2018 Miami-Dade ITD Lidar: Miami-Dade County, FL

Create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base. Change to an orthometric vertical datum is one of the many options.

Bulk download of data files in LAZ format, geographic coordinates, orthometric heights. Note that the vertical datum (hence elevations) of the files here are different than described in this document. They will be in an orthometric datum.

The Data Access Viewer (DAV) allows a user to search for and download elevation, imagery, and land cover data for the coastal U.S. and its territories. The data, hosted by the NOAA Office for Coastal Management, can be customized and requested for free download through a checkout interface. An email provides a link to the customized data, while the original data set is available through a link within the viewer.

This graphic displays the footprint for this lidar data set.

Link to data set report.

Link to the data set breaklines.

Link to custom download, from the Data Access Viewer (DAV), the raster Digital Elevation Model (DEM) data that were created from this lidar data set.

GPI Geospatial Inc.

The project was divided in two phases: Collection and classification of LiDAR data; and creation of 5-foot cell spaced hydro enforced mosaic DEM of the project area. The LiDAR data was collected utilizing a Riegl VQ-1560i in a Cessna 206 from an approximate altitude of 4,200 feet above ground level, at an approximate ground speed of 110 knots at a pulse rate repetition of 2000 kHg, resulting in an average of 15.2 points per square meter single swath and 20 plus with the 55% overlap. To get under the cloud ceiling some flight lines were collected at 2,000 feet agl at 110 knots. These lines were collected at 29.12 points per square meter single swath. The sensor used a 60-degree field of view. The project was flown to have 55 percent overlap between swaths. The Global Positioning System (GPS) data were processed using Applanix POSPac Mapping Suite version 8.3 using Smart Base method and single base methods. A fixed bias carrier phase solution was computed in forward and reverse directions. The LiDAR collection took place when Positional Dilution of Precision (PDOP) was at or below 3. Occasionally, the PDOP rose slightly above 3. This had no effect on the data. The GPS trajectory was combined with the IMU data using the Applanix POSPac software. The resulting Smoothed Best Estimate of Trajectory (SBET) was exported and used in Riegl RiProcess software to compute the laser mass point positions in Northing, Easting, and Elevations coordinates.

The raw laser data were merged with the SBET using Riegl RiProcess software. The data set was processed using RiProcess, RiAnalyze, and RiWorld software where each flight line was processed to a point cloud. The data was adjusted flight line to flight line using Riegl’s Scan Data Adjustment tool to ensure a proper relative calibration match between flight lines. Each flight was checked for project coverage, data gaps between overlapping flight lines, point density and then exported in LAS 1.4 format. The entire project was collected without gaps.

The LAS files were projected to the NAD_1983_2011_StatePlane_Florida_East_FIPS_0901_Feet and North American Vertical Datum of 1988 (NAVD88). Ellipsoidal heights were converted to orthometric heights using the current Geiod12B. The LAS files were imported to TerraSolid, LTD TerraScan software to be classified to bare earth ground and later feature coded to USGS specifications. The LAS files contain 12 classifications: 1 = unclassified; 2 = ground; 3 = low veg; 4 = med veg; 5 = high veg; 6 = building; 7 = noise points; 9 = water; 10 = buffered ground points surrounding breaklines; 12 = overlap; 17 = overpass and bridges; 18 = high noise. The LiDAR data was run through an automated ground and building classification using terrascan software. A manual check of the building classification was done. The vegetation heights were assigned by an automated process after the bare-earth and buildings were classified. No manual classification of the vegetation class was performed on this data set. Breaklines were digitized from the LiDAR data in Microstation and elevations were assigned using LP360 and ArcGIS. The double line linear hydrographic features were hydro-enforced with downhill constraints to model correct flow patterns. Water bodies were hydro-flattened to ensure uniform elevation across the feature. DEMs were created using QCoherent LP360 software. The bare-earth LAS data was loaded into the software along with the tile layout and hydro shapefile collected from the LAS data set. DEMS were produced at a 5ft cell size and hydro-flattened. To QC the DEMs Global Mapper was used to check for completeness of the tiles and that the hydro features were flattened and represented correct elevations. Once the QC was complete the files were exported out of ArcGIS to create Arc DEM.

COLLECTION DATES: 4/25/18, 4/26/18, 4/29/18, 4/30/18, 5/01/18, 6/05/18, 6/06/18, 6/22/18, 12/05/18

173 flight lines of data were collected.

The NOAA Office for Coastal Management (OCM) received 10,904 files in las format from the Miami-Dade Information Technology Department (ITD). The lidar data had elevation and intensity measurements. The data were in FL State Plane East, Zone 0901, NAD83 (2011), US survey foot coordinates and NAVD88 (GEOID12B) elevations in feet. The data were classified as: 1 - Unclassified, 2 - Ground, 3 - Low vegetation (0 -5 ft), 4 - Medium Vegetation (5 - 25 ft), 5 - High Vegetation (above 25 feet), 6 - Buildings, 7 - Noise, 9 - Water, 10 - Buffered Ground surrounding breaklines, 17 - Overpasses and Bridges, 18 - High Noise. Although the accompanying metadata and report indicated that there were class 12 - Overlap points, an internal OCM script did not find any points with this classification. OCM processed the 1, 2, 3, 4, 5, 6, 7, 9, 10, 17, and 18 point classes to the Digital Coast Data Access Viewer (DAV).

OCM performed the following processing on the data for Digital Coast storage and provisioning purposes:

1. The data were converted to laz format using laszip

2. Internal OCM scripts were run to check the number of points by classification and by flight ID and the gps, elevation, and intensity ranges.

3. Internal OCM scripts were run on the laz files to:

a. Convert from orthometric (NAVD88) elevations to ellipsoid elevations using the Geoid12B model

b. Convert from FL State Plane East Zone 0901 (NAD83 2011), US survey foot coordinates to geographic coordinates

c. Convert from vertical units of feet to meters

d. Filter points outside the elevation range of -100 to 2000 feet

e. Filter points outside the geographic range of the bounding coordinates of -82, 24, -79, 28 degrees

f. Assign the geokeys, to sort the data by gps time and zip the data to database and to http.