2015 NRCS/MDEQ QL2 Lidar: Southeast MS

Mississippi QL2 Lidar 0.7m NPS Lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G14PD01046 Woolpert Order No. 74853 CONTRACTOR: Woolpert, Inc. This task is for a high resolution data set of lidar covering approximately 4385 square miles. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, one (1) meter pixel raster DEMs of the bare-earth surface in ERDAS IMG Format, and 8-bit intensity images. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format, and LAS swath data. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off.

This metadata record supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data set, the DAV is leveraging the Entwine Point Tiles (EPT) hosted by USGS on Amazon Web Services.

Provide elevation data for southeast Mississippi.

10471

<ldrinfo>

<ldrspec>USGS NGP Base Specifications v1</ldrspec>

<ldrsens>Leica ALS70</ldrsens>

<ldrmaxnr>4</ldrmaxnr>

<ldrnps>0.7</ldrnps>

<ldranps>0.7</ldranps>

<ldrdens>2</ldrdens>

<ldradens>2</ldradens>

<ldrfltht>1981</ldrfltht>

<ldrfltsp>150</ldrfltsp>

<ldrscana>40</ldrscana>

<ldrscanr>41</ldrscanr>

<ldrpulsr>272</ldrpulsr>

<ldrpulsd>5</ldrpulsd>

<ldrpulsw>1.5</ldrpulsw>

<ldrwavel>1064</ldrwavel>

<ldrmpia>1</ldrmpia>

<ldrbmdiv>0.22</ldrbmdiv>

<ldrswatw>1443</ldrswatw>

<ldrswato>25</ldrswato>

<ldrcrs>NAD_1983(2011)_UTM_Zone_16N_Meters</ldrcrs>

<ldrgeoid>GEOID12A</ldrgeoid>

</ldrinfo>

<ldraccur>

<ldrchacc>0.36</ldrchacc>

<rawfva>0.158</rawfva>

<clsfva>0.150</clsfva>

<clscva>0.232</clscva>

<clssvas>

<svalctyp>Urban Land Cover </svalctyp>

<svavalue>0.114</svavalue>

</clssvas>

<clssvas>

<svalctyp>Tall Grass Land Cover </svalctyp>

<svavalue>0.238</svavalue>

</clssvas>

<clssvas>

<svalctyp>Brushlands/Trees Land </svalctyp>

<svavalue>0.249</svavalue>

</clssvas>

<clssvas>

<svalctyp>Forested and Fully Grown Land Cover </svalctyp>

<svavalue>0.237</svavalue>

</clssvas>

<clssvas>

<svalctyp>Swamp Land Cover </svalctyp>

<svavalue>0.136</svavalue>

</clssvas>

</ldraccur>

<lasinfo>

<lasver>1.2</lasver>

<lasprf>6</lasprf>

<laswheld>Geometrically unreliable points were identified using a combination of automated and manual techniques and subsequently classified as noise.</laswheld>

<lasolap>Swath overlap points were identified in these files by adding 16 to the standard classication values yielding overlap default and overlap ground.</lasolap>

<lasintr>8</lasintr>

<lasclass>

<clascode>1</clascode>

<clasitem>default/unclassified</clasitem>

</lasclass>

<lasclass>

<clascode>2</clascode>

<clasitem>Bare-earth</clasitem>

</lasclass>

<lasclass>

<clascode>7</clascode>

<clasitem>Noise</clasitem>

</lasclass>

<lasclass>

<clascode>9</clascode>

<clasitem>Water</clasitem>

</lasclass>

<lasclass>

<clascode>10</clascode>

<clasitem>Ignored ground</clasitem>

</lasclass>

<lasclass>

<clascode>17</clascode>

<clasitem>Overlap Default</clasitem>

</lasclass>

<lasclass>

<clascode>18</clascode>

<clasitem>Overlap Ground</clasitem>

</lasclass>

</lasinfo>

Lidar points in LAZ format (Classes 1,2,7,9,10,17,18)

none

Any conclusions drawn from the analysis of this information are not the responsibility of USDA-NRCS, MDEQ, Wooolpert, NOAA, the Office for Coastal Management or its partners.

