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Title: THE MANTEÑO OF BOLA DE ORO: PAST HUMAN RESILIENCY TO CLIMATE CHANGE THROUGH REMOTE SENSING, EXCAVATION, AND CHRONOLOGICAL RECONSTRUCTION OF LANDSCAPE MODIFICATIONS.
Creator: Garzón-Oechsle, Andrés E., Johanson, Erik, Florida Atlantic University, Department of Geosciences, Charles E. Schmidt College of Science
Abstract/Description: The term "collapse" has become a widely used term that oversimplifies the intricate histories of human-environment interactions. It has contributed to the belief that civilizations in the Americas and the tropics could not endure over time. However, the Manteño civilization of the Ecuadorian coast challenges this notion. Flourishing for a thousand years (ca. 650–1700 CE), the Manteños inhabited the neotropics at the gates of one of the world's most influential climatic forces, the El Niño...
Show moreThe term "collapse" has become a widely used term that oversimplifies the intricate histories of human-environment interactions. It has contributed to the belief that civilizations in the Americas and the tropics could not endure over time. However, the Manteño civilization of the Ecuadorian coast challenges this notion. Flourishing for a thousand years (ca. 650–1700 CE), the Manteños inhabited the neotropics at the gates of one of the world's most influential climatic forces, the El Niño-Southern Oscillation (ENSO). To thrive, the Manteños needed to navigate the extremes of ENSO during the Medieval Climate Anomaly (MCA, ca. 950–1250 CE) and the Little Ice Age (LIA, ca. 1400–1700 CE) while capitalizing on ENSO's milder phases. This research uses change detection analysis of Normalized Difference Vegetation Index (NDVI) on Landsat satellite imagery under various ENSO conditions from 1986 to 2020 in southern Manabí, where the 16th-century Manteño territory of Salangome was situated. The findings indicate that the cloud forests found in the highest elevations of the Chongón-Colonche Mountains provide the most resilient environment in the region to adapt to a changing climate. Further investigations of the cloud forest of the Bola de Oro Mountain using Uncrewed Aerial Vehicles (UAV) equipped with LiDAR, ground-truthing, and excavation uncovered a landscape shaped by the Manteños.
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Date Issued: 2023
PURL: http://purl.flvc.org/fau/fd/FA00014225
Subject Headings: Climate change, Remote sensing, Archaeology
Format: Document (PDF)

Title: Fourier telescopy test system.
Creator: Randunu-Pathirannehelage, Nishantha, Torres Moreno, Yezid, Rhodes, William T., Graduate College
Date Issued: 2013-04-12
PURL: http://purl.flvc.org/fcla/dt/3361948
Subject Headings: Fourier transform optics, Imaging systems, Remote sensing
Format: Document (PDF)

Title: Characterization and Modeling of Profiling Oceanographic Lidar for Remotely Sampling Ocean Optical Properties.
Creator: Strait, Christopher, Nayak, Aditya, Florida Atlantic University, Department of Ocean and Mechanical Engineering, College of Engineering and Computer Science
Abstract/Description: Lidar has the ability to supplant or compliment many current measurement technologies in ocean optics. Lidar measures Inherent Optical Properties over long distances without impacting the orientation and assemblages of particles it measures, unlike many systems today which require pumps and flow cells. As an active sensing technology, it has the benefit of being independent of time of day and weather. Techniques to interpret oceanographic lidar lags behind atmospheric lidar inversion...
Show moreLidar has the ability to supplant or compliment many current measurement technologies in ocean optics. Lidar measures Inherent Optical Properties over long distances without impacting the orientation and assemblages of particles it measures, unlike many systems today which require pumps and flow cells. As an active sensing technology, it has the benefit of being independent of time of day and weather. Techniques to interpret oceanographic lidar lags behind atmospheric lidar inversion techniques to measure optical properties due to the complexity and variability of the ocean. Unlike in the atmosphere, two unknowns in the lidar equation backscattering at 180o (𝛽𝜋) and attenuation (c) do not necessarily covary. A lidar system developed at the Harbor Branch Oceanographic Institute is used as a test bed to validate a Monte-Carlo model to investigate the inversion of optical properties from lidar signals. Controlled tank experiments and field measurements are used to generate lidar waveforms and provide optical situations to model. The Metron EODES backscatter model is used to model waveforms. A chlorophyll based forward optical model provides a set of 1500 unique optical situations which are modeled to test inversion techniques and lidar geometries. Due to issues with the lidar system and model the goal of validating the model as well as a more mature inversion experiment were not completed. However, the results are valuable to show the complexity and promise of lidar systems.
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Date Issued: 2020
PURL: http://purl.flvc.org/fau/fd/FA00013631
Subject Headings: Lidar, Remote sensing, Seawater--Optical properties
Format: Document (PDF)

