Geodataset Name:       TOPO2FT_CH2MHILL
Geodataset Type:       FILE GEODATABASE (ArcGIS 9.2 or later)
Geodataset Feature:    Polyline
Feature Count:         542193

DATA SOURCE(S):                    Florida Division of Emergency Management
SCALE OF ORIGINAL SOURCE MAPS:     24000
GEODATASET EXTENT:                 Broward, Miami-Dade, Martin, Monroe, Palm Beach, St Lucie

PUBLICATION DATE:                  2009
TIME PERIOD OF CONTENT:            Begin Date: 20080104    End Date: 20081002
DOWNLOAD LINK:                     http://www.fgdl.org/metadataexplorer/explorer.jsp

FEATURE ATTRIBUTE TABLES:

Datafile Name: TOPO2FT_CH2MHILL.DBF

FEATURE ATTRIBUTE TABLES CODES AND VALUES:

Item	Item Description
OBJECTID	Internal feature number.
SHAPE	Feature geometry.
CONTOUR_ELEVATION_MS	Elevation of represented contour in feet
CONTOUR_TYPE_DESC	Description of represented contour type 1 = Intermediate contours (the three or four lines between adjacent index contours) are about half the line weight of index contours. They are normally continuous throughout a map, but may be dropped or joined with an index contour where the slope is steep and where there is insufficient space to show all of the intermediate lines. 2 = Supplementary contours are used to portray important relief features that would otherwise not be shown by the index and intermediate contours (basic contours). They are normally added only in areas of low relief, but they may also be used in rugged terrain to emphasize features. Supplementary contours are shown as screened lines so that they are distinguishable from the basic contours, yet not unduly prominent on the published map. 3 = Depression contours are closed contours that surround a basin or sink. They are shown by right-angle ticks placed on the contour lines, pointed inward (down slope). Fill contours are a special type of depression contours, used to indicate an area that has been filled to support a road or railway grade. 4 = Index contours are defined as every 5th contour line. For example, with the Contour_2FT feature class, the first positive intermediate contour would be 0 with the following index contours at 10, 20, 30 feet, etc. 5 = INTERMEDIATE LOW CONFIDENCE 6 = SUPPLEMENTARY LOW CONFIDENCE 7 = DEPRESSION LOW CONFIDENCE 8 = INDEX LOW CONFIDENCE
DATESTAMP_DT	The date the feature was imported into the geodatabase
SOURCE	Abbreviated 3-letter code representing the data source. CDM = CDM CH2 = CH2MHILL MER = Merrick PDS = PDS WOO = Woolpert
FGDLAQDATE	Date GeoPlan acquired data from source
AUTOID	Unique ID added by GeoPlan
SHAPE.LEN	Length in meters

USER NOTES:

Contours (2-foot interval) were generated in Terrasolids' Terrascan. To create the contours, a 5-meter bare-earth LiDAR grid that included hydrographic, road, seawall, soft feature, and water body breaklines was used. When this process was complete ESRI's ArcInfo was used for topology validation. The contour data have been edge-matched to adjacent tiles in this project and automated testing has revealed that no contour lines cross themselves or others. The data exhibit spikes and on slopes and banks that are the result of trees and bushes that were not effectively filtered out of precursor source data. Pockets of trees result in complex areas of contouring that represent vegetation noise rather than any real variation in bare ground surface. Depression contours have been identified.

The Light Detection and Ranging (LiDAR) LAS dataset is a topographic survey conducted for the State of Florida Division of Emergency Management LiDAR Project. These data were produced for Florida Division of Emergency Management. Block 10 of the State of Florida Division of Emergency Management LiDAR Project consists of approximately 356 tiles. The LiDAR point cloud was flown at a density sufficient to support a maximum final post spacing of 4 feet for unobscured areas. 3001 Inc. acquired 164 flightlines on January 4, 2008 through January 31, 2008. The data was divided into 5000' by 5000' cells that serve as the final tiling scheme. The State of Florida Division of Emergency Management LiDAR Survey was collected under the guidance of a Professional Mapper /Surveyor.

GeoPlan relied on the integrity of the attribute information within the original data.

The metadata is not FGDC compliant if copies of the survey report in PDF format are not delivered as an attachment. The information in this report is the result of the LiDAR surveys performed on the dates indicated and the general conditions at that time.

Elevation contour data are a fundamental base map layer for large scale mapping and GIS analysis. The user should be aware that elevation contour models produced by computer are highly sensitive to the algorithm employed and the parameter of the algorithm. As a result, it is easily possible to get two differing results from the same source data. The algorithm and parameters employed to produce this contour model were deemed acceptable for reason of appearance and processing time. These data will also be acceptable for most 12000 scale maps.

The contours are based on a 5-meter bare-earth LiDAR grid that included hydrographic, road, seawall, soft feature, and water body breaklines.

