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|2012 FEMA Topographic Lidar: Hudson-Hoosic and Deerfield Watersheds, MassachusettsspatialRepresentationInfo|
language: eng; USA
characterSet: (MD_CharacterSetCode) utf8
hierarchyLevel: (MD_ScopeCode) dataset
contact: Mike Sutherland(author) (CI_ResponsibleParty)
role: (CI_RoleCode) author
metadataStandardName: ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
metadataStandardVersion: ISO 19115-2:2009(E)
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geometricObjectType: (MD_GeometricObjectTypeCode) point
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title: 2012 FEMA Topographic Lidar: Hudson-Hoosic and Deerfield Watersheds, Massachusetts
dateType: (CI_DateTypeCode) publication
citedResponsibleParty: NOAA CSC (originator)
citedResponsibleParty: FEMA (originator)
citedResponsibleParty: NOAA CSC (publisher) (CI_ResponsibleParty)
role: (CI_RoleCode) publisher
presentationForm: (CI_PresentationFormCode) imageDigital
abstract: The Light Detection and Ranging (LiDAR) dataset is a survey of the Hudson-Hoosic and Deerfield project area. The entire survey area for Massachusetts is approximately 690 square miles. The LiDAR point cloud was flown at a nominal post spacing of 2.0 meters for unobscured areas. The LiDAR data and derivative products produced are in compliance with the U.S. Geological Survey National Geospatial Program LiDAR Guidelines and Base Specifications, Version 13-ILMF 2010. The flight lines were acquired by Northrop Grumman, Advanced GEOINT Solutions Operating Unit. Derivative products from the aerial acquisition include: high accuracy multiple return LiDAR data, both raw and separated into several classes, along with hydro flattening breaklines, bare earth DEM tiles, control points, and FGDC compliant XML metadata.
purpose: The purpose of this project was to produce a high resolution LiDAR data set of approximately 2,895 square miles over the Hudson-Hoosic and Deerfield Watersheds in New York.
credit: Please credit FEMA and Northrop Grumman for all products derived from this data.
status: (MD_ProgressCode) completed
organisationName: Federal Emergency Management Agency, Region I
positionName: Flood Insurance and Mitigation Division
deliveryPoint: 99 High Street, 6th Floor
role: (CI_RoleCode) pointOfContact
maintenanceAndUpdateFrequency: (MD_MaintenanceFrequencyCode) asNeeded
fileDescription: This kmz file shows the extent of coverage for the 2012 FEMA Hudson-Hoosic and Deerfield Watersheds, MA lidar data set.
keyword: Light Detection and Ranging
keyword: Remote Sensing
type: (MD_KeywordTypeCode) theme
keyword: Berkshire County
keyword: Franklin County
type: (MD_KeywordTypeCode) place
resourceConstraints: Lidar Use Limitation
resourceConstraints: NOAA Legal Statement
spatialRepresentationType: (MD_SpatialRepresentationTypeCode) vector
language: eng; USA
topicCategory: (MD_TopicCategoryCode) elevation
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distributorContact: NOAA CSC(distributor) (CI_ResponsibleParty)
role: (CI_RoleCode) distributor
orderingInstructions: The National Geophysical Data Center serves as the archive for this LIDAR data. NGDC should only be contacted for this data if it cannot be obtained from NOAA Coastal Services Center.
distributorContact: Mike Sutherland
orderingInstructions: The National Geophysical Data Center serves as the archive for this LIDAR dataset. NGDC should only be contacted for the data if it cannot be obtained from NOAA Coastal Services Center.
