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
Three-dimensional technologies have matured over the years.At the same time,3D information is becoming increasingly important in many applications.Still it is not straightforward to apply the solutions that work on pr...Three-dimensional technologies have matured over the years.At the same time,3D information is becoming increasingly important in many applications.Still it is not straightforward to apply the solutions that work on prototypes,small areas or for specific projects to 3D modeling of a whole nation.In the Netherlands,two initiatives are ongoing to address the issues of nation-wide 3D modeling.First,the initiative that aims at establishing and implementing a national 3D standard for large-scale topography with support of all stakeholders.Collecting and maintaining the large-scale data are the responsibility of local governments(mainly municipalities).The second initiative is led by the Kadaster(the organization responsible for topographic mapping in the Netherlands)and aims at automatically generating a 3D version of the 1:10 k object-oriented data-set based on a smart combination of the two-dimensional data with high-resolution laser data.Both initiatives are presented in this paper including results,open issues,and future plans.展开更多
Geographic information has become central for data scientists of many disciplines to put their analyzes into a spatio-temporal perspective.However,just as the volume and variety of data sources on the Web grow,it beco...Geographic information has become central for data scientists of many disciplines to put their analyzes into a spatio-temporal perspective.However,just as the volume and variety of data sources on the Web grow,it becomes increasingly harder for analysts to be familiar with all the available geospatial tools,including toolboxes in Geographic Information Systems(GIS),R packages,and Python modules.Even though the semantics of the questions answered by these tools can be broadly shared,tools and data sources are still divided by syntax and platform-specific technicalities.It would,therefore,be hugely beneficial for information science if analysts could simply ask questions in generic and familiar terms to obtain the tools and data necessary to answer them.In this article,we systematically investigate the analytic questions that lie behind a range of common GIS tools,and we propose a semantic framework to match analytic questions and tools that are capable of answering them.To support the matching process,we define a tractable subset of SPARQL,the query language of the Semantic Web,and we propose and test an algorithm for computing query containment.We illustrate the identification of tools to answer user questions on a set of common user requests.展开更多
Information on Earth’s land surface cover is commonly obtained through digital image analysis of data acquired from remote sensing sensors.In this study,we evaluated the use of diverse classification techniques in di...Information on Earth’s land surface cover is commonly obtained through digital image analysis of data acquired from remote sensing sensors.In this study,we evaluated the use of diverse classification techniques in discriminating land use/cover types in a typical Mediterranean setting using Hyperion imagery.For this purpose,the spectral angle mapper(SAM),the object-based and the non-linear spectral unmixing based on artificial neural networks(ANNs)techniques were applied.A further objective had been to investigate the effect of two approaches for training sites selection in the SAM classification,namely of the pixel purity index(PPI)and of the direct selection of training points from the Hyperion imagery assisted by a QuickBird imagery and field-based training sites.Objectbased classification outperformed the other techniques with an overall accuracy of 83%.Sub-pixel classification based on the ANN showed an overall accuracy of 52%,very close to that of SAM(48%).SAM applied using the training sites selected directly from the Hyperion imagery supported by the QuickBird image and the field visits returned an increase accuracy by 16%.Yet,all techniques appeared to suffer from the relatively low spatial resolution of the Hyperion imagery,which affected the spectral separation among the land use/cover classes.展开更多
Holistic understanding of wind behaviour over space,time and height is essential for harvesting wind energy application.This study presents a novel approach for mapping frequent wind profile patterns using multidimen...Holistic understanding of wind behaviour over space,time and height is essential for harvesting wind energy application.This study presents a novel approach for mapping frequent wind profile patterns using multidimensional sequential pattern mining(MDSPM).This study is illustrated with a time series of 24 years of European Centre for Medium-Range Weather Forecasts European Reanalysis-Interim gridded(0.125°×0.125°)wind data for the Netherlands every 6 h and at six height levels.The wind data were first transformed into two spatio-temporal sequence databases(for speed and direction,respectively).Then,the Linear time Closed Itemset Miner Sequence algorithm was used to extract the multidimensional sequential patterns,which were then visualized using a 3D wind rose,a circular histogram and a geographical map.These patterns were further analysed to determine their wind shear coefficients and turbulence intensities as well as their spatial overlap with current areas with wind turbines.Our analysis identified four frequent wind profile patterns.One of them highly suitable to harvest wind energy at a height of 128 m and 68.97%of the geographical area covered by this pattern already contains wind turbines.This study shows that the proposed approach is capable of efficiently extracting meaningful patterns from complex spatio-temporal datasets.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This research is supported by the Dutch Technology Foundation STW,which is part of the Netherlands Organization for Scientific Research(NWO),and which is partly funded by the Ministry of Economic Affairs(project code:11300).