Title: Mapping urban land cover using multi-scale and spatial autocorrelation information in high resolution imagery.
Creator: Johnson, Brian A., Charles E. Schmidt College of Science, Department of Geosciences
Abstract/Description: Fine-scale urban land cover information is important for a number of applications, including urban tree canopy mapping, green space analysis, and urban hydrologic modeling. Land cover information has traditionally been extracted from satellite or aerial images using automated image classification techniques, which classify pixels into different categories of land cover based on their spectral characteristics. However, in fine spatial resolution images (4 meters or better), the high degree of...
Show moreFine-scale urban land cover information is important for a number of applications, including urban tree canopy mapping, green space analysis, and urban hydrologic modeling. Land cover information has traditionally been extracted from satellite or aerial images using automated image classification techniques, which classify pixels into different categories of land cover based on their spectral characteristics. However, in fine spatial resolution images (4 meters or better), the high degree of within-class spectral variability and between-class spectral similarity of many types of land cover leads to low classification accuracy when pixel-based, purely spectral classification techniques are used. Object-based classification methods, which involve segmenting an image into relatively homogeneous regions (i.e. image segments) prior to classification, have been shown to increase classification accuracy by incorporating the spectral (e.g. mean, standard deviation) and non-spectral (e.g. te xture, size, shape) information of image segments for classification. One difficulty with the object-based method, however, is that a segmentation parameter (or set of parameters), which determines the average size of segments (i.e. the segmentation scale), is difficult to choose. Some studies use one segmentation scale to segment and classify all types of land cover, while others use multiple scales due to the fact that different types of land cover typically vary in size. In this dissertation, two multi-scale object-based classification methods were developed and tested for classifying high resolution images of Deerfield Beach, FL and Houston, TX. These multi-scale methods achieved higher overall classification accuracies and Kappa coefficients than single-scale object-based classification methods., Since the two dissertation methods used an automated algorithm (Random Forest) for image classification, they are also less subjective and easier to apply to other study areas than most existing multi-scale object-based methods that rely on expert knowledge (i.e. decision rules developed based on detailed visual inspection of image segments) for classifying each type of land cover.
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Date Issued: 2012
PURL: http://purl.flvc.org/FAU/3342110
Subject Headings: Image processing, Digital techniques, Remote sensing, Mathematics, Remote-sensing images, Computational intelligence, Cities and towns, Remote sensing, Environmental sciences, Remote sensing, Spatial analysis (Statistics)
Format: Document (PDF)

Title: Image classification and image resolution issues for DOQQ analysis.
Creator: Boruff, Bryan Jeffery., Florida Atlantic University, Roberts, Charles
Abstract/Description: High-resolution imagery is becoming readily available to the public. Private firms and government organizations are using high-resolution images but are running into problems with storage space and processing time. High-resolution images are extremely large files, and have proven cumbersome to work with and control. By resampling fine resolution imagery to a lower resolution, storage and processing space can be dramatically reduced. Fine-resolution imagery is not needed to map most features...
Show moreHigh-resolution imagery is becoming readily available to the public. Private firms and government organizations are using high-resolution images but are running into problems with storage space and processing time. High-resolution images are extremely large files, and have proven cumbersome to work with and control. By resampling fine resolution imagery to a lower resolution, storage and processing space can be dramatically reduced. Fine-resolution imagery is not needed to map most features and resampled high-resolution imagery can be used as a replacement for low-resolution satellite imagery in some cases. The effects of resampling on the spectral quality of a high-resolution image can be demonstrated by answering the following questions: (1) Is the quality of spectral information on a color infrared DOQQ comparable to SPOT and TM Landsat satellite imagery for the purpose of digital image classification? (2) What is the appropriate resolution for mapping surface features using high-resolution imagery for spectral categories of information? (3) What is the appropriate resolution for mapping surface features using high-resolution imagery for land-use land-cover information?
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Date Issued: 2000
PURL: http://purl.flvc.org/fcla/dt/15787
Subject Headings: Remote sensing, Image processing, Image analysis
Format: Document (PDF)

Title: Remote sensing systems for monitoring and quantifying tropical deforestation in the Huallaga River Valley of Peru.
Creator: Echavarria, Fernando R., Florida Atlantic University, Craig, Alan K., Charles E. Schmidt College of Science, Department of Geosciences
Abstract/Description: This thesis examines the quantification of tropical deforestation, the use of remote sensing techniques for its scientific measurement, and the many controversies surrounding the problem. Aerial photographs and Landsat-based planimetric maps were used to determine the conversion of montane rain forest in a 1,000 km$\sp2$ sector of Peru's Huallaga River Valley. Between 1963 and 1976, 244 km$\sp2$ of forest (approximately a quarter of the study area) were converted to agricultural and other...
Show moreThis thesis examines the quantification of tropical deforestation, the use of remote sensing techniques for its scientific measurement, and the many controversies surrounding the problem. Aerial photographs and Landsat-based planimetric maps were used to determine the conversion of montane rain forest in a 1,000 km$\sp2$ sector of Peru's Huallaga River Valley. Between 1963 and 1976, 244 km$\sp2$ of forest (approximately a quarter of the study area) were converted to agricultural and other land uses, an apparent deforestation rate of 19 km$\sp2$/yr or approximately 1,872 ha/yr. The method entailed the cutting and weighing of strips of Mylar overlays. Despite the photogrammetric limitations, the results demonstrate an economical and practical technique that is readily applicable to developing countries. The potential of other remote sensing systems and the application of change detection techniques such as digital image subtraction to monitor deforestation is detailed.
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Date Issued: 1989
PURL: http://purl.flvc.org/fcla/dt/14538
Subject Headings: Geography, Physical Geography, Environmental Sciences, Remote Sensing
Format: Document (PDF)