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level: (MD_ScopeCode) dataset
nameOfMeasure: Horizontal Positional Accuracy Report
evaluationMethodDescription: There is not a systematic method of testing when testing horizontal accuracy in LiDAR. However this is tested during calibration of the sensor and is rechecked during the comparing of parallel and perpendicular flight lines. Additionally the horizontal accuracy is checked by collecting building corners during the survey. Lines are then digitized representing the building outline and the differences are measure from each individual survey point to the corner of the building outline. Stats are calculated to ensure horizontal tolerances are met. These measurements resulted in an RMSEr of .21 meters and equals a RMSE accuracy of .36 meter horizontal accuracy at the 95 % confidence level. Accuracy defined by NSSDA at the 95 % confidence level would be multiplier by 1.7308 times the RMSE.
nameOfMeasure: Horizontal Positional Accuracy
measureDescription: Value represent horizontal accuracy assessment at the 95% confidence interval. Units in meters.
nameOfMeasure: Vertical Positional Accuracy Report
evaluationMethodDescription: The accuracy assessment was performed using the NSSDA standard method to compute the root mean square error (RMSE) based on a comparison of ground control points (GCP) and DEM derived from the LiDAR dataset. Testing was performed prior to gridding of the filtered LiDAR data points and construction of the 32-bit ESRI float grid format bare earth tiles. The RMSEz figure was used to compute the vertical National Standard for Spatial Data Accuracy (NSSDA). 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 subsampling 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 .03 to .04 meters. 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 which provides 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 (The vertical accuracy requirements meet or exceed the required RMSEz of 12.5cm and the vertical accuracy of 24.5cm at the 95% confidence level). Data collected under this task order exceeds the required National Standards for Spatial Database Accuracy (NSSDA) accuracy standards. SVA accuracies at the 95th Percentile collected and tested, as target accuracies results as follows: Tall Weeds Crops =0.22 meters, Fully Forested = 0.40 meters. Consolidated Vertical Accuracies (CVA) at the 95th Percentile =0.25 meters. Final accuracy statement for this task order is as follows; FVA Tested 0.15 meters vertical accuracy at the 95% confidence level.
nameOfMeasure: Vertical Positional Accuracy
measureDescription: Value represents the Fundamental Vertical Accuracy (FVA) assessment at the 95% confidence interval. This represents the FVA checkpoints compared against the derived DEM at the 95% confidence interval. Units in meters.
evaluationMethodDescription: Ground Truth data was collected of the three major land cover classes representing 10% of the predominate vegetation dispersed within the area of interest. 30 points were collected in each of the three predominate vegetation classes bare earth, tall weeds crops, and fully forested, points collected in the trees vegetation class were collected with a Total Station. Pair of points was surveyed using the local NGS CORS network once completed the total station is used to collect the forested vegetation class. A total station was used to collect all the shots collected in the forested vegetation class, due to the limited GPS signal when working in and around tree canopy.
measureDescription: The GPS survey was tied into the local NYSNet Realtime Network located in NEW York, and Vermont, and the KEYNet Realtime Network located in the Northeast covering Massachusetts. These networks are networks of continuously operating GPS reference stations that allows for Realtime Kinematic (RTK) capabilities within a realtime network (RTN). This allows for corrections to be applied to the points as they are being collected, eliminating the need for an adjustment. As a quality control measure several check-in points consisting of NSRS published horizontal and vertical control points were used as checks within the real-time networks used. The survey crew checked into these published points daily to validate the consistency of the network. The NSRS published points also confirm that the project will meet the 5cm local network accuracy at the 95% confidence level. Data analysis was accomplished by comparing ground truth checkpoints with LiDAR points from the derived DEM and reported three ways 1. FVA 2. SVA 3. CVA. Additionally the FVA points were assessed against the TIN derived from the LAS LiDAR point cloud controlled and calibrated swath data to ensure they met the required accuracy of 12.5cm RMSEz and 24.5cm at the 95% confidence interval.
description: 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 collected by receivers on the aircraft and base stations on the ground. The ground base stations are placed no more than 40 km radius from the flight survey area.
