Block L-D2 LiDAR 3rd Quality Assessment Report...2.7 Computing the RMSE (z) 18 2.8 Visual Assessment...

Block L-D2 LiDAR 3rd

Party

Quality Assessment Report

Prepared for the:

Prepared by:

6901 East Fish Lake Road Suite 140 Maple Grove Minnesota 55369

September 10, 2010

IInntteerrnnaattiioonnaall WWaatteerr IInnssttiittuuttee

RReedd RRiivveerr BBaassiinn

LLiiDDAARR MMaappppiinngg IInniittiiaattiivvee

1301 12th Avenue North Box 5057 Fargo, North Dakota 58105

www.houstoneng.com

International Water Institute Red River Basin LiDAR Mapping Initiative

Block L-D2 LiDAR 3rd Party Quality Assessment Report

i.

CERTIFICATION

I hereby certify that this plan, specification, or report, was prepared by me or under my direct

supervision, and that I am a duly licensed professional under the laws of the State of Minnesota

or the State of North Dakota.

Curtis A. Skarphol, RLS Mark R. Deutschman, P.E.

Minn. Reg. No. 42303 Minn. Reg. No. 41259

North Dakota Reg. No. 4723

Quality assurance oversight has been provided by me during the completion of this project.

I certify that I have reviewed the work products in accordance with the specifications and criteria

contained herein.

Mr. Brian Fischer, CFM

GIS Project Manager

Date: September 10, 2010

Houston Engineering, Inc.

6901 East Fish Lake Road, Suite 140

Maple Grove, Minnesota 55369

763.493.4522 (Phone)

763.493.5572 (Fax)

and

Houston Engineering, Inc.

1401 21st Avenue North

Fargo, ND 58102

701.237.5065 (Phone)

701.237.5101 (Fax)

www.houstonengineeringinc.com

http://www.houstonengineeringinc.com/



Block L-D2 LiDAR 3rd Party Quality Assessment Report HEI Project No. R09.4875-007

September 10, 2010 I.

Table of Contents

Page

Section 1.0 Project Overview 1

Section 2.0 Quality Assurance Considerations 4

2.1 References and Applicable Methods 4

2.2 Performance Specifications for LiDAR Products

Established by the Contract 5

2.3 Quality Assurance Process 6

2.4 Quality Assurance Unit 8

2.5 Collection of Known Elevations in the Field 8

2.6 Chain of Custody 18

2.7 Computing the RMSE(z) 18

2.8 Visual Assessment 18

2.9 Criteria for Acceptance 19

Section 3.0 Quality Assurance Results and Conclusions for Block L-D2 20

3.1 Block Description 20

3.2 Results 20

3.2.1 Vertical Accuracy 20

3.2.2 Visual Assessment 26

3.2.3 Concurrence with the Specification 27



Block L-D2 LiDAR 3rd Party Quality Assessment Report HEI Project No. R09.4875-007

September 10, 2010 II.

Table of Contents (continued)

List of Figures

Figure 1. LiDAR Collection Areas and Blocks 3

Figure 2. Land Use Within the LiDAR Project Area 11

Figure 3. Monument and Control Locations Used to Establish

Checkpoints 12

Figure 4. Check Point Locations within the Project Area 13

Figure 5. Land Use within Block L-D2 22

Figure 6. Control Points within Block L-D2 23

Figure 7. Checkpoints within Block L-D2 24

Figure 8. RMSE(Z) by Land Class in Block L-D2 25

Figure 9. Histogram of Residual Differences within Block L-D225 26

Figure 10. Histogram of Absolute Value of the Residuals

Across All Land Use Classes in Block L-D2 27

Figure 11. Checkpoint Results and Blunders 28

Figure 12. Delivery Block L-D2 Tiles Reviewed 29

List of Tables

Table 1. Numbered Checkpoints by Block 14

Table 2. Vertical Accuracy Statistics by Land Class for Block L-D2 21

List of Appendices

Appendix A: Chain of Custody Form 30

Appendix B: Vertical Accuracy Computations by HEI Checkpoints 32

Appendix C: Comparison of Vertical Accuracy by Block 38

Appendix D: Visual Assessment Screenshots 39

Appendix E: CD-ROM containing an ESRI Shapefile of HEI

Checkpoints and Photos 51



Block L-D2 LiDAR 3rd Party Quality Assessment Report HEI Project No. R09.4875-007 September 10, 2010 Page 1 of 51