Title: MONITORING AND MODELING URBAN GROWTH PROCESS AND MEASURING COMMUNITY RESILIENCE TO DISASTERS IN THE COASTAL UNITED STATES.
Creator: Rifat, Shaikh Abdullah Al, Liu, Weibo, Florida Atlantic University, Department of Geosciences, Charles E. Schmidt College of Science
Abstract/Description: Global population is increasing at an alarming rate with rapid urbanization of the earth’s land surface. Currently, more than half of the world’s population lives in urban areas and this number is projected to increase to 66% by 2050. Urban expansion in coastal zones is more complex due to the rapid urbanization and higher population growth. In the United States (US), more than 39% of the total population now lives in coastal counties. Although urbanization offers some advantages such as...
Show moreGlobal population is increasing at an alarming rate with rapid urbanization of the earth’s land surface. Currently, more than half of the world’s population lives in urban areas and this number is projected to increase to 66% by 2050. Urban expansion in coastal zones is more complex due to the rapid urbanization and higher population growth. In the United States (US), more than 39% of the total population now lives in coastal counties. Although urbanization offers some advantages such as economic development, unplanned urbanization can adversely affect our environment. Additionally, coastal communities in the US are frequently impacted by disasters. Climate change such as sea level rise could intensify these coastal disasters and impact more lives and properties. Therefore, using Geographic Information Systems (GIS) and remote sensing, this study examines these pressing environmental challenges with the coastal US as the Study area. We first quantified the historical spatiotemporal patterns and major explanatory factors of urban expansion in the Miami Metropolitan Area during 1992 - 2016 at different spatial scales. Additionally, different urban expansion dynamics such as expansion rate, pattern, types, intensity, and landscape metrics were analyzed. Multi-level spatiotemporal analyses suggest that urban growth varied both spatially and temporally across the study area. We then measured the community resilience to coastal disasters by constructing a composite index. Additionally, spatial relationships between resilience components and disaster impacts were investigated. Results suggest that northeastern coastal communities in the US are more resilient to disasters compared to the southeastern communities. Furthermore, community resilience varies across the space and resilience components used in this study can explain disaster damages. Finally, this research also simulates and predicts three future urban growth scenarios including business as usual, planned growth, and sustainable growth in the study area. Then current and future exposures to flooding were estimated by considering different sea level rise scenarios. Results suggest that future urban areas will be developed significantly in the flood risk areas if development is not restricted in the high-risk flooding zone. Findings from this study could be useful for area-specific disaster management policy guidelines and formation of land use policy and planning.
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Date Issued: 2021
PURL: http://purl.flvc.org/fau/fd/FA00013855
Subject Headings: Coastal Zones, Urban growth, Disasters, Remote sensing
Format: Document (PDF)

Title: Supervised classification of a digital orthophoto quadrangle quarter.
Creator: Vacchiano, James., Florida Atlantic University, Roberts, Charles
Abstract/Description: Digital orthophoto quadrangle quarter (DOQQ) is a new type of imagery. The DOQQ is a product of the United States Geological Survey, which has many uses. The spectral and spatial qualities of a DOQQ are equal to and surpass the qualities of traditional satellite imagery. These qualities can be demonstrated by answering the following questions: (1) Is the quality of the spectral information on a color infrared DOQQ comparable to a SPOT and TM Landsat satellite imagery for the purpose of...
Show moreDigital orthophoto quadrangle quarter (DOQQ) is a new type of imagery. The DOQQ is a product of the United States Geological Survey, which has many uses. The spectral and spatial qualities of a DOQQ are equal to and surpass the qualities of traditional satellite imagery. These qualities can be demonstrated by answering the following questions: (1) Is the quality of the spectral information on a color infrared DOQQ comparable to a SPOT and TM Landsat satellite imagery for the purpose of digital image classification? (2) What are the optimal number of classes for achieving an accuracy supervised classification of a one-meter resolution DOQQ? (3) What is the effect of changing the spatial resolution on image classification of a DOQQ?
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Date Issued: 1998
PURL: http://purl.flvc.org/fcla/dt/15584
Subject Headings: Digital mapping, Remote-sensing images
Format: Document (PDF)

