Current Search: Geographic information systems -- Mathematical models (x)
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- Title
- Assessment of Changes in Precipitation Data Characteristics due to Infilling by Spatially Interpolated Estimates.
- Creator
- Hachmi, Mohammad, Teegavarapu, Ramesh, Florida Atlantic University, College of Engineering and Computer Science, Department of Civil, Environmental and Geomatics Engineering
- Abstract/Description
-
Spatial and temporal interpolation methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these interpolation methods have not been comprehensively checked for their ability to preserve time series characteristics. Assessing the preservation of time series characteristics helps achieving a threshold criteria of length of gaps in a data set that is acceptable to be filled. This study evaluates the efficacy...
Show moreSpatial and temporal interpolation methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these interpolation methods have not been comprehensively checked for their ability to preserve time series characteristics. Assessing the preservation of time series characteristics helps achieving a threshold criteria of length of gaps in a data set that is acceptable to be filled. This study evaluates the efficacy of optimal weighting interpolation for estimation of missing data in preserving time series characteristics. Rain gauges in the state of Kentucky are used as a case study. Several model performance measures are also evaluated to validate the filling model; followed by time series characteristics to evaluate the accuracy of estimation and preservation of precipitation data characteristics. This study resulted in a definition of region-specific threshold of the maximum length of gaps allowed in a data set at five percent.
Show less - Date Issued
- 2016
- PURL
- http://purl.flvc.org/fau/fd/FA00004783, http://purl.flvc.org/fau/fd/FA00004783
- Subject Headings
- Precipitation (Meteorology), Spatial analysis (Statistics), Geographic information systems--Mathematical models., Climatic changes--Environmental aspects., Functions of real variables.
- Format
- Document (PDF)
- Title
- Statistics preserving spatial interpolation methods for missing precipitation data.
- Creator
- El Sharif, Husayn., College of Engineering and Computer Science, Department of Civil, Environmental and Geomatics Engineering
- Abstract/Description
-
Deterministic and stochastic weighting methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these spatial interpolation methods seldom check for their ability to preserve site and regional statistics. Such statistics and primarily defined by spatial correlations and other site-to-site statistics in a region. Preservation of site and regional statistics represents a means of assessing the validity of...
Show moreDeterministic and stochastic weighting methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these spatial interpolation methods seldom check for their ability to preserve site and regional statistics. Such statistics and primarily defined by spatial correlations and other site-to-site statistics in a region. Preservation of site and regional statistics represents a means of assessing the validity of missing precipitation estimates at a site. This study evaluates the efficacy of traditional interpolation methods for estimation of missing data in preserving site and regional statistics. New optimal spatial interpolation methods intended to preserve these statistics are also proposed and evaluated in this study. Rain gauge sites in the state of Kentucky are used as a case study, and several error and performance measures are used to evaluate the trade-offs in accuracy of estimation and preservation of site and regional statistics.
Show less - Date Issued
- 2012
- PURL
- http://purl.flvc.org/FAU/3355568
- Subject Headings
- Numerical analysis, Meteorology, Statistical methods, Spatial analysis (Statistics), Data processing, Atmospheric physics, Statistical methods, Geographic information systems, Mathematical models
- Format
- Document (PDF)
- Title
- A GIS approach to linking spatial patterns and trip generation/trip distribution modeling.
- Creator
- Harris, David Michael., Florida Atlantic University, Shaw, Shih-Lung, Charles E. Schmidt College of Science, Department of Geosciences
- Abstract/Description
-
Geographic information systems (GIS) have been increasingly used in urban transportation planning and modeling. One key advantage of GIS is its ability to integrate and analyze various kinds of geographically referenced data. Modeling and analysis tools used to predict travel patterns should be shaped by changes in spatial organization that are currently taking place. Utilizing the detailed data made available by GIS, this study investigates the potential improvements offered to the...
Show moreGeographic information systems (GIS) have been increasingly used in urban transportation planning and modeling. One key advantage of GIS is its ability to integrate and analyze various kinds of geographically referenced data. Modeling and analysis tools used to predict travel patterns should be shaped by changes in spatial organization that are currently taking place. Utilizing the detailed data made available by GIS, this study investigates the potential improvements offered to the conventional trip generation and trip distribution models by explicitly referencing the spatial land use and street network patterns within traffic analysis zones (TAZs).
Show less - Date Issued
- 1995
- PURL
- http://purl.flvc.org/fcla/dt/15174
- Subject Headings
- Geographic information systems, Spatial analysis (Statistics)--Data processing, Urban transportation--United States--Mathematical models
- Format
- Document (PDF)
- Title
- Data Fusion of LiDAR and Aerial Imagery to Map the Campus of Florida Atlantic University.
- Creator
- Gamboa, Nicole, Zhang, Caiyun, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Geosciences
- Abstract/Description
-
Reliable geographic intelligence is essential for urban areas; land-cover classification creates the data for urban spatial decision making. This research tested a methodology to create a land-cover map for the main campus of Florida Atlantic University in Boca Raton, Florida. The accuracy of nine separate land-cover classification results were tested; the one with the highest accuracy was chosen for the final map. Object-based image segmentation was applied to fused and LiDAR point cloud ...
Show moreReliable geographic intelligence is essential for urban areas; land-cover classification creates the data for urban spatial decision making. This research tested a methodology to create a land-cover map for the main campus of Florida Atlantic University in Boca Raton, Florida. The accuracy of nine separate land-cover classification results were tested; the one with the highest accuracy was chosen for the final map. Object-based image segmentation was applied to fused and LiDAR point cloud (elevation and intensity) data and aerial imagery. These were classified by Random Forest, k-Nearest Neighbor and Support Vector Machines classifiers. Shadow features were reclassified hierarchically in order to create a complete map. The Random Forest classifier used with the fused data set gave the highest overall accuracy at 82.3%, and a Kappa value at 0.77. When combined with the results from the shadow reclassification, the overall accuracy increased to 86.3% and the Kappa value improved to 0.82.
Show less - Date Issued
- 2016
- PURL
- http://purl.flvc.org/fau/fd/FA00004595, http://purl.flvc.org/fau/fd/FA00004595
- Subject Headings
- Spatial analysis (Statistics), Geographic information systems., Cartography--Remote sensing., Thematic maps., Geospatial data--Mathematical models., Criminal justice, Administration of., African Americans, Violence against.
- Format
- Document (PDF)