SECTION 1.0

PROJECT OVERVIEW

The International Water Institute (IWI) has secured funding for a high-resolution digital

elevation data collection project in the United States portion of the Red River of the North

watershed. The Red River Basin Mapping Initiative (RRBMI) includes all or portions of 45

counties in North Dakota, Minnesota, and South Dakota (i.e., the Project Area). The size of the

proposed collection area is approximately 45,000 square miles. In the spring of 2008, the IWI

selected Fugro-Horizons as the vendor to collect and process the LiDAR data. The United States

Army Corps of Engineers (COE) has entered into a cost share agreement with the Minnesota Red

River Watershed Management Board and the North Dakota Red River Joint Water Resource

District to contribute funding and resources towards the project. The COE is also using Fugro-

Horizons to collect and process LIDAR data.

The Project Area is divided into 14 delivery blocks as shown on Figure 1. Fugro-

Horizons is under contract to deliver the final products by Block (A thru O), using 2000 x 2000

meter tiles. The blocks that have been completed are as follows:

Block A delivered in late August 2008;

Block B delivered November 29, 2008;

Block C delivered February 4, 2009;

Block H and the western portion of Block D were combined to form Block H-D1.

The eastern portion of Block D has not been collected as of this date. The

remaining portion of Block D will be combined with Block L into a QA report

called Block L-D2;

Block G delivered on May 8, 2009;

Block O delivered on August 11th

, 2009;

Block E delivered on November 23rd

2009; and

Block L-D2 delivered on January 12 2010, which is the focus of this current

quality assurance review. This revised report now contains portions of Big Stone

County that was flown in the Spring of 2010. The report now includes all of the

original area known as L-D2.




The IWI selected Houston Engineering, Inc. to conduct the 3rd party Quality Assessment

(QA) review of select LiDAR deliverables. By passing the QA review, final acceptance of the

data by the IWI is possible. Houston Engineering is primarily responsible for assessing the

vertical accuracy1 of the data using Global Positioning Survey (GPS) checkpoints.

1 Horizontal accuracy and orthoimagery are excluded from this QC process.

!.

!.

Marshall Roberts

Sargent

Ransom

Richland

Cass

Barnes

Stutsman

Foster

Traill

SteeleGriggs

EddyWells

Sheridan

GrandForksNelson

Benson

Walsh

Ramsey

Pierce

McHenry

RoletteTowner

Cavalier Pembina

Pierce

BigStone

Stevens

Traverse

Grant

Wilkin OtterTail

BeckerClay

Hubbard

MahnomenNorman

ItascaRedLake

Clearwater

Pennington

Polk

Beltrami

Marshall

Koochiching

RoseauKittsonLakeof the

Woods

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Figure 1. LiDAR Collection Areas and Blocks

!. Fargo!. Grand Forks

RiversLiDAR Delivery BlocksMN DNR Project Boundary

South Dakota CountiesNorth Dakota CountiesMinnesota Counties

0 25 50 7512.5 MilesFigure 1

LiDAR Collection Blocks

´Sources: MN DOT, MN DNR, ND GIS Hub, US TIGER Data

August 31, 2010Block L-D2 3rd Party Quality Assessment ReportHEI Project No. 4875-007

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SECTION 2.0

Quality Assurance Considerations

2.1 REFERENCES AND APPLICABLE METHODS

The processes and methods used to QA the LiDAR products are largely based upon

guidance, established by various federal agencies/entities including the Federal Emergency

Management Agency (FEMA) and the Federal Geographic Data Committee (FGDC). Portions

of the following references form the basis for the QA process:

American Society for Photogrammetry and Remote Sensing (ASPRS) Guidelines,

Vertical Accuracy Reporting for LiDAR Data, Version 1.0, Released May 24,

2004, ASPRS LiDAR Committee, 20 p.

Federal Geographic Data Committee, 1996. Content Standards for Digital

Geospatial Metadata (version 2.0), FGDC-STD-001-1998: Washington, D.C.,

Federal Geographic Data Committee, 9 p.