Title: MACHINE LEARNING METHODS FOR IMAGE ENHANCEMENT IN DEGRADED VISUAL ENVIRONMENTS.
Creator: Estrada, Dennis, Tang, Yufei, Ouyang, Bing, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
Abstract/Description: Significant reduction in space, weight, power, and cost (SWAP-C) of imaging hardware has induced a paradigm shift in remote sensing where unmanned platforms have become the mainstay. However, mitigating the degraded visual environment (DVE) remains an issue. DVEs can cause a loss of contrast and image detail due to particle scattering and distortion due to turbulence-induced effects. The problem is especially challenging when imaging from unmanned platforms such as autonomous underwater...
Show moreSignificant reduction in space, weight, power, and cost (SWAP-C) of imaging hardware has induced a paradigm shift in remote sensing where unmanned platforms have become the mainstay. However, mitigating the degraded visual environment (DVE) remains an issue. DVEs can cause a loss of contrast and image detail due to particle scattering and distortion due to turbulence-induced effects. The problem is especially challenging when imaging from unmanned platforms such as autonomous underwater vehicles (AUV) and unmanned ariel vehicles (UAV). While single-frame image restoration techniques have been studied extensively in recent years, single image capture is not adequate to address the effects of DVEs due to under-sampling, low dynamic range, and chromatic aberration. Significant development has been made to employ multi-frame image fusion techniques to take advantage of spatial and temporal information to aid in the recovery of corrupted image detail and high-frequency content and increasing dynamic range.
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Date Issued: 2022
PURL: http://purl.flvc.org/fau/fd/FA00013987
Subject Headings: Image Enhancement, Machine learning, Remote sensing
Format: Document (PDF)

Title: QUANTIFICATION OF PERMAFROST THAW DEPTH AND SNOW DEPTH IN INTERIOR ALASKA AT MULTIPLE SCALES USING FIELD, AIRBORNE, AND SPACEBORNE DATA.
Creator: Brodylo, David, Zhang, Caiyun, Florida Atlantic University, Department of Geosciences, Charles E. Schmidt College of Science
Abstract/Description: Much of Interior Alaska contains permafrost, which is a permanently frozen layer found within or at the surface of the Earth. Historically, this permafrost has experienced relative stability, with limited thaw during warmer summer months and fire events. However, largely due to the impact of a warming climate, among other factors, permafrost that would typically experience limited thawing during the summer season has recently been thawing at an unprecedented rate. Trapped by this layer of...
Show moreMuch of Interior Alaska contains permafrost, which is a permanently frozen layer found within or at the surface of the Earth. Historically, this permafrost has experienced relative stability, with limited thaw during warmer summer months and fire events. However, largely due to the impact of a warming climate, among other factors, permafrost that would typically experience limited thawing during the summer season has recently been thawing at an unprecedented rate. Trapped by this layer of permafrost is a large quantity of carbon (C), which could be released into the atmosphere as greenhouse gases such as carbon dioxide (CO2) and methane (CH4). Due to the remoteness of the Arctic, there is a lack of yearly recorded permafrost thaw depth and snow depth values across much of the region. As such, the focus of this research was to establish a framework to identify how permafrost thaw depth and snow depth can be predicted across both a 1 km2 local scale and a 100 km2 regional scale in Interior Alaska by a combination of 1 m2 field data, airborne and spaceborne remote sensing products, and object-based machine learning techniques from 2014 – 2022. Machine learning techniques Random Forest, Support Vector Machine, k-Nearest Neighbor, Multiple Linear Regression, and Ensemble Analysis were applied to predict the permafrost thaw depth and snow depth. Results indicated that this methodology was able to successfully upscale both the 1 m2 field permafrost thaw depth and snow depth data to a 1 km2 local scale before successfully further upscaling the estimated results to a 100 km2 regional scale, while also linking the estimated values with ecotypes. The best results were produced by Ensemble Analysis, which tended to have the highest Pearson’s Correlation Coefficient, alongside the lowest Mean Absolute Error and Root Mean Square Error. Both Random Forest and k-Nearest Neighbor also provided encouraging results. The presence or absence of a thick canopy cover was strongly connected with thaw depth and snow depth estimates. Image resolution was an important factor when upscaling field data to the local scale, however it was overall less critical for further upscaling to the regional scale.
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Date Issued: 2023
PURL: http://purl.flvc.org/fau/fd/FA00014229
Subject Headings: Permafrost--Alaska, Remote sensing, Machine learning
Format: Document (PDF)

Title: Commercialization of high-resolution earth observation satellite remote sensing.
Creator: Jarica, Cornelia Christa, Florida Atlantic University, Tata, Robert J., Charles E. Schmidt College of Science, Department of Geosciences
Abstract/Description: The imminent availability of high resolution satellite imagery is causing a paradigm shift in remote sensing. Detente brought about new policy directives in the U.S. and abroad, which opened up for civilian use former Earth observation spy technology down to one meter resolution, previously considered classified and strictly used by the intelligence communities for national security. This study describes a number of new ventures in the private sector which have been formed to launch...
Show moreThe imminent availability of high resolution satellite imagery is causing a paradigm shift in remote sensing. Detente brought about new policy directives in the U.S. and abroad, which opened up for civilian use former Earth observation spy technology down to one meter resolution, previously considered classified and strictly used by the intelligence communities for national security. This study describes a number of new ventures in the private sector which have been formed to launch commercial high resolution systems. The satellites' technical capabilities are analyzed, and application development options for the new imagery are discussed in detail. This new remote sensing data source is also seen within the framework of the larger GeoTechnology Industry to which it belongs, and the author proposes appropriate business strategies for successful commercialization.
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Date Issued: 1996
PURL: http://purl.flvc.org/fcla/dt/15321
Subject Headings: Earth resources technology satellites, Remote sensing, Remote-sensing images, Geographic information systems
Format: Document (PDF)

