Roberts, Charles

The population of southeast Florida has grown considerably since the 1940's. Managing this population growth has challenged urban planners and growth managers. Prior to 1970, geographers and cartographers struggled with mapping this area as the landscape underwent rapid transformation to accommodate millions of new residents. With the launch of the Landsat satellite series in 1972, digital satellite images of southeast Florida have been acquired every 18 days to provide geographers and cartographers with a new tool for monitoring land use change. This thesis examines the utility of using this new tool combined with historical aerial photographs to document land use change through time.

Satellite derived vegetative data of urban areas is normally classified into several classes of trees, fields, grass and bare soil using unsupervised and supervised classification methods. Normalized Difference Vegetation Indexes (NDVI) have traditionally been applied to agricultural satellite images to assess the health and maturity of commercial crops. When a NDVI is used to examine urban vegetation, many discrete data values are generated which can be differentiated into meaningful vegetation classes.

The objective of this thesis is to conduct a time series analysis of melaleuca growth in the littoral zone of western Lake Okeechobee, using historical aerial photography and Scientific Visualization, Image Enhancement and Image Exploration techniques are examined and compared. Problems associated with creating a time series analysis using aerial photography for use in an integrated GIS are explored. A spatial analysis of environmental factors affecting the growth of Melaleuca quinquenervia is conducted, and an analysis of the validity of such statistical inferences for use in future decision making is examined. Results indicate that managed water levels inside Lake Okeechobee did indeed have an effect on the rate of growth of Melaleuca quinquenervia. Recommendations for future data gathering and study are outlined.

Much of the recent research concerning the use of GIS has revolved around data quality. Types of errors inherent in GIS data layers, and also errors that may be produced through the creation and manipulation of data layers have been identified. Definitions of these errors, and observations of how these errors occur have been offered. However, the majority of the research is qualitative. It is known that positional variation is produced through differing interpretations and generalization of points, lines, and polygons, but it is not known to what extent. This information would be extremely helpful in allowing the user of the information to fine tune the application, based on the accuracy of the data. Providing this type of information is the goal of this research. Quantitative analysis of the results of a series of experiments will give a numerical range of possible positional errors produced through database creation via aerial photo interpretation.

Protecting Natural Resources, such as drinking water in terms of quality and quantity, is one of the missions of South Florida Water Management District (SFWMD). Water Supply Planning is one of the many projects at the Planning Department of the SFWMD, in which sixteen counties are analyzed to determine the most accurate population distribution for water supply distribution among the water utility companies. This thesis examines the current methodology which is used at the SFWMD, and addresses its shortcomings. It then introduces a proposed methodology, to improve population distribution analysis, by incorporating satellite imagery. Textural classification of satellite imagery will be used to extract residential neighborhoods from non-residential areas. The resultant residential areas, which is in the form of raster data, then will be converted to a vector coverage to be utilized as an additional source of data. Incorporating satellite imagery eliminates the assumption of homogenous population distribution, which the current methodology is based on and consequently, leads to a more accurate population distribution methodology.

The Loxahatchee Slough is the largest wilderness island refuge existing in Palm Beach County, Florida. Cultural impacts have altered the hydrology of the area. This study provides a database of historical and geographical information regarding the Slough. Aerial photography and satellite imagery from pre- and post-channelization dates are classified according to vegetation ecosystems. GIS analysis is used to compare these diverse data sets. Changes in hydroperiod are examined, using vegetation as an indicator. Results show a general trend toward dryer hydroperiod vegetation land cover. Since 1979, the Army Corps of Engineers has raised water levels back toward pre-channelization levels, in a portion of the study area known as the Historic Region. Results indicate a positive response, with a net increase of longer hydroperiod vegetation in this region since 1979.

A new technique was devised that produces a LIDAR based predevelopment Digital Elevation Model and offers a more superior visualization, of the natural landscape prior to development, than the Bare Earth Model produced by Florida International University's Hurricane Center. Two locations in southeastern Florida have been chosen for this study. The first site is utilized as a control for testing the model and contains a present day ridge system that runs north and south through the Boca Raton cemetery. The second site is a paleowatershed, the Yamato Marsh which was located in Delray Beach. Modeling of the marsh site will assist in delineating surficial geomorphic features before they were anthropogenically altered. The predevelopment Digital Elevation Model successfully represents human derived land-use changes and defines the watershed boundaries of the historic Yamato Marsh.

The development of high resolution LIDAR DSM combined with digital infrared ortho-photography data enhances the ability to map canopy structures with a higher degree of accuracy and precision than with either data set alone. The purpose of this thesis is to map Australian Pine (Casuarina equisetifolia with a 85% or greater accuracy by creating a methodology that uses LIDAR and color infrared ortho-photography and to test it within three different landscape types within Broward County. LIDAR features below a determined height threshold (i.e. Deerpoint 25 ft) were eliminated and recoded to 0 to create Mask 1. NDVI technique separated non-vegetative features from vegetative features to create Mask 2. Mask 1 and Mask 2 were merged and overlaid on the raw LIDAR data set to perform isodata clustering, as well as density slicing to identify mature Australian Pines. Careful delineation of study areas is critical to obtain the highest possible accuracy. Density slicing proved to be a faster and less time consuming technique for achieving 85% level of accuracy than compared to isodata clustering.

The project manager has much to deliberate when choosing a software package for image rectification/registration. He/she must be able to perform a cost analysis evaluation of the packages in question, and determine which package will provide the highest level of positional accuracy. Objective and subjective analysis of six software packages, ArcView Image Analysis, GeoMedia Pro, Arc/Info 8.1, ERMAPPER, ENVI and Idrisi 3.2, and their multiple products (polynomials and triangulations) provide the basis with which the project manager may attain this goal. He/she is familiarized with the user interface of each package, through detailed step-by-step methodology. Positional accuracy of each product is compared to Ground Control Points (GCPs) derived from a Differential Global Positioning System (DGPS). The accuracy of each product is also compared to the industry standard USGS DOQQ, and it is discovered that while simple rectification procedures may produce mean errors acceptable to the specifications of NMAS, the strictest application of these standards reveal that these products are not accurate enough to satisfy the USGS standards.