description: The ABGPS, IMU, and raw scans are integrated using proprietary software developed by Optech and delivered with the Optech System. The resultant file is in a LAS binary file format. The LAS version 1.2 file format can be easily transferred from one file format to another. It is a binary file format that maintains information specific to the LiDAR data (return number, intensity value, xyz, etc.). The resultant points are produced in the NAD83/2007 UTM 18 North Coordinate System, with units in Meters and referenced to the NAVD88 datum. The LiDAR mass points were processed in American Society for Photogrammetry and Remote Sensing LAS 1.2 format. The header file for each dataset is complete as defined by the LAS 1.2 specification. The datasets were divided into a 1500 meter by 1500 meter tiling scheme. The tiles are contiguous, do not overlap, and are suitable for seamless topographic data mosaics that include no "no data" areas. The names of the tiles include numeric column and row designations and all files utilize the LAS file extension.
description: The unedited data are classified to facilitate the application of the appropriate feature extraction filters. A combination of proprietary filters are applied as appropriate for the production of bare earth digital elevation models (DEMs). 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.
description: Filtered and edited data are subjected to rigorous QA/QC, according to the Northrop Grumman, Advanced GEOINT Solutions Operating Unit Quality Control Plan and Procedures. 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 Northrop Grumman, Advanced GEOINT Solutions Operating Unit and GPS-derived ground control points (GCPs) in various areas of dominant and prescribed land cover. These points are coded according to land cover, 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 to Federal Geographic Data Committee (FGDC) specifications.
description: The Bare Earth DEM was extracted from the raw LIDAR products and attributed with the bare earth elevation for each cell of the DEM. Bare Earth DEMs do not include buildings, vegetation, bridges or overpass structures in the bare earth model. Where abutments were clearly delineated, this transition occurred at the junction of the bridge and abutment. Where this junction was not clear, the extractor used their best estimate to delineate the separation of ground from elevated bridge surface. In the case of bridges over water bodies, if the abutment was not visible, the junction was biased to the prevailing stream bank so as not to impede the flow of water in a hydrographic model. Bare earth surface includes the top of water bodies not underwater terrain, if visible.
description: The NOAA Coastal Services Center (CSC) received topographic files in LAS V1.2 format. The files contained lidar elevation measurements, intensity values, scan angle values, return information, and GPS week time. The data were received in UTM Zone 18N, NAD83 coordinates and were vertically referenced to NAVD88 using the Geoid09 model. The vertical units of the data were meters. CSC performed the following processing for data storage and Digital Coast provisioning purposes: 1. Points in Class 11 (Unknown) wer changed to Class 14. 2. The topographic las files were converted from orthometric (NAVD88) heights to ellipsoidal heights using Geoid09. 3. The topographic las files were converted from a Projected Coordinate System (UTM Zone 18N) to a Geographic Coordinate System (NAD83). 4. The topographic las files' horizontal units were converted from meters to decimal degrees. 5. The data were converted to LAZ format.
processor: NOAA CSC (processor) (CI_ResponsibleParty)
role: (CI_RoleCode) processor
description: The NOAA National Geophysical Data Center (NGDC) received lidar data files via ftp transfer from the NOAA Coastal Services Center. The data are currently being served via NOAA CSC Digital Coast at http://www.csc.noaa.gov/digitalcoast/. The data can be used to re-populate the system. The data are archived in LAS or LAZ format. The LAS format is an industry standard for LiDAR data developed by the American Society of Photogrammetry and Remote Sensing (ASPRS); LAZ is a loseless compressed version of LAS developed by Martin Isenburg (http://www.laszip.org/). The data are exclusively in geographic coordinates (either NAD83 or ITRF94). The data are referenced vertically to the ellipsoid (either GRS80 or ITRF94), allowing for the ability to apply the most up to date geoid model when transforming to orthometric heights.
processor: Mike Sutherland (processor) (CI_ResponsibleParty)
role: (CI_RoleCode) processor
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maintenanceAndUpdateFrequency: (MD_MaintenanceFrequencyCode) annually
maintenanceNote: This metadata was automatically generated from the FGDC Content Standards for Digital Geospatial Metadata standard (version FGDC-STD-001-1998) using the 2013-01-04 version of the FGDC RSE to ISO 19115-2 for LiDAR transform.
maintenanceNote: Translated from FGDC 2013-11-19T15:41:50.316-07:00
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type: Light Detection and Ranging