Title: Determination of Horizontal Motion through Optical Flow Computations.
Creator: Chih-Ho, Yu, Caimi, F. M., Harbor Branch Oceanographic Institute
Date Issued: 1997
PURL: http://purl.flvc.org/fcla/dt/3318842
Subject Headings: Remote submersibles, Remote submersibles --Automatic control, Computer vision, Optical measurements --Remote sensing
Format: Document (PDF)

Title: Utilizing Remote Sensing to Describe the Area of Occurrence of the Dania Beach Monkeys, Chlorocebus sabaeus, from Introduction to Present.
Creator: Lyon, Ashley M., Detwiler, Kate, Florida Atlantic University, Dorothy F. Schmidt College of Arts and Letters, Department of Anthropology
Abstract/Description: This research investigates land use change and the area of occurrence of an introduced primate species, Chlorocebus sabaeus, from 1940 until the present. Research into the importation and subsequent release of these monkeys has revealed that they were released from a failed tourist attraction in 1947. The attraction was located southeast of the Hollywood International Airport in Fort Lauderdale, Florida. Remote sensing techniques were utilized to examine land use change over time, create a...
Show moreThis research investigates land use change and the area of occurrence of an introduced primate species, Chlorocebus sabaeus, from 1940 until the present. Research into the importation and subsequent release of these monkeys has revealed that they were released from a failed tourist attraction in 1947. The attraction was located southeast of the Hollywood International Airport in Fort Lauderdale, Florida. Remote sensing techniques were utilized to examine land use change over time, create a land classification map, and create a canopy model. These data were used to better understand the area of occurrence of an introduced primate species by examining anthropogenic changes through time and measuring changes in available forest habitat. Corridors, and their transformation through the decades, were evaluated to better understand potential dispersal routes and connectivity to natural areas for colonization.
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Date Issued: 2019
PURL: http://purl.flvc.org/fau/fd/FA00013330
Subject Headings: Green monkey, Introduced species, Dania Beach (Fla ), Remote sensing
Format: Document (PDF)

Title: RURAL-URBAN FRINGE DELINEATION BY INSTRUMENTED INTERPRETATION OF IMAGERY FROM HIGH-ALTITUDE AND ORBITAL REMOTE SENSORS: AN EXPERIMENTAL APPLICATION OF TV SCANNING WAVEFORM ANALYSIS AND COLOR-INFRARED IMAGERY INTERPRETATION FOR EXTRACTING GEOGRAPHIC PATTERNS.
Creator: SENYKOFF, RONALD SERGEI., Florida Atlantic University, Latham, James P., Charles E. Schmidt College of Science, Department of Geosciences
Abstract/Description: Delineating the rural-urban fringe around an urban area has importance because much urban growth takes place on rural lands, often agricultural, thus changing land use patterns. Characteristics of geographic phenomena in this fringe area are analyzed and illustrated. This investigation examines.the possibilities for geographically delineating with multi-spectral imagery from ERTS-1 satellite the fringe zone of Delray Beach, a coastal city in southeastern Florida. Experimental methodology...
Show moreDelineating the rural-urban fringe around an urban area has importance because much urban growth takes place on rural lands, often agricultural, thus changing land use patterns. Characteristics of geographic phenomena in this fringe area are analyzed and illustrated. This investigation examines.the possibilities for geographically delineating with multi-spectral imagery from ERTS-1 satellite the fringe zone of Delray Beach, a coastal city in southeastern Florida. Experimental methodology interprets land use categories from high-altitude color-infrared and ERTS-1 imagery. A closed-circuit television system demonstrates possibilities for automatic analysis. Land use data were classified with automation as the principal objective. Some filtering techniques were used for image enhancement. Test results indicate that with sufficient ground data acquisition and statistical computations the fringe zone can be mapped using ERTS imagery as a data base.
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Date Issued: 1975
PURL: http://purl.flvc.org/fcla/dt/13695
Subject Headings: Land use--Florida--Remote sensing, Aerial photogrammetry--Florida
Format: Document (PDF)