Federal Geographic Data Committee, 1998, Part 3: Geospatial Positioning

Accuracy Standards, FGDC-STD-007.3-1998: Washington, D.C., Federal

Geographic Data Committee, 25 p.

Federal Emergency Management Agency, 2003, Guidelines and Specifications for

Flood Hazard Mapping Partners, Appendix A: Guidance for Aerial Mapping and

Surveying [February 2002], 57p.

Federal Emergency Management Agency, 2003, Guidelines and Specifications for

Flood Hazard Mapping Partners, Appendix 4B: LIDAR Specifications for Flood

Hazard Mapping, 8p.

The QA process included select portions from these references (primarily to determine

vertical accuracy) as well as visual methods as described within this section. The U.S.

Geological Survey National Geospatial Program is currently soliciting input additional

specifications for the collection of high resolution topographic data using LiDAR

(http://lidar.cr.usgs.gov/USGS-

NGP%20Lidar%20Guidelines%20and%20Base%20Specification%20v13(ILMF).pdf).

However, because these specifications were developed subsequent initiation of this project, they

were not relied upon for completing the quality assurance review.

http://lidar.cr.usgs.gov/USGS-NGP%20Lidar%20Guidelines%20and%20Base%20Specification%20v13(ILMF).pdf)

http://lidar.cr.usgs.gov/USGS-NGP%20Lidar%20Guidelines%20and%20Base%20Specification%20v13(ILMF).pdf)




2.2 PERFORMANCE SPECIFICATIONS FOR LIDAR PRODUCTS ESTABLISHED BY THE

CONTRACT

The Request for Proposal (RFP) established the following requirements for several

LiDAR Products:

Performance Standards - The performance standards for this project are the Federal

Emergency Management Agency’s (FEMA) “Guidelines and Specifications for

Flood Hazard Mapping Partners, Appendix A” Guidance for Aerial Mapping and

Surveying”. (http://www.fema.gov/pdf/fhm/frm_gsaa02.pdf). At a minimum, all

bare earth digital elevation data delivered shall meet a 15 centimeter root mean

square error (RMSE(z)) vertical and one (1) meter horizontal accuracy.

Mandatory Deliverables - Delivery of the following products shall be required to

satisfy the contract:

All Raw Classified Data

o All raw classified (post calibrated, pre-filtered) data files shall be

delivered for each collection area. Other raw data deliverable

requirements include:

Delivered in Universal Trans-Mercator (UTM) Coordinate System

(Zone 14, NAD 83).

Elevation values (z) provided in orthometric heights in meters with 1

(one) centimeter resolution in the NAVD88 datum.

Classified raw data in LASer (LAS version 1.1) File Format

Exchange format.

Data as a collection of files which are subdivided using 2000m by

2000m tiles.

Filtered Bare-earth Data

o Provide northing, easting, and elevation data for filtered raw data

representing the bare earth – all other elevation points shall be removed

(i.e. bridges, buildings, vegetations, etc). Other filtered bare earth data

requirements include:

Delivered in Universal Trans-Mercator (UTM) Coordinate System

(Zone 14, NAD 83).

Elevation values (z) provided in orthometric heights in integer meters

with 1 (one) centimeter resolution in the NAVD88 datum.

Filtered Bare-earth data in the LAS (version 1.1) format.

http://www.fema.gov/pdf/fhm/frm_gsaa02.pdf




Data as a collection of files which are subdivided using 2000m by

2000m tiles.

Bare-Earth Digital Elevation Model (DEM)

o Provide a raster-based DEM derived from bare-earth points of the filtered

bare-earth data that meets the following requirements:

Horizontal DEM grid spacing of 1 (one) meter in Easting and

Northing.

Delivered in Universal Trans-Mercator (UTM) coordinate system

(Zone 14, NAD 83).

Vertical DEM resolution shall preserve ranging resolution at a

minimum of 1 (one) centimeter resolution in the NAVD88 datum.

Provided in ASCII GRID format.

Data as a collection of files which are subdivided using 2000 meters

by 2000 meters tiles.

