2015 FEMA Lidar: Region 2 NY Great Lakes Area

Aerial Cartographics of America (ACA) collected 2233 square miles in the New York counties of Chautauqua, Orleans, Wayne, Cayuga, Jefferson, Oswego and St. Lawrence. The nominal pulse spacing for this project was no greater than 0.7 meters. Dewberry used proprietary procedures to classify the LAS into an initial ground surface. Dewberry then used proprietary procedures to classify the LAS and performed manual classifications according to project specifications: 1-Unclassified, 2-Ground, 7-Noise, 9-Water, 10-Ignored Ground due to breakline proximity, 11- Witheld. The LiDAR data were processed to a bare-earth digital terrain model (DTM). Detailed breaklines and bare-earth Digital Elevation Models (DEMs) were produced for the project area. Deliverables were produced in NAD83 (2011) UTM Zone 18, meters and NAVD88 (geoid 12a), meters. The data was formatted according to the USNG Tile naming convention with each tile covering an area of 1,500 meters by 1,500 meters.

The NOAA Office for Coastal Management (OCM) downloaded:

2344 laz files from ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/USGS_LPC_NY_GreatLakes_Phase2_L3_2014_LAS_2017/

218 laz files from ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/USGS_LPC_NY_FEMA_R2L1_ChautauquaCo_2014_LAS_2017/

507 laz files from ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/USGS_LPC_NY_FEMA_R2L2_OrleansCo_2014_LAS_2017/ (Two files from this source were later determined to be corrupt and were removed from the the NOAA OCM Data Access Viewer (DAV) database and the bulk download AWS S3 site. Valid files were downloaded from the Discover GIS Data NY site (https://orthos.dhses.ny.gov/) and processed to provide a complete dataset).

and processed the data to the Data Access Viewer (DAV) and https. OCM noted that along the Chautauqua and Orleans County shoreline, there are points that fall in Lake Erie and Lake Ontario that are classified as ground.

Hydro breaklines are also available. These data are available for download at the link provided in the URL section of this metadata record. Please note that these products have not been reviewed by the NOAA Office for Coastal Management (OCM) and any conclusions drawn from the analysis of this information are not the responsibility of NOAA or OCM.

The purpose of this LiDAR data was to produce high accuracy 3D elevation products, including tiled LiDAR in LAS 1.2 format, 3D breaklines, 1 meter cell size hydro flattened Digital Elevation Models (DEMs) and 1 foot contours. All products follow and comply with USGS Program Lidar Base Specification Version 1.0.

A complete description of this dataset is available in the Final Project Report submitted to the USGS.

The following are the USGS lidar fields in JSON:

{

"ldrinfo" : {

"ldrspec" : "USGS-NGP Lidar Base Specification V1.0",

"ldrsens" : "Riegl 680i/Riegl 780i",

"ldrmaxnr" : "7",

"ldrnps" : "0.38",

"ldrdens" : "7.00",

"ldranps" : "0.38",

"ldradens" : "7.00",

"ldrfltht" : "853",

"ldrfltsp" : "100",

"ldrscana" : "60",

"ldrscanr" : "92",

"ldrpulsr" : "260",

"ldrpulsd" : "3",

"ldrpulsw" : "0.351",

"ldrwavel" : "1550",

"ldrmpia" : "1",

"ldrbmdiv" : "0.5",

"ldrswatw" : "985.7",

"ldrswato" : "55",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid12A"

},

"ldraccur" : {

"ldrchacc" : "0.1813",

"rawnva" : "0.169",

"rawnvan" : "23",

"clsnva" : "0.169",

"clsnvan" : "23",

"clsvva" : "0.227",

"clsvvan" : "106"

},

"lasinfo" : {

"lasver" : "1.2",

"lasprf" : "1",

"laswheld" : "Withheld points are classified to class 11 per project specifications",

"lasolap" : "Swath overage points were not identified in these files using the standard LAS overlap bit",

"lasintr" : "16",

"lasclass" : {

"clascode" : "1",

"clasitem" : "Processed, but unclassified"

},

"lasclass" : {

"clascode" : "2",

"clasitem" : "Bare earth, ground"

},

"lasclass" : {

"clascode" : "7",

"clasitem" : "Noise"

},

"lasclass" : {

"clascode" : "9",

"clasitem" : "Water"

},

"lasclass" : {

"clascode" : "10",

"clasitem" : "Ignored ground due to breakline proximity"

},

"lasclass" : {

"clascode" : "11",

"clasitem" : "Withheld points +/- 20 degree scan angle"

}

}}

none

This data was produced for the U.S. Geological Survey according to specific project requirements. This information is provided "as is". Further documentation of this data can be obtained by contacting: USGS, 1400 Independence Road, Rolla, MO 65401. Telephone (573) 308-3756

Any conclusions drawn from the analysis of this information are not the responsibility of USGS, FEMA, NOAA, the Office for Coastal Management or its partners.

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.

Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 3; ESRI ArcCatalog 10.1

Lidar source produced to meet 1 meter horizontal accuracy.

Project specifications required a horizontal accuracy of 1 m based on a RMSEr (0.578m) x 1.7308. Only checkpoints photo-identifiable in the intensity imagery can be used to test the horizontal accuracy of the LiDAR. Photo-identifiable checkpoints in intensity imagery typically include checkpoints located at the ends of paint stripes on concrete or asphalt surfaces or checkpoints located at 90 degree corners of different reflectivity, e.g. a sidewalk corner adjoining a grass surface. The xy coordinates of checkpoints, as defined in the intensity imagery, are compared to surveyed xy coordinates for each photo-identifiable checkpoint. These differences are used to compute the tested horizontal accuracy of the LiDAR. As not all projects contain photo-identifiable checkpoints, the horizontal accuracy of the LiDAR cannot always be tested. LiDAR vendors perform calibrations on the LiDAR sensor and compare data to adjoining flight lines to ensure LiDAR meets the 1 meter horizontal accuracy standard at the 95% confidence level.

