Orlando Planning Land Use

The FDOT GIS Maximum Speed Limits provides spatial information Maximum Speed Limits on Florida Roadways. It is required for all designated roadways on the SHS and HPMS samples. This dataset is maintained by the Transportation Data & Analytics office (TDA). The source spatial data for this hosted feature layer was created on: 11/22/2025.For more details please review the FDOT RCI Handbook Download Data: Enter Guest as Username to download the source shapefile from here: https://ftp.fdot.gov/file/d/FTP/FDOT/co/planning/transtat/gis/shapefiles/maxspeed.zip

River hydraulic geometry is an important input to hydraulic and hydrologic models that route flow along streams, determine the relationship between stage and discharge, and map the potential for flood inundation give the flow in a stream reach. Traditional approaches to quantify river geometry have involved river cross-sections, such as are required for input to the HEC-RAS model. Extending such cross-section based models to large scales has proven complex, and, in this presentation, an alternative approach, the Height Above Nearest Drainage, or HAND, is described. As we have implemented it, HAND uses multi-directional flow directions derived from a digital elevation model (DEM) using the Dinifinity method in TauDEM software (http://hydrology.usu.edu/taudem) to determine the height of each grid cell above the nearest stream along the flow path from that cell to the stream. With this information, and the depth of flow in the stream, the potential for and depth of flood inundation can be determined. Furthermore, by dividing streams into reaches or segments, the area draining to each reach can be isolated and a series of threshold depths applied to the grid of HAND values in that isolated reach catchment, to determine inundation volume, surface area and wetted bed area. Dividing these by length yields reach average cross section area, width, and wetted perimeter. Together with slope (also determined from the DEM) and roughness (Manning's n) these provide all the inputs needed for establishing a Manning's equation uniform flow assumption stage-discharge rating curve and for mapping potential inundation from discharge. This presentation will describe the application of this approach across the continental US in conjunction with NOAA’s National Water Model for prediction of stage and flood inundation potential in each of the 2.7 million reaches of the National Hydrography Plus (NHDPlus) dataset, the vast majority of which are ungauged. The continental US scale application has been enabled through the use of high performance parallel computing at the National Center for Supercomputing Applications (NCSA) and the CyberGIS Center at the University of Illinois.

Presentation at 2018 AWRA Spring Specialty Conference: Geographic Information Systems (GIS) and Water Resources X, Orlando, Florida, April 23-25, http://awra.org/meetings/Orlando2018/.

This Multi-Year Model GWLF-E/Mapshed model for the Eagleville Watershed was generated as a demonstration of WikiWatershed toolkit functionality applied to watersheds delineated using the Rapid Watershed delineation approach described in a presentation at the 2018 AWRA Spring Specialty Conference: Geographic Information Systems (GIS) and Water Resources X, Orlando, Florida, April 23-25, http://awra.org/meetings/Orlando2018/.

Tarboton, D. G., N. Sazib and A. Aufdenkampe, (2018), "The Model My Watershed Rapid Watershed Delineation Tool " 2018 AWRA Spring Specialty Conference: Geographic Information Systems (GIS) and Water Resources X, Orlando, Florida, April 23-25, http://awra.org/meetings/Orlando2018/. https://www.hydroshare.org/resource/d752efeae812478898fb78327f25c87c/

The GDAL/OGR libraries are open-source, geo-spatial libraries that work with a wide range of raster and vector data sources. One of many impressive features of the GDAL/OGR libraries is the ViRTual (VRT) format. It is an XML format description of how to transform raster or vector data sources on the fly into a new dataset. The transformations include: mosaicking, re-projection, look-up table (raster), change data type (raster), and SQL SELECT command (vector). VRTs can be used by GDAL/OGR functions and utilities as if they were an original source, even allowing for chaining of functionality, for example: have a VRT mosaic hundreds of VRTs that use look-up tables to transform original GeoTiff files. We used the VRT format for the presentation of hydrologic model results, allowing for thousands of small VRT files representing all components of the monthly water balance to be transformations of a single land cover GeoTiff file.

Presentation at 2018 AWRA Spring Specialty Conference: Geographic Information Systems (GIS) and Water Resources X, Orlando, Florida, April 23-25, http://awra.org/meetings/Orlando2018/

https://stars.library.ucf.edu/cfm-images/1991ContributorsOrlando Chamber of CommerceDescriptionStreet Map of Orlando, Florida, authorized by the Orlando Chamber of Commerce.Date1925SubjectsStreets -- Florida -- Orlando.; Orlando (Fla.) -- Historical geography -- Maps.; Real Property -- Florida -- Orlando -- Maps.

AWRA GIS & Water Resources X: Spatial Analysis of Watersheds: Ecological, Hydrological and Societal Responses April 22 – 25, 2018 Abstract Title: LiDAR and Wetlands: Acquisition Guidelines for these Challenging Landforms Presenter: Sandra Fox, SJRWMD Co-authors: Keith Paterson, Dewberry; Nick Kules, Dewberry; Kimberli Ponzio, SJRWMD; Steven J. Miller, SJRWMD; Richard Guilfoyle, SJRWMD; Bill Van Sickle, SJRWMD; James Walters, SJRWMD; Sherry Brandt-Williams, SJRWMD, Al Karlin, SWFWMD

Abstract included in Topical Session Topical Session Title: New and Emerging LiDAR Technologies: High Density and TopoBathymetric LiDAR Sensors (organized by Dr. Al Karlin, SWFWMD)

Abstract: As part of a topical session devoted to new and emerging Light Detection and Ranging (LiDAR) technologies, this presentation focuses on the challenges present when wetlands are a major component of the landscape, particularly in Florida. Examples: A “standard” driver for determining acquisition timing has been “leaf off” conditions, which may not be relevant in our sunny clime especially in wetlands. A far more relevant driver is hydrology. Wetlands are not always “wet”; simple models based on historical stage records are being used in the Upper St Johns River Basin (USJRB) to “fly when it’s dry” – a better driver for LiDAR acquisition. The problem of dense vegetation obscuring true ground has been successfully addressed with high point densities and 55% flight overlap, among other sensor specifications. Lastly, successful results involving reprocessing and recalibrating older (2012) LiDAR data, also in USJRB wetlands (at a significant cost savings compared to re-flying the project area) will be presented.

Presentation at 2018 AWRA Spring Specialty Conference: Geographic Information Systems (GIS) and Water Resources X, Orlando, Florida, April 23-25, http://awra.org/meetings/Orlando2018/

Overview:This document describes the 2021 accessibility data released by the Accessibility Observatory at the University of Minnesota. The data are included in the National Accessibility Evaluation Project for 2021, and this information can be accessed for each state in the U.S. at https://access.umn.edu/research/america. The following sections describe the format, naming, and content of the data files.Data Formats: The data files are provided in a Geopackage format. Geopackage (.gpkg) files are an open-source, geospatial filetype that can contain multiple layers of data in a single file, and can be opened with most GIS software, including both ArcGIS and QGIS.Within this zipfile, there are six geopackage files (.gpkg) structured as follows. Each of them contains the blocks shapes layer, results at the block level for all LEHD variables (jobs and workers), with a layer of results for each travel time (5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60 minutes). {MPO ID}_tr_2021_0700-0859-avg.gpkg = Average Transit Access Departing Every Minute 7am-9am{MPO ID}_au_2021_08.gpkg = Average Auto Access Departing 8am{MPO ID}_bi_2021_1200_lts1.gpkg = Average Bike Access on LTS1 Network{MPO ID}_bi_2021_1200_lts2.gpkg = Average Bike Access on LTS2 Network{MPO ID}_bi_2021_1200_lts3.gpkg = Average Bike Access on LTS3 Network{MPO ID}_bi_2021_1200_lts4.gpkg = Average Bike Access on LTS4 NetworkFor mapping and geospatial analysis, the blocks shape layer within each geopackage can be joined to the blockid of the access attribute data. Opening and Using Geopackages in ArcGIS:Unzip the zip archiveUse the "Add Data" function in Arc to select the .gpkg fileSelect which layer(s) are needed — always select "main.blocks" as this layer contains the Census block shapes; select any other attribute data layers as well.There are three types of layers in the geopackage file — the "main.blocks" layer is the spatial features layer, and all other layers are either numerical attribute data tables, or the "fieldname_descriptions" metadata layer. The numerical attribute layers are named with the following format:[mode]_[threshold]_minutes[mode] is a two-character code indicating the transport mode used[threshold] is an integer indicating the travel time threshold used for this data layerTo use the data spatially, perform a join between the "main.blocks" layer and the desired numerical data layer, using either the numerical "id" fields, or 15-digit "blockid" fields as join fields.

The Surficial Aquifer System (SAS) depth to water table surface grid was created by subtracting the water table surface grid from the DEM.

Historical imagery was obtained from University of Florida’s historical Imagery site, “Aerial Photography: Florida”, the Florida Department of Transportation (FDOT) Aerial Photo Lookup System, or from the FDEP district offices. Images downloaded from UF were saved locally and georeferenced by GIS team members, whereas the imagery received from the district offices were georeferenced by District staff. It is understood that these "pre-georeferenced" tiles were georeferenced within ArcMap by various staff from the District offices. The following applies to the imagery georeferenced in-office by the Division of Water Resource Management (DWRM):The georeferencing was completed in either ArcMap 10.3.1 or ArcGIS Pro. The following standards were held for the georeferencing process: the minimum number of control points was 10 points. The RMS value was kept at or below 5.0 for all tiles georeferenced in 1st Order Polynomial, and 2.0 for those georeferenced in 2nd Order Polynomial (where 1st Order was not possible). The maximum individual residual was at or under twice the RMS. Again, these were the standards, but the accuracy is not guaranteed. To QC for human error, once all counties for the given decade were georeferenced a comparison task was completed. This QC emphasized that this data is only a visual aid in that distances can be off 50 meters or more in some areas. These are mostly areas where there were limited reference features to georectify the original images. The smallest distance found was under 10 meters. To attain more information on this QC please contact FDEP WRM GIS. As stated in the use limitation, but emphasized here, information contained herein is provided for informational purposes only. The State of Florida, Department of Environmental Protection provides geographic information systems (GIS) data and metadata with no claim as to the completeness, usefulness, or accuracy of its content, positional or otherwise. The State and its officials and employees make no warranty, express or implied, and assume no legal liability or responsibility for the ability of users to fulfill their intended purposes in accessing or using GIS data or metadata or for omissions in content regarding such data. The data could include technical inaccuracies and typographical errors. The data is presented "as is," without warranty of any kind, including, but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. Your use of the information provided is at your own risk. In providing this data or access to it, the State assumes no obligation to assist the user in the use of such data or in the development, use, or maintenance of any applications applied to or associated with the data or metadata.Please contact GIS.Librarian@FloridaDEP.gov for more information.