Title: IDENTIFICATION OF SURFACE DEPRESSIONAL FEATURES POTENTIALLY RELATED TO SINKHOLES IN MARTIN COUNTY, FLORIDA, USING REMOTE SENSING TECHNIQUES.
Creator: Sanju, Khatri, Comas, Xavier, Florida Atlantic University, Department of Geosciences, Charles E. Schmidt College of Science
Abstract/Description: Sinkholes are common karst features in Florida, having the highest rate of sinkhole occurrence in the US, which results in hundreds of millions estimated costs in damage per year and occasional life losses. While most sinkhole incidents reported in Florida relate to surface subsidence and collapse processes, other sinkhole formation mechanisms (like sagging) have received little attention as a relevant subsidence process. This is important since extensive areas of karst bedrock are overlain...
Show moreSinkholes are common karst features in Florida, having the highest rate of sinkhole occurrence in the US, which results in hundreds of millions estimated costs in damage per year and occasional life losses. While most sinkhole incidents reported in Florida relate to surface subsidence and collapse processes, other sinkhole formation mechanisms (like sagging) have received little attention as a relevant subsidence process. This is important since extensive areas of karst bedrock are overlain by variable thicknesses of non-soluble formations that may affect both the kinematics and damaging potential of these sinkholes in Florida. This research presents an automated GIS-based method to easily delineate surface depressional features in Martin County that result in surface depressional features and are related to cover sagging sinkholes. A total of 3,091 depressional features in Martin County were mapped using GIS methods and constrained with already existing direct drill cores. Results show a consistent statistically significant negative correlation between several morphometric features (i.e., area, perimeter, or depth) from these depressional features and depth to the limestone, suggesting that depressions are linked to sinkholes developed in deep-seated karst. While further subsurface imaging is needed to confirm this correlation, previous studies confirm these results and suggest that cover sagging, or cover suffusion sinkholes may represent a very large group of sinkholes traditionally unaccounted for in current sinkhole assessment maps in Florida. The methodology presented in this study can be easily extrapolated to other areas to further expand current sinkhole hazard and distribution maps.
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Date Issued: 2021
PURL: http://purl.flvc.org/fau/fd/FA00013872
Subject Headings: Sinkholes--Florida, Martin County (Fla.), Karst, Remote sensing
Format: Document (PDF)

Title: Iterative remote sensing as an alternative for complex vegetation mapping.
Creator: Boutiette, Robert L., Florida Atlantic University, Roberts, Charles
Abstract/Description: The South Florida Water Management District in conjunction with Florida Atlantic University began an effort to record vegetation invading Lake Okeechobee in 1994. This effort included a mapping project that would include all detectable vegetation within the expanding littoral zone. There were several problems associated with remote sensing aspects of this project. These problems resulted in inaccurate classification of species and a redundancy of mapping for large areas. This thesis will...
Show moreThe South Florida Water Management District in conjunction with Florida Atlantic University began an effort to record vegetation invading Lake Okeechobee in 1994. This effort included a mapping project that would include all detectable vegetation within the expanding littoral zone. There were several problems associated with remote sensing aspects of this project. These problems resulted in inaccurate classification of species and a redundancy of mapping for large areas. This thesis will review the remote sensing methods used for the mapping project, analyze the associated errors within the map product, and lastly offer an alternative approach, incorporating the use of iterative remote sensing, for mapping the vegetation of Lake Okeechobee and other areas of complex vegetation.
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Date Issued: 1997
PURL: http://purl.flvc.org/fcla/dt/15491
Subject Headings: Vegetation mapping--Remote sensing, Phytogeography, Geographic information systems
Format: Document (PDF)

Title: SALT MARSH SPECIES CLASSIFICATION AND SOIL PROPERTY MODELING USING MULTIPLE REMOTE SENSORS.
Creator: Nicholson, Heather M., Zhang, Caiyun, Florida Atlantic University, Department of Geosciences, Charles E. Schmidt College of Science
Abstract/Description: Salt marshes are highly dynamic ecosystems that rely on multiple environmental and physical drivers that determine species distribution and soil property distribution. However, climate change and human interference are threatening the delicate ecosystem. One of the easiest ways to monitor marsh dynamics is through remote sensing. Traditional methods may not handle the large, non-parametric datasets well and often do not spatially determine areas of uncertainty. This dissertation research...
Show moreSalt marshes are highly dynamic ecosystems that rely on multiple environmental and physical drivers that determine species distribution and soil property distribution. However, climate change and human interference are threatening the delicate ecosystem. One of the easiest ways to monitor marsh dynamics is through remote sensing. Traditional methods may not handle the large, non-parametric datasets well and often do not spatially determine areas of uncertainty. This dissertation research developed a framework to map marsh species and predict ground soil properties using multiple remote sensing data sources by integrating modern Object-based Image Analysis (OBIA), machine learning, data fusion, and band indices techniques. It also sought to determine areas of uncertainty in the final outputs and differences between different spectral resolutions. Five machine learning classifiers were examined including Support Vector Machine (SVM) and Random Forest (RF) to map marsh species. Overall results illustrated that RF and SVM typically performed best, especially when using hyperspectral data combined with DEM information. Seven regressors were assessed to map three different soil properties. Again, RF and SVM performed the best no matter the dataset used, or soil property mapped. Soil salinity had r as high as 0.93, soil moisture had r as high as 0.91, and soil organic an r as high as 0.74 when using hyperspectral data.
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Date Issued: 2022
PURL: http://purl.flvc.org/fau/fd/FA00014000
Subject Headings: Salt marshes, Salt marsh ecology, Species, Remote sensing
Format: Document (PDF)

