Abstract

Projects focusing on spatio-temporal modelling of the living environment need to manage a wide range of terrain measurements, existing spatial data, time series, results of spatial analysis and inputs/outputs from numerical simulations. Thus, GISs are often used to manage data from remote sensors, to provide advanced spatial analysis and to integrate numerical models. In order to demonstrate the integration of spatial data, time series and methods in the framework of the GIS, we present a case study focused on the modelling of dust transport over a surface coal mining area, exploring spatial data from 3D laser scanners, GPS measurements, aerial images, time series of meteorological observations, inputs/outputs form numerical models and existing geographic resources. To achieve this, digital terrain models, layers including GPS thematic mapping, and scenes with simulation of wind flows are created to visualize and interpret coal dust transport over the mine area and a neighbouring residential zone. A temporary coal storage and sorting site, located near the residential zone, is one of the dominant sources of emissions. Using numerical simulations, the possible effects of wind flows are observed over the surface, modified by natural objects and man-made obstacles. The coal dust drifts with the wind in the direction of the residential zone and is partially deposited in this area. The simultaneous display of the digital map layers together with the location of the dominant emission source, wind flows and protected areas enables a risk assessment of the dust deposition in the area of interest to be performed. In order to obtain a more accurate simulation of wind flows over the temporary storage and sorting site, 3D laser scanning and GPS thematic mapping are used to create a more detailed digital terrain model. Thus, visualization of wind flows over the area of interest combined with 3D map layers enables the exploration of the processes of coal dust deposition at a local scale. In general, this project could be used as a template for dust-transport modelling which couples spatial data focused on the construction of digital terrain models and thematic mapping with data generated by numerical simulations based on Reynolds averaged Navier-Stokes equations.

Highlights

  • Introduction and the general approachThe impacts of mineral dust on the natural environment in the neighbourhood of surface coal mines have long been recognized

  • In order to achieve this spatio-temporal modelling of dust transport over the surface of a mining area and neighbouring residential zones, a geographic information system (GIS) is used to create spatial data structures and modelling tools

  • This study describes the extension of the capabilities for spatio-temporal analysis, with an emphasis on physically based dust transport and coupling with GIS

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Summary

Introduction and the general approach

The impacts of mineral dust on the natural environment in the neighbourhood of surface coal mines have long been recognized. Despite existing studies on the subject [1,2,3], practical numerical calculations have not been possible until recently This is because the processes governing emissions and transport by wind flows over a surface are very complex. In addition to wind flows, a set of physical processes in soils predetermines the conditions of primary dust dispersion These processes are affected by highly variable natural factors, such as climate, soil state, and surface roughness. In order to achieve this spatio-temporal modelling of dust transport over the surface of a mining area and neighbouring residential zones, a geographic information system (GIS) is used to create spatial data structures and modelling tools. In order to provide spatio-temporal modelling, a GIS database is created to manage data from 3D surface laser scanners, GPS measurements, existing thematic maps, numerical models and meteorological stations.

The main data sources for the spatio-temporal modelling
Data sources from surface laser scanning
Data sources from GPS
Data sources from meteorological stations
Emission sources
Other data sources
The GIS approach
The modelling approach
Visualization of the dust transport
Discussion and suggested future research
Conclusions

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