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INTEGRATING GEOSPATIAL ANALYSIS AND TRAFFIC SIMULATION TO MODEL FLOOD IMPACTS IN RURAL AREAS
Title
INTEGRATING GEOSPATIAL ANALYSIS AND TRAFFIC SIMULATION TO MODEL FLOOD IMPACTS IN RURAL AREAS.
Creator
Reginato, Attilio Junior, Kaisar, Evangelos I., Florida Atlantic University, Department of Civil, Environmental and Geomatics Engineering, College of Engineering and Computer Science
Abstract/Description
This study aims to address the unique challenges of transportation in rural and disconnected communities through innovative data-driven methodologies. The primary methods employed in this research involve Geographic Information Systems (GIS) tools and simulation techniques to model and assess the impact of flood zones on rural traffic dynamics. The study recognizes the distinct mobility patterns and limited infrastructure prevalent in rural areas, emphasizing the need for tailored solutions...
Show moreThis study aims to address the unique challenges of transportation in rural and disconnected communities through innovative data-driven methodologies. The primary methods employed in this research involve Geographic Information Systems (GIS) tools and simulation techniques to model and assess the impact of flood zones on rural traffic dynamics. The study recognizes the distinct mobility patterns and limited infrastructure prevalent in rural areas, emphasizing the need for tailored solutions to manage flood-induced disruptions. By leveraging GIS tools, the study intends to spatially analyze existing transportation networks, population distribution, flood-prone areas, and key points of interest to formulate a comprehensive understanding of the local context. Simulation-based approaches using the PTV VISSIM platform will be employed to model and assess various flood scenarios and their effects on traffic flow and accessibility. This study’s outcomes aim to contribute valuable insights into improving accessibility, efficiency, and safety in transportation for these underserved areas during flood events. By combining GIS tools and simulation techniques, this research seeks to provide a robust framework for data-driven decision-making and policy formulation in the realm of rural and disconnected community mobility, particularly in the context of flood risks.
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Date Issued
2024
PURL
http://purl.flvc.org/fau/fd/FA00014472
Subject Headings
Rural transportation, Geospatial data, Floods, Urban planning
Format
Document (PDF)
Development of a Mobile Mapping System for Road Corridor Mapping
Title
Development of a Mobile Mapping System for Road Corridor Mapping.
Creator
Sairam, Nivedita, Nagarajan, Sudhagar, Florida Atlantic University, College of Engineering and Computer Science, Department of Civil, Environmental and Geomatics Engineering
Abstract/Description
In any infrastructure project, managing the built assets is an important task. In the case of transportation asset inventories, a significant cost and effort is spent on recording and storing the asset information. In order to reduce the time and cost involved in road corridor mapping, this paper proposes a low cost MMS (Mobile Mapping System) using an equipped laser scanner and cameras. The process of building the MMS, components and sensors involved and calibration procedures are discussed....
Show moreIn any infrastructure project, managing the built assets is an important task. In the case of transportation asset inventories, a significant cost and effort is spent on recording and storing the asset information. In order to reduce the time and cost involved in road corridor mapping, this paper proposes a low cost MMS (Mobile Mapping System) using an equipped laser scanner and cameras. The process of building the MMS, components and sensors involved and calibration procedures are discussed. The efficiency of this Mobile Mapping System is experimented by mounting it on a truck and golf cart. The paper also provides a framework to extract road assets both automatically and manually using stateof- the-art techniques. The efficiency of this method is compared with traditional field survey methods. Quality of collected data, data integrity and process flow are experimented with a sample asset management framework and a spatial database structure for mapping road corridor features.
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Date Issued
2016
PURL
http://purl.flvc.org/fau/fd/FA00004629, http://purl.flvc.org/fau/fd/FA00004629
Subject Headings
Transportation engineering., Electronics in engineering., Geographic information systems--Software., Internetworking (Telecommuniation), Geospatial data.
Format
Document (PDF)
Data Fusion of LiDAR and Aerial Imagery to Map the Campus of Florida Atlantic University
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.
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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)
Salinity Assessment, Change, and Impact on Plant Stress / Canopy Water Content (CWC) in Florida Bay using Remote Sensing and GIS
Title
Salinity Assessment, Change, and Impact on Plant Stress / Canopy Water Content (CWC) in Florida Bay using Remote Sensing and GIS.
Creator
Selch, Donna, Zhang, Caiyun, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Geosciences
Abstract/Description
Human activities in the past century have caused a variety of environmental problems in South Florida. In 2000, Congress authorized the Comprehensive Everglades Restoration Plan (CERP), a $10.5-billion mission to restore the South Florida ecosystem. Environmental projects in CERP require salinity monitoring in Florida Bay to provide measures of the effects of restoration on the Everglades ecosystem. However current salinity monitoring cannot cover large areas and is costly, time-consuming,...
Show moreHuman activities in the past century have caused a variety of environmental problems in South Florida. In 2000, Congress authorized the Comprehensive Everglades Restoration Plan (CERP), a $10.5-billion mission to restore the South Florida ecosystem. Environmental projects in CERP require salinity monitoring in Florida Bay to provide measures of the effects of restoration on the Everglades ecosystem. However current salinity monitoring cannot cover large areas and is costly, time-consuming, and laborintensive. The purpose of this dissertation is to model salinity, detect salinity changes, and evaluate the impact of salinity in Florida Bay using remote sensing and geospatial information sciences (GIS) techniques. The specific objectives are to: 1) examine the capability of Landsat multispectral imagery for salinity modeling and monitoring; 2) detect salinity changes by building a series of salinity maps using archived Landsat images; and 3) assess the capability of spectroscopy techniques in characterizing plant stress / canopy water content (CWC) with varying salinity, sea level rise (SLR), and nutrient levels. Geographic weighted regression (GWR) models created using the first three imagery components with atmospheric and sun glint corrections proved to be more correlated (R^2 = 0.458) to salinity data versus ordinary least squares (OLS) regression models (R^2 = 0.158) and therefore GWR was the ideal regression model for continued Florida Bay salinity assessment. J. roemerianus was also examined to assess the coastal Everglades where salinity modeling is important to the water-land interface. Multivariate greenhouse studies determined the impact of nutrients to be inconsequential but increases in salinity and sea level rise both negatively affected J. roemerianus. Field spectroscopic data was then used to ascertain correlations between CWC and reflectance spectra using spectral indices and derivative analysis. It was determined that established spectral indices (max R^2 = 0.195) and continuum removal (max R^2= 0.331) were not significantly correlated to CWC but derivative analysis showed a higher correlation (R^2 = 0.515 using the first derivative at 948.5 nm). These models can be input into future imagery to predict the salinity of the South Florida water ecosystem.
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Date Issued
2016
PURL
http://purl.flvc.org/fau/fd/FA00004686, http://purl.flvc.org/fau/fd/FA00004686
Subject Headings
Environmental management, Florida Bay (Fla.), Geographic information systems, Geospatial data, Marine ecology, Plant water relationships, Remote sensing, Salinity -- Florida -- Florida Bay -- Measurement
Format
Document (PDF)