Title: Placement and Denoising of Total Magnetic Field Sensors Onboard an AUV in Support of Geophysical Navigation.
Creator: Cracchiolo, Timothy, Beaujean, Pierre-Philippe, Florida Atlantic University, Department of Ocean and Mechanical Engineering, College of Engineering and Computer Science
Abstract/Description: The objective of this thesis is to study the proper placement and denoising of Total Field Magnetometers (TFM) installed on an Autonomous Underwater Vehicle (AUV), in support of a long-term goal to perform geophysical navigation based on total field magnetic sensing. This new form of navigation works by using the magnetic field of the Earth as a source of reference to find the desired heading. The primary tools used in this experiment are a REMUS 100 AUV, a QuSpin scalar magnetometer, and a...
Show moreThe objective of this thesis is to study the proper placement and denoising of Total Field Magnetometers (TFM) installed on an Autonomous Underwater Vehicle (AUV), in support of a long-term goal to perform geophysical navigation based on total field magnetic sensing. This new form of navigation works by using the magnetic field of the Earth as a source of reference to find the desired heading. The primary tools used in this experiment are a REMUS 100 AUV, a QuSpin scalar magnetometer, and a TwinLeaf vector magnetometer. The Earth’s magnetic field was measured over periods of several hours to determine the range of values it provides under natural conditions. Digital filters were created to digitally reduce fluctuations caused by sources of external interference and sources of internal interference. To mitigate the issue of platform based interference, two methods were examined. These methods involved the use of the Tolles-Lawson model and Wavelet Multiresolution Analysis. The Tolles-Lawson model is used to determine the compensation coefficients from a calibration mission to mitigate the effects from the permanently detected magnetic field, the induced magnetic field, eddy currents. and the geomagnetic field. Wavelet multiresolution analysis follows the same basic steps as Fourier transformations and is used to analyze time series with power sources in motion over a frequency spectrum. Several acquisitions were run with the QuSpin in various locations around and along REMUS, and it was concluded that placing the sensor at the very front of the vessel which is approximately 1.8 [m] from the DC motor, with assistance from wavelet analysis was acceptable for the project.
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Date Issued: 2022
PURL: http://purl.flvc.org/fau/fd/FA00013972
Subject Headings: Autonomous underwater vehicles, Magnetometers, Magnetic fields, Remote sensing
Format: Document (PDF)

Title: MONITORING AND ANALYZING THE SEASONAL WETLAND INUNDATION DYNAMICS IN THE EVERGLADES FROM 2002 TO 2021 USING GOOGLE EARTH ENGINE.
Creator: Hasan, Ikramul, Liu, Weibo, Florida Atlantic University, Department of Geosciences, Charles E. Schmidt College of Science
Abstract/Description: Previously published in Geographies 2023, 3(1), 161-177 (DOI: https://doi.org/10.3390/geographies3010010) Inundation dynamics coupled with seasonal information is critical to study the wetland environment. Analyses based on remotely sensed data are the most effective means to monitor and investigate wetland inundation dynamics. For the first time, this study deployed an automated thresholding method to quantify and compare the annual inundation characteristics in dry and wet seasons in the...
Show morePreviously published in Geographies 2023, 3(1), 161-177 (DOI: https://doi.org/10.3390/geographies3010010) Inundation dynamics coupled with seasonal information is critical to study the wetland environment. Analyses based on remotely sensed data are the most effective means to monitor and investigate wetland inundation dynamics. For the first time, this study deployed an automated thresholding method to quantify and compare the annual inundation characteristics in dry and wet seasons in the Everglades, using Landsat imagery in Google Earth Engine (GEE). This research presents the long-term time series maps from 2002 to 2021, with a comprehensive spatiotemporal depiction of inundation. In this paper, we bridged the research gap of space-time analysis for multi-season inundation dynamics, which is urgently needed for the Everglades wetland. Within a GIS-based framework, we integrated statistical models, such as Mann–Kendall and Sen’s Slope tests, to track the evolutionary trend of seasonal inundation dynamics. The spatiotemporal analyses highlight the significant differences in wet and dry seasons through time and space. The stationary or permanent inundation is more likely to be distributed along the coastal regions (Gulf of Mexico and Florida Bay) of the Everglades, presenting a warning regarding their vulnerability to sea level rise.
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Date Issued: 2023
PURL: http://purl.flvc.org/fau/fd/FA00014244
Subject Headings: Everglades (Fla.)--Environmental conditions--Remote sensing, Google Earth
Format: Document (PDF)

