Understanding the behavior of urban air pollution is important en route for sustainable urban development (SUD). Malaysia is on its mission to be a developed country by year 2020 comprehends dealing with air pollution...Understanding the behavior of urban air pollution is important en route for sustainable urban development (SUD). Malaysia is on its mission to be a developed country by year 2020 comprehends dealing with air pollution is one of the indicators headed towards it. At present monitoring and managing air pollution in urban areas encompasses sophisticated air quality modeling and data acquisition. However, rapid developments in major cities cause difficulties in acquiring the city geometries. The existing method in acquiring city geometries data via ground or space measurement inspection such as field survey, photogrammetry, laser scanning, remote sensing or using architectural plans appears not to be practical because of its cost and efforts. Moreover, air monitoring stations deployed are intended for regional to global scale model whereby it is not accurate for urban areas with typical resolution of less than 2 km. Furthermore in urban areas, the pollutant dispersion movements are trapped between buildings initiating it to move vertically causing visualization complications which imply the limitations of existing visualization scheme that is based on two-dimensional (2D) framework. Therefore this paper aims is to perform groundwork assessment and discuss on the current scenario in Malaysia in the aspect of current policies towards SUD, air quality monitoring stations, scale model and detail discussion on air pollution dispersion model used called the Operational Street Pollution Model (OSPM). This research proposed the implementation of three-dimensional (3D) spatial city model as a new physical data input for OSPM. The five Level of Details (LOD) of 3D spatial city model shows the scale applicability for the dispersion model implementtation. Subsequently 3D spatial city model data commonly available on the web, by having a unified data model shows the advantages in easy data acquisition, 3D visualization of air pollution dispersion and improves visual analysis of air quality monitoring in urban areas.展开更多
Alpine regions face severe flood management challenges due to complex terrain,climate extremes,and sparse data.This commentary critiques limitations in current hydrological practices supporting China's Four-pre st...Alpine regions face severe flood management challenges due to complex terrain,climate extremes,and sparse data.This commentary critiques limitations in current hydrological practices supporting China's Four-pre strategy.Key barriers include poor data quality,model limitations,and fragmented systems.Thus,we recommend optimizing observation networks,using physicsinformed neural networks,and establishing unified data platforms.This integrated approach will enhance flood modeling reliability in data-scarce regions,providing actionable insights for adaptive flood governance in high-risk mountainous regions.展开更多
基金Major funding for this research was provided by the Ministry of Higher Education Malaysia and partially funded by the Land Surveyors Board of Malaysia.
文摘Understanding the behavior of urban air pollution is important en route for sustainable urban development (SUD). Malaysia is on its mission to be a developed country by year 2020 comprehends dealing with air pollution is one of the indicators headed towards it. At present monitoring and managing air pollution in urban areas encompasses sophisticated air quality modeling and data acquisition. However, rapid developments in major cities cause difficulties in acquiring the city geometries. The existing method in acquiring city geometries data via ground or space measurement inspection such as field survey, photogrammetry, laser scanning, remote sensing or using architectural plans appears not to be practical because of its cost and efforts. Moreover, air monitoring stations deployed are intended for regional to global scale model whereby it is not accurate for urban areas with typical resolution of less than 2 km. Furthermore in urban areas, the pollutant dispersion movements are trapped between buildings initiating it to move vertically causing visualization complications which imply the limitations of existing visualization scheme that is based on two-dimensional (2D) framework. Therefore this paper aims is to perform groundwork assessment and discuss on the current scenario in Malaysia in the aspect of current policies towards SUD, air quality monitoring stations, scale model and detail discussion on air pollution dispersion model used called the Operational Street Pollution Model (OSPM). This research proposed the implementation of three-dimensional (3D) spatial city model as a new physical data input for OSPM. The five Level of Details (LOD) of 3D spatial city model shows the scale applicability for the dispersion model implementtation. Subsequently 3D spatial city model data commonly available on the web, by having a unified data model shows the advantages in easy data acquisition, 3D visualization of air pollution dispersion and improves visual analysis of air quality monitoring in urban areas.
基金the Science and Technology Projects of Xizang Autonomous Region(XZ202501ZY0145)Natural Science Foundation Youth Project of the Science and Technology Department of Sichuan Province(2024NSFSC0984)China Yangtze Power Co.Ltd(Z242302038).
文摘Alpine regions face severe flood management challenges due to complex terrain,climate extremes,and sparse data.This commentary critiques limitations in current hydrological practices supporting China's Four-pre strategy.Key barriers include poor data quality,model limitations,and fragmented systems.Thus,we recommend optimizing observation networks,using physicsinformed neural networks,and establishing unified data platforms.This integrated approach will enhance flood modeling reliability in data-scarce regions,providing actionable insights for adaptive flood governance in high-risk mountainous regions.