However, Dewberry tested the horizontal accuracy of the LiDAR by comparing photo-identifiable survey checkpoints to the LiDAR Intensity Imagery. As only eleven (11) checkpoints were photo-identifiable, the results are not statistically significant enough to report as a final tested value but the results of this testing are shown below.

Using NSSDA methodology, horizontal accuracy at the 95% confidence level (called Accuracyr) is computed by the formula RMSEr x 1.7308. The dataset for the New York Great Lakes LiDAR project satisfies the criteria:

Lidar dataset tested 0.843 m horizontal accuracy at 95% confidence level, based on RMSEr (0.487 m) x 1.7308.

The final vertical accuracy has been calculated for the full project area covering all counties using all surveyed checkpoints. The final vertical accuracy of the LiDAR was tested by Dewberry with 106 independent survey checkpoints. The survey checkpoints were evenly distributed throughout the project area and were located in areas of bare earth and open terrain (23), grass weeds and crops (21), brush and low trees (21), forested and fully grown (20), and urban (21). The vertical accuracy of the LiDAR was tested by comparing survey checkpoints to a triangulated irregular network (TIN) that is created from the LiDAR points. Checkpoints are always compared to interpolated surfaces created from the LiDAR point cloud because it is unlikely that a survey checkpoint will be located at the location of a discrete LiDAR point.

Checkpoints in open terrain were used to compute the Fundamental Vertical Accuracy (FVA). Project specifications required a FVA of 0.181 m based on a RMSEz (0.0925m) x 1.9600. All checkpoints were used to compute the Consolidated Vertical Accuracy (CVA). Project specifications required a CVA of 0.269 m based on the 95th percentile. Supplemental Vertical Accuracy (SVA) was computed on each individual land cover category other than open terrain. Target specifications for SVA are 0.269 m based on the 95th percentile. NDEP and ASPRS testing methodologies allow individual SVA's to fail as long as the mandatory CVA passes project specifications.

FVA

Based on the vertical accuracy testing conducted by Dewberry, using NSSDA and FEMA methodology, vertical accuracy at the 95% confidence level (called Accuracyz) is computed by the formula RMSEz x 1.9600. The dataset satisfies the criteria: tested 0.169 m vertical accuracy at 95% confidence level in open terrain, based on RMSEz (0.086 m) x 1.9600.

CVA

Based on the vertical accuracy testing conducted by Dewberry, using NDEP and ASPRS methodology, consolidated vertical accuracy (CVA) is computed using the 95th percentile method. The dataset satisfies the criteria: tested 0.227 m consolidated vertical accuracy at 95th percentile in all land cover categories combined. The 5% outliers consist of 6 checkpoints that are larger than the 95th percentile. These checkpoints have DZ values ranging between +0.230 m to +0.388 m.

SVA (Forested, Fully Grown)

Based on the vertical accuracy testing conducted by Dewberry, using NDEP and ASPRS methodology, supplemental vertical accuracy (SVA) is computed using the 95th percentile method. The dataset satisfies the criteria: tested 0.224 m m supplemental vertical accuracy at 95th percentile in the forested and fully grown land cover category.

SVA (Urban)

Based on the vertical accuracy testing conducted by Dewberry, using NDEP and ASPRS methodology, supplemental vertical accuracy (SVA) is computed using the 95th percentile method. The dataset satisfies the criteria: tested 0.121 m supplemental vertical accuracy at 95th percentile in the urban land cover category.

SVA (Grass, Weeds, Crops)

Based on the vertical accuracy testing conducted by Dewberry, using NDEP and ASPRS methodology, supplemental vertical accuracy (SVA) is computed using the 95th percentile method. The dataset satisfies the criteria: tested 0.328 m supplemental vertical accuracy at 95th percentile in the grass, weeds, and crops land cover category.

SVA (Brush, Trees)

Based on the vertical accuracy testing conducted by Dewberry, using NDEP and ASPRS methodology, supplemental vertical accuracy (SVA) is computed using the 95th percentile method. The dataset satisfies the criteria: tested 0.290 m supplemental vertical accuracy at 95th percentile in the brush land and trees land cover category.

A visual qualitative assessment was performed to ensure data completeness and bare earth data cleanliness. The data passes vertical accuracy specifications. One tile in the final delivered tile grid did not have an associated LAS file. Tile 18TVP8580980 is located in an area that the acquistion provider was unable to collect due to restricted airspace limitations. All gaps due to restricted air space are documented in the project report and a shapefile showing the locations of these gaps is provided with the data deliverables.

Data covers the tile scheme provided for the project area.

The laz files for this dataset were downloaded mainly from the USGS rockyweb site: https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/FEMA_Region_2_NY_Great_Lakes_Area_QL2_LiDAR/. Two files from this source in the Orleans County part of the dataset were determined to be corrupt. Those files were deleted from the NOAA OCM Data Access Viewer (DAV) database and the bulk download AWS S3 site. Valid versions of the two corrupt files were downloaded from the Discover GIS Data NY site (https://orthos.dhses.ny.gov/) and processed to provide a complete dataset for custom and bulk downloads.