To the extent possible under law, the U.S. Government has waived all copyright and related or neighboring rights to this dataset.

Data is available online for bulk and custom downloads.

None

Users should be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations. These data depict the heights at the time of the survey and are only accurate for that time.

Compiled to meet 0.36 meters horizontal accuracy at 95 percent confidence level.

The vertical accuracy statistics were calculated by comparison of the lidar bare earth points to the ground surveyed QA/QC points. Mississippi QL2 Lidar was processed and delivered in NAD1983(2011) UTM16, NAVD88 Geoid12A meters. Data deliverables were reprojected and also delivered in NAD1983(2011) UTM15, NAVD88 Geoid12A meters. It should be noted that accuracy analysis was reported for the UTM16 data.

Raw LAS Swath Fundamental Vertical Accuracy (FVA) Tested 0.158 meters fundamental vertical accuracy at a 95 percent confidence level, derived according to NSSDA, in open terrain using (RMSEz) x 1.96000 as defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using National Digital Elevation Program (NDEP)/ASPRS Guidelines and tested against the TIN using all points.

Bare-Earth DEM Fundamental Vertical Accuracy (FVA) Tested 0.162 meters fundamental vertical accuracy at a 95 percent confidence level, derived according to NSSDA, in open terrain using (RMSEz) x 1.96000 as defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using National Digital Elevation Program (NDEP)/ASPRS Guidelines and tested against the DEM.

Supplemental Vertical Accuracy Assessments

Urban Land Cover Classification Supplemental Vertical Accuracy (SVA) Tested 0.114 meters supplemental vertical accuracy at the 95th percentile in the Urban supplemental class reported using National Digital Elevation Program (NDEP)/ASPRS Guidelines and tested against the DEM.

Tall Grass Land Cover Classification Supplemental Vertical Accuracy (SVA) Tested 0.238 meters supplemental vertical accuracy at the 95th percentile in the Tall Weeds/Crops supplemental class reported using National Digital Elevation Program (NDEP)/ASPRS Guidelines and tested against the DEM. There were no Tall Grass Errors exceeding the 95th percentile.

Brushlands/Trees Land Cover Classification Supplemental Vertical Accuracy (SVA) Tested 0.249 meters supplemental vertical accuracy at the 95th percentile in the Brushlands/Trees supplemental class reported using National Digital Elevation Program (NDEP)/ASPRS Guidelines and tested against the DEM.

Forested and Fully Grown Land Cover Classification Supplemental Vertical Accuracy (SVA) Tested 0.237 meters supplemental vertical accuracy at the 95th percentile in the Forested/Fully Grown supplemental class reported using National Digital Elevation Program (NDEP)/ASPRS Guidelines and tested against the DEM.

Swamp Land Cover Classification Supplemental Vertical Accuracy (SVA) Tested 0.136 meters supplemental vertical accuracy at the 95th percentile in the Forested/Fully Grown supplemental class reported using National Digital Elevation Program (NDEP)/ASPRS Guidelines and tested against the DEM.

Consolidated Vertical Accuracy Assessment

Consolidated Vertical Accuracy (CVA) Tested 0.232 meters consolidated vertical accuracy at the 95th percentile level; reported using National Digital Elevation Program (NDEP)/ASPRS Guidelines and tested against the DEM. CVA is based on the 95th percentile error in all land cover categories combined

The LiDAR data is visually inspected for completeness to ensure that are no gaps between flight lines.

All formatted data are validated using commercial GIS software to ensure proper formatting and loading prior to delivery.

The NOAA Office for Coastal Management (OCM) ingested references to the USGS Entwine Point Tiles (EPT) hosted on Amazon Web Services (AWS) into the Digital Coast Data Access Viewer (DAV). The DAV accesses the point cloud as it resides on AWS under the usgs-lidar-public-container.