Title: Remote sensing of evapotranspiration using automated calibration: development and testing in the state of Florida.
Creator: Evans, Aaron H., Obeysekera, Jayantha, Zhang, Caiyun, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Geosciences
Abstract/Description: Thermal remote sensing is a powerful tool for measuring the spatial variability of evapotranspiration due to the cooling effect of vaporization. The residual method is a popular technique which calculates evapotranspiration by subtracting sensible heat from available energy. Estimating sensible heat requires aerodynamic surface temperature which is difficult to retrieve accurately. Methods such as SEBAL/METRIC correct for this problem by calibrating the relationship between sensible heat and...
Show moreThermal remote sensing is a powerful tool for measuring the spatial variability of evapotranspiration due to the cooling effect of vaporization. The residual method is a popular technique which calculates evapotranspiration by subtracting sensible heat from available energy. Estimating sensible heat requires aerodynamic surface temperature which is difficult to retrieve accurately. Methods such as SEBAL/METRIC correct for this problem by calibrating the relationship between sensible heat and retrieved surface temperature. Disadvantage of these calibrations are 1) user must manually identify extremely dry and wet pixels in image 2) each calibration is only applicable over limited spatial extent. Producing larger maps is operationally limited due to time required to manually calibrate multiple spatial extents over multiple days. This dissertation develops techniques which automatically detect dry and wet pixels. LANDSAT imagery is used because it resolves dry pixels. Calibrations using 1) only dry pixels and 2) including wet pixels are developed. Snapshots of retrieved evaporative fraction and actual evapotranspiration are compared to eddy covariance measurements for five study areas in Florida: 1) Big Cypress 2) Disney Wilderness 3) Everglades 4) near Gainesville, FL. 5) Kennedy Space Center. The sensitivity of evaporative fraction to temperature, available energy, roughness length and wind speed is tested. A technique for temporally interpolating evapotranspiration by fusing LANDSAT and MODIS is developed and tested. The automated algorithm is successful at detecting wet and dry pixels (if they exist). Including wet pixels in calibration and assuming constant atmospheric conductance significantly improved results for all but Big Cypress and Gainesville. Evaporative fraction is not very sensitive to instantaneous available energy but it is sensitive to temperature when wet pixels are included because temperature is required for estimating wet pixel evapotranspiration. Data fusion techniques only slightly outperformed linear interpolation. Eddy covariance comparison and temporal interpolation produced acceptable bias error for most cases suggesting automated calibration and interpolation could be used to predict monthly or annual ET. Maps demonstrating spatial patterns of evapotranspiration at field scale were successfully produced, but only for limited spatial extents. A framework has been established for producing larger maps by creating a mosaic of smaller individual maps.
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Date Issued: 2014
PURL: http://purl.flvc.org/fau/fd/FA00004194, http://purl.flvc.org/fau/fd/FA00004194
Subject Headings: Climatic changes, Environmental sciences -- Remote sensing, Evapotranspiration -- Measurement, Geographic information systems, Remote sensing -- Data processing, Spatial analysis (Mathematics)
Format: Document (PDF)

FAU Theses and Dissertations (47)	+ -
FAU Graduate Student Research (1)	+ -
HBOI Faculty Contributions (1)	+ -

Remote sensing (21)	+ -
Geographic information systems (6)	+ -
Image processing (4)	+ -
Remote-sensing images (4)	+ -
Spatial analysis (Statistics) (4)	+ -

Aerial photogrammetry (3)	+ -
Ecology--Remote sensing (3)	+ -
Geographic information systems. (3)	+ -
Image analysis (3)	+ -
Machine learning (3)	+ -
Digital techniques (2)	+ -
Everglades National Park (Fla.)--Environmental conditions. (2)	+ -
Imaging systems (2)	+ -
Marine ecology (2)	+ -
Remote sensing. (2)	+ -
Vegetation mapping--Remote sensing (2)	+ -
Aerial photogrammetry--Data processing (1)	+ -
Aerial photogrammetry--Florida (1)	+ -
Aerial photography (1)	+ -
Aerial photography in archaeology. (1)	+ -
Aerial photography in forestry (1)	+ -
Aerial photography in geography--Florida--Palm Beach County (1)	+ -
African Americans, Violence against. (1)	+ -
Amazon parrots (1)	+ -
Anthropogenic effects on nature (1)	+ -
Archaeology (1)	+ -
Autonomous underwater vehicles (1)	+ -
Canals--Remote sensing. (1)	+ -
Canals--Sable, Cape (Fla.) (1)	+ -
Cartography--Remote sensing. (1)	+ -

Florida (4)	+ -
Casuarina--Florida (1)	+ -
Continental shelf--Florida (1)	+ -
Environmental mapping--Florida (1)	+ -
Evergaldes (1)	+ -

Florida Bay (1)	+ -
Florida Reef Tract (1)	+ -
Geomorphological mapping--Florida--Broward County (1)	+ -
Rotenberger Wildlife Management Area (Fla.) (1)	+ -
United States (1)	+ -
Whitewater Bay (1)	+ -
Whitewater Bay (Fla.) (1)	+ -

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