Project Completion Report

o This report shall be provided to the IWI in both printed copy and

electronic format (CDROM – Microsoft Word), and shall contain the

information specified in FEMA’s Appendix A, Section A.8.7.2

(http://www.fema.gov/pdf/fhm/frm_gsaa.pdf)

Metadata Record

o For each dataset produced under this contract, the Vendor shall use the

information compiled in the Project Completion Report to deliver a

metadata document compatible with the FGDC Content Standards for

Digital Geospatial Metadata.

(http://www.fgdc.gov/standards/projects/FGDC-standards-

projects/metadata/base-metadata/v2_0698.pdf)

Although several LiDAR products are generated by the current collection effort, this QA

report pertains solely to the bare earth products.

2.3 QUALITY ASSURANCE PROCESS

The QA process is intended to assess whether the LiDAR deliverables meets the

following criteria:

http://www.fema.gov/pdf/fhm/frm_gsaa.pdf

http://www.fgdc.gov/standards/projects/FGDC-standards-projects/metadata/base-metadata/v2_0698.pdf

http://www.fgdc.gov/standards/projects/FGDC-standards-projects/metadata/base-metadata/v2_0698.pdf

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The final products are delivered in UTM Coordinate System NAD 83, Zone 14

with elevation values in NAVD 1988 datum (orthometric heights);

Files are named correctly in accordance with the tiling and collection area scheme

and are not corrupt;

Investigation for the presence of blunders based upon the checkpoints. Blunders

are defined as a difference between the measured checkpoint elevation and the

elevation determined from the bare earth products which exceeds 3 times the

standard deviation (as defined by ASPRS Guidelines) as an indicator of potential

for systematic error;

Visual assessment of the raw classified data to ensure proper classification (2

– Ground, 6 – Building, 8 – Model Keypoint, 12 – Overlap Points) and

qualitatively assess the number of unclassified points;

Visual assessment of the filtered bare earth data to assess the homogeneity and

density of points and ensure suitable overlap between the tiles and point density

at the tile seams;

Lack of obvious anomalies as determined from visual audit goal of assessing

5% of the tiles.

o Per FEMA’s Appendix A, Section A.8.3.1, data voids are areas lacking

points exceeding two times the DEM post spacing. For the purpose of

this assessment, voids are functionally defined by an absence of points

within a maximum area of ~ 1,000,000 square meters (~250-acres).

Except within bodies of water, raw data voids cannot exceed 25% of any

given tile.

o Per FEMA’s Appendix A, Section A.8.3.1, artifacts are regions of

anomalous elevations or oscillations or ripples within the DEM data.

Artifacts may consist of elevation spikes or depressions, ridges between

tiles, poor penetration of the LiDAR or processing. Artifact aerial extent

should generally be limited to a maximum area of ~ 1,000,000 square

meters (~250-acres) and less than 25% of any given tile.

Descriptive statistics computed by land use for the elevation difference between

the checkpoint elevation and the LiDAR elevation to verify normality

assumptions used when computing the root mean square error (RMSE(z)) for

fundamental accuracy (mean of ± 2 cm and skewness coefficient of ± 4 cm);

Vertical accuracy expressed as:

o Block RMSE(z) computed from all checkpoints within a block regardless of

land use. The block RMSE(z) is consistent with the vertical accuracy as

described within the contract between the IWI and Fugro-Horizons:




o Fundamental vertical accuracy within a block for those checkpoints located

within open terrain where there is a high probability that the sensor detected

the ground surface. The fundamental vertical accuracy is the value by which

vertical accuracy can be equitably assessed and compared among different

datasets. Fundamental vertical accuracy is calculated at the 95-percent

confidence level as a function of the RMSE(z);

o Supplemental vertical accuracy for those check points not located within

open terrain and expressed as the 95th percentile error value;

o Consolidated vertical accuracy computed across land use categories and

expressed as the 95th percentile error value; and

o Absolute and percent difference between the checkpoint and LiDAR

elevation;

Metadata meets accepted standards.

2.4 QUALITY ASSURANCE UNIT

QA procedures were applied to the LiDAR deliverables by block. Each block comprises

an approximate area between 470 square miles and 4,473 square miles and is further subdivided

into tiles approximately 2000 meters by 2000 meters. Generally, a minimum of twenty (20)

known elevations within the dominant land use (i.e., comprising 90% of the total area within a

block) is desired to assess vertical accuracy.

2.5 COLLECTION OF KNOWN ELEVATIONS