The proposed methodology integrates Geographic Information System (GIS) data, incorporating a Digital Surface Model (DSM) to spatially represent relevant factors. The dominant site-selection criteria were identified and weighted according to their scientific and strategic importance in collaboration with the ET scientific community. An interactive parametric model was developed to interface directly with the GIS data, enabling evaluation of key factors and providing real-time analytical feedback on placement scenarios. Using an evolutionary algorithm combined with a composite fitness function, the system balances competing objectives and delivers optimised solutions, offering a robust decision-support tool for the early planning stages of the Einstein Telescope project.
Although the Sardinia site is currently considered a preliminary case study, the methodology is generalisable and applicable to other candidate sites to host ET.]]>
To address this gap, this study proposes the construction of an standardized, efficient and reusable foundational database system consisting of three key components: image control point database, interpretation sample database, and spectral information database. The image control point database establishes a unified geometric reference for multi-source data; The interpretation sample database provides large-scale, high-quality labeled data for deep learning-based image analysis; and the spectral database offers standardized spectral features for accurate classification and parameter inversion.
Together, the three databases form a collaborative mechanism that links geometric accuracy, semantic understanding, and spectral consistency, thereby building a complete chain from analysis-ready data (ARD) production to rapid information extraction. Using Shanghai as a case study, this paper presents the design, construction, and collaborate applications of the three databases, demonstrating their effectiveness in supporting refined and sustainable megacity governance.]]>
For the forest features, the process comprised optical point cloud filtration and constrained Delaunay triangulation, resulting in height-extruded forest base polygons with canopy cover tops. The 3D representation uses MultiSurface geometry, recorded as a PlantCover object in CityGML/3DCityDB, and is in line with the LoD2 standard for buildings. For solitary trees, predefined prototypes were scaled and positioned based on individual tree detection and parameters extracted from point clouds. Features were mapped to the CityGML/3DCityDB SolitaryVegetationObjects class, utilizing Implicit geometry to optimize for data volume and visualization speed. While the digital surface model, generated from periodically acquired optical imagery, was sufficient for the forest features, aerial laser scanning data was superior in individual tree modelling. The number of extractable parameters increases with point density and is dependent on the platform used. However, the availability of such higher-density laser scanning data in Europe is limited and varies across countries and regions. The results demonstrate the generation of LoD2 compliant 3D models from nationwide datasets for both vegetation feature types, visually enriching the basic built environment model.]]>
https://github.com/ROAMer-Geo/Web]]>The PEARL findings informed the identification and characterization of local dust events over other parts of the CAA using a suite of satellite instruments whose remote sensing (RS) capabilities were complementary to or an extension of the ground- and satellite-based techniques employed at Eureka. The events included plumes emanating from Axel Heiberg Island, just west of Ellesmere Island, Banks Island in the southwest corner of the CAA, Ellef Ringnes Island in the eastern part of the central CAA and Prince of Wales Island/Victoria Island in the central southern CAA. Plume identification, plume source and CM (coarse mode) aerosol optical depth (AOD) retrievals were investigated using a combination of low to high spatial resolution (MODIS to Sentinel-2) color imagery and the MODIS dark target AOD product over water. Plume thickness, height and speed for most of the events were obtained (depending on orbit availability and lack of cloud contamination) from MISR (Multi-angle Imaging Spectro Radiometer) stereoscopic products.
These RS results support an argument for the ubiquitous presence of pan-Arctic, low altitude dust that is typically (away from any strong sources such as mountainous drainage basins) at the lower levels of detectability offered by ground- and satellite-based RS techniques. The ability to RS airborne, near-source, local dust events and characterize dust properties and dynamics of important regions such as the CAA is critical to understanding local dust impacts such as early snow/ice melt and the nucleation role of local dust in the formation of low-altitude clouds.
]]>Our analysis confirms that TCO declined across all datasets before 2000. The annual mean decreased at a rate of 2 Dobson units per year (DU yr−1), while more pronounced decreases of approximately 6 DU yr−1 occurred in September and October. For the 2001–2019 period, TCO showed signs of recovery in the annual mean (0.5 DU yr−1) and September (1.5 DU yr−1), while the annual trend shifted to −0.4 DU yr−1 and September trend was near zero over the extended 2001–2023 period. The MLR effectively captures long-term ozone changes as well as unusual dynamical events such as the sudden stratospheric warmings in 2002 and 2019. Annual mean and springtime (September/October) TCO exhibited a positive correlation with the estimated BDC contribution throughout the 2001–2023 period. As dynamical proxies show the largest influence, we use TOMCAT simulations to illustrate the impact of the BDC on the Antarctic ozone. Two sensitivity simulations further demonstrate that the strengthening (weakening) of the circulation leads to high (low) ozone values in spring. Cold temperatures and abnormal BDC in 2021–2022 resulted in low ozone levels. These findings suggest that now ozone-depleting substances have been effectively controlled, dynamical processes are playing an increasingly important role in controlling the ozone recovery patterns in Antarctica.
]]>Dynamically, dissipation is characterized by weakening of the coherent large-scale circulations and an increasing relative contribution of small-scale turbulence. In non-precipitating polluted clouds, continued upward transport of moist air from cloud base allows lower-cloud updrafts to persist even as the upper cloud decays. In contrast, in precipitating clean clouds, rain formation strengthens downdrafts. The microphysical evolution also depends strongly on aerosol loading: clean precipitating clouds exhibit rapid depletion of small droplets and growth of large drops, whereas polluted non-precipitating clouds undergo weaker temporal changes. Dissipation also leaves a clear imprint on the cloud's surrounding environment. Enstrophy increases outside the cloud, indicating enhanced vorticity near the cloud–environment interface that extends outward through detrainment. A humid halo develops and expands around the cloud, exhibiting oscillatory behavior in both precipitating and non-precipitating cases.
Overall, our results show that shallow-cumulus dissipation is a distinct and prolonged stage involving coupled changes in cloud dynamics, microphysics, turbulence, and the near-cloud environment. Therefore, dissipation should be explicitly considered when interpreting instantaneous observations and representing shallow convection in models.]]>