-2015, with the weakest wind power in tails. Moreover, the annual variability of DPt is well correlated with Lake Urmia water level changes; but there is no correlation between the DPt and precipitation amount. The evaluation of image processing results depicted that after 2003, the area of sand dunes had dramatically increased. On average, the smallest area belongs to 2010 (287.3 m2), and the largest area is for years 2019 (775.96 m2), 2018 (739.08 m2), and 2017 (739.74 m2). In addition, between the years 2010 and 2014, a significant increase in area of the sand dunes from 287.25 to 662.8 m2 was observed. The migration rate is the highest between 2010 and 2015, with the lowest values before 2010 and after 2015.The results of this study have broad implications in the context of sustainable development and climate-related challenges, ecosystem management and policy-making for regions with sand dune challenges, hence crucial insights can be gained by coupling remote sensing techniques and in-situ studies.

Aeolian sand hazards severely constrain highway safety and operation in arid regions. To support targeted mitigation along Highway S315 in the Gobi Desert of northern China, this study integrates meteorological observations with sand removal records to quantify wind regimes and classify sand hazard intensity. Event thresholds were objectively identified using change points in semi-logarithmic distributions of daily sand removal volumes, and spatial hazard severity was graded based on annual sand removal per unit road length. The results showed that (1) the study area was subject to intense aeolian activity, with a mean annual sand-driving wind frequency of 23.98%, an annual drift potential of 344.91 vector units (VU), and a resultant sand transport direction of 129.88° (east–southeast). (2) Based on inflection point characteristics, sand hazard events were classified into three intensity levels, namely, slight (3000 m³), accounting for 13.0%, 76.1%, and 10.9% of all events along Highway S315, respectively. (3) Spatial grading criteria for sand hazard severity were defined as slight (1.0 × 10⁴ m³ km⁻¹ yr⁻¹). Application of these criteria to a representative road section (K9+000–K30+600; 21.6 km) indicated that severe, moderate, and slight sand hazard segments extend over 6.0 km, 9.1 km, and 6.5 km, respectively, thereby delineating priority zones for targeted mitigation measures. This study proposes a quantitative framework that couples regional wind-driven sand dynamics with highway hazard severity, enabling targeted mitigation and offering a transferable reference for sand risk management in arid and desert regions.