文摘Three-dimensional technologies have matured over the years.At the same time,3D information is becoming increasingly important in many applications.Still it is not straightforward to apply the solutions that work on prototypes,small areas or for specific projects to 3D modeling of a whole nation.In the Netherlands,two initiatives are ongoing to address the issues of nation-wide 3D modeling.First,the initiative that aims at establishing and implementing a national 3D standard for large-scale topography with support of all stakeholders.Collecting and maintaining the large-scale data are the responsibility of local governments(mainly municipalities).The second initiative is led by the Kadaster(the organization responsible for topographic mapping in the Netherlands)and aims at automatically generating a 3D version of the 1:10 k object-oriented data-set based on a smart combination of the two-dimensional data with high-resolution laser data.Both initiatives are presented in this paper including results,open issues,and future plans.
文摘Geographic information has become central for data scientists of many disciplines to put their analyzes into a spatio-temporal perspective.However,just as the volume and variety of data sources on the Web grow,it becomes increasingly harder for analysts to be familiar with all the available geospatial tools,including toolboxes in Geographic Information Systems(GIS),R packages,and Python modules.Even though the semantics of the questions answered by these tools can be broadly shared,tools and data sources are still divided by syntax and platform-specific technicalities.It would,therefore,be hugely beneficial for information science if analysts could simply ask questions in generic and familiar terms to obtain the tools and data necessary to answer them.In this article,we systematically investigate the analytic questions that lie behind a range of common GIS tools,and we propose a semantic framework to match analytic questions and tools that are capable of answering them.To support the matching process,we define a tractable subset of SPARQL,the query language of the Semantic Web,and we propose and test an algorithm for computing query containment.We illustrate the identification of tools to answer user questions on a set of common user requests.
文摘Information on Earth’s land surface cover is commonly obtained through digital image analysis of data acquired from remote sensing sensors.In this study,we evaluated the use of diverse classification techniques in discriminating land use/cover types in a typical Mediterranean setting using Hyperion imagery.For this purpose,the spectral angle mapper(SAM),the object-based and the non-linear spectral unmixing based on artificial neural networks(ANNs)techniques were applied.A further objective had been to investigate the effect of two approaches for training sites selection in the SAM classification,namely of the pixel purity index(PPI)and of the direct selection of training points from the Hyperion imagery assisted by a QuickBird imagery and field-based training sites.Objectbased classification outperformed the other techniques with an overall accuracy of 83%.Sub-pixel classification based on the ANN showed an overall accuracy of 52%,very close to that of SAM(48%).SAM applied using the training sites selected directly from the Hyperion imagery supported by the QuickBird image and the field visits returned an increase accuracy by 16%.Yet,all techniques appeared to suffer from the relatively low spatial resolution of the Hyperion imagery,which affected the spectral separation among the land use/cover classes.
基金This work was supported by the Malaysian Ministry of Education(SLAI)and Universiti Teknologi Malaysia(UTM).
文摘Holistic understanding of wind behaviour over space,time and height is essential for harvesting wind energy application.This study presents a novel approach for mapping frequent wind profile patterns using multidimensional sequential pattern mining(MDSPM).This study is illustrated with a time series of 24 years of European Centre for Medium-Range Weather Forecasts European Reanalysis-Interim gridded(0.125°×0.125°)wind data for the Netherlands every 6 h and at six height levels.The wind data were first transformed into two spatio-temporal sequence databases(for speed and direction,respectively).Then,the Linear time Closed Itemset Miner Sequence algorithm was used to extract the multidimensional sequential patterns,which were then visualized using a 3D wind rose,a circular histogram and a geographical map.These patterns were further analysed to determine their wind shear coefficients and turbulence intensities as well as their spatial overlap with current areas with wind turbines.Our analysis identified four frequent wind profile patterns.One of them highly suitable to harvest wind energy at a height of 128 m and 68.97%of the geographical area covered by this pattern already contains wind turbines.This study shows that the proposed approach is capable of efficiently extracting meaningful patterns from complex spatio-temporal datasets.