The accuracy assessment was performed using a standard method to compute the root mean square error (RMSE) based on a comparison of ground control points (GCP) and filtered LiDAR data points. Filtered LiDAR data has had vegetation and cultural features removed and by analysis represents bare-earth elevations. . The RMSE figure was used to compute the vertical National Standard for Spatial Data Accuracy (NSSDA). Ground control was established by 3001, Inc. A spatial proximity analysis was used to select edited LiDAR data points contiguous to the relevant GCPs. A search radius decision rule is applied with consideration of terrain complexity, cumulative error and adequate sample size. Cumulative error results from the errors inherent in the various sources of horizontal measurement. These sources include the airborne GPS, GCPs and the uncertainty of the accuracy of the LiDAR data points. This accuracy is achieved prior to the sub-sampling that occurs through integration with the inertial measurement unit (IMU) positions that are recorded. It is unclear at this time whether the initial accuracy is maintained. The horizontal accuracy of the GCPs is estimated to be in the range of approximately 1 to 1.6 inches. Finally, sample size was considered. The specification for the National Standard for Spatial Data Accuracy is a minimum of 20 points to conduct a statistically significant accuracy evaluation (Minnesota Planning, 1999, Positional Accuracy Handbook, Minnesota Planning Land Management Information Center, St. Paul, Minnesota., p.3). Most statistical texts indicate that a minimum of 30 sample points provide a reasonable Approximation of a normal distribution. The intent of the NSSDA is to reflect the geographic area of interest and the distribution of error in the data set (Federal Geographic Data Committee, 1998, Geospatial National Standard for Spatial Data Accuracy, Federal Geographic Data Committee Secretariat, Reston, Virginia, p.3-4). Additional steps were taken to ensure the vertical accuracy Of the LiDAR data including: Step 1: Precision Bore sighting (Check Edge-matching) Step 2: Compare the LiDAR data to the Field Survey (Field survey is to FEMA specifications and more stringent internal specifications) Step 3: Automated Filtering Step 4: Manual Editing (Quality Control) Step 5: 3-D digitizing and Photogrammetric Compilation of hydrographic breaklines

The unaltered data may not be redistributed without all of the elements of the metadata listed in the Supplemental Information section of this metadata document. Acknowledgement of Florida Division of Emergency Management would be appreciated in products derived from these data.

The Florida Geographic Data Library is a collection of Geospatial Data compiled by the University of Florida GeoPlan Center with support from the Florida Department of Transportation. GIS data available in FGDL is collected from various state, federal, and other agencies (data sources) who are data stewards, producers, or publishers. The data available in FGDL may not be the most current version of the data offered by the data source. University of Florida GeoPlan Center makes no guarantees about the currentness of the data and suggests that data users check with the data source to see if more recent versions of the data exist. Furthermore, the GIS data available in the FGDL are provided 'as is'. The University of Florida GeoPlan Center makes no warranties, guaranties or representations as to the truth, accuracy or completeness of the data provided by the data sources. The University of Florida GeoPlan Center makes no representations or warranties about the quality or suitability of the materials, either expressly or implied, including but not limited to any implied warranties of merchantability, fitness for a particular purpose, or non-infringement. The University of Florida GeoPlan Center shall not be liable for any damages suffered as a result of using, modifying, contributing or distributing the materials. A note about data scale: Scale is an important factor in data usage. Certain scale datasets are not suitable for some project, analysis, or modeling purposes. Please be sure you are using the best available data. 1:24000 scale datasets are recommended for projects that are at the county level. 1:24000 data should NOT be used for high accuracy base mapping such as property parcel boundaries. 1:100000 scale datasets are recommended for projects that are at the multi-county or regional level. 1:125000 scale datasets are recommended for projects that are at the regional or state level or larger. Vector datasets with no defined scale or accuracy should be considered suspect. Make sure you are familiar with your data before using it for projects or analysis. Every effort has been made to supply the user with data documentation. For additional information, see the References section and the Data Source Contact section of this documentation. For more information regarding scale and accuracy, see our webpage at: http://geoplan.ufl.edu/education.html

REFERENCES:

http://www.floridadisaster.org/gis/LiDAR/index.htm Baseline Specifications for Orthophotography and LiDAR: http://www.floridadisaster.org/gis/specifications/Documents/BaselineSpecifications_1.2.pdf Standards for 1:24,000 Scale Digital Line Graphs: http://rockyweb.cr.usgs.gov/nmpstds/acrodocs/dlgqmap/7dqm0401.pdf

DATA LINEAGE SUMMARY:

The ABGPS, inertial measurement unit (IMU), and raw scans are collected during the LiDAR aerial survey. The ABGPS monitors the xyz position of the sensor and the IMU monitors the orientation. During the aerial survey laser pulses reflected from features on the ground surface are detected by the receiver optics and collected by the data logger. GPS locations are based on data collection receivers on the aircraft and base stations on the ground. The ground base stations are placed no more than 30 mile radius from the flight survey area. Process Date: 20080131 The ABGPS, IMU, and raw scans are integrated using proprietary software developed by the Leica Geosystems and delivered with the Leica ALS50 System. The resultant file is in a LAS binary file format. The LAS file version 1.1 format can easily transferred from one file format to another. It is a binary file format that maintains information specific to the LiDAR data (return#, intensity value, xyz, etc,). The resultant points are produced in the Florida State Plane East Zone coordinate system, with units in feet and referenced to the NAD83/90 HARN horizontal datum and NAVD88 vertical datum. Process Date: 20080131 The unedited data are classified to facilitate the application of the appropriate feature extraction filters. A combination of proprietary filters is applied as appropriate for the production of bare-earth digital terrain models (DTMs). Interactive editing methods are applied to those areas where it is inappropriate or impossible to use the feature extraction filters, based upon the design criteria and/or limitations of the relevant filters. These same feature extraction filters are used to produce elevation height surfaces. Process Date: 20080411 Filtered and edited data are subjected to rigorous QA/QC according to the 3001 Inc. Quality Control Plan and procedures. Very briefly, a series of quantitative and visual procedures are employed to validate the accuracy and consistency of the filtered and edited data. Ground control is established by 3001, Inc. and GPS-derived ground control points (GCPs) points in various areas of dominant and prescribed land cover. These points are coded according to landcover, surface material and ground control suitability. A suitable number of points are selected for calculation of a statistically significant accuracy assessment as per the requirements of the National Standard for Spatial Data Accuracy. A spatial proximity analysis is used to select edited LiDAR data points within a specified distance of the relevant GCPs. A search radius decision rule is applied with consideration of terrain complexity, cumulative error and adequate sample size. Accuracy validation and evaluation is accomplished using proprietary software to apply relevant statistical routines for calculation of Root Mean Square Error (RMSE) and the National Standard for Spatial Data Accuracy (NSSDA) according the Federal Geographic Data Committee (FGDC) specifications. Process Date: 20080901 Contours are a set of lines representing the same value of a selected attribute and forming an imaginary line. The terms contour or contour lines are most commonly used for lines connecting points on the ground having the same elevation. The contours were created using an ASCII Binary grid with breaklines embedded into the surface. Each grid included 50-meters of overlap to ensure continuity between tiles. After the contours are created, the overlap is cropped to the edge of the project / tile boundary. The contours are being delivered as an ArcGIS geodatabase with an elevation field and contour description / type identifier. In the preliminary processing of the LiDAR data into 1 and 2 foot contours, it was discovered that there were several locations where a contour line would follow the seam lines between flights of the LiDAR data. These contours at the flight seam lines were due to slight elevation differences between LiDAR data from adjacent seam lines. These elevation shifts were within the allowable vertical accuracy tolerances of the data. However, to mitigate this problem all flight line overlap of LiDAR data was removed (set to class 12) for blocks 9 and 10 and the contours were generated from the break line and LiDAR data without the overlap. Even though this removed most of the seam line following contours, there are several locations in blocks 9 and 10 where this still occurs. The root cause of these remaining within tolerance elevations shifts in LiDAR data across some flight lines is unknown, although there is evidence of tidal influence based on the fact that the adjacent flight lines at these locations have significantly differing time stamps. Process Date: 20080930 GeoPlan received this data via hard drive from Jones Edmunds on 8/27/09. The Florida Division of Emergency Management contracted this data out to CH2MHill. When received the data was in a series of file geodatabases. The data was merged into 1 file geodatabase and clipped to the appropriate county boundary. The feature class was projected from NAD83 HARN State Plane East - feet to Albers HPGN. -Added SOURCE field and populated all values to CH2 -Added FGDLAQDATE field based on date GeoPlan acquired data from source -Changed name from Block#_CH2MHILL.CONTOUR_2ft to TOPO2FT_county Process Date: 20091103

MAP PROJECTION PARAMETERS:

Projection                          ALBERS
Datum                               HPGN
Units                               METERS
Spheroid                            GRS1980
1st Standard Parallel               24  0  0.000
2nd Standard Parallel               31 30  0.000
Central Meridian                   -84 00  0.000
Latitude of Projection's Origin     24  0  0.000
False Easting (meters)              400000.00000
False Northing (meters)             0.00000

DATA SOURCE CONTACT (S):

Name:
Abbr. Name:
Address:


Phone:

Web site:
E-mail:
Contact Person:
         Phone:
        E-mail:

Florida Division of Emergency Management
FDEM
2555 Shumard Oak Boulevard
Tallahassee, FL
32399-2100
850-413-9907


http://www.floridadisaster.org/gis
richard.butgereit@em.myflorida.com
Richard Butgereit

Name:                   FLORIDA GEOGRAPHIC DATA LIBRARY
Abbr. Name:             FGDL
Address:                Florida Geographic Data Library
                        431 Architecture Building
                        PO Box 115706
                        Gainesville, FL  32611-5706
Web site:               http://www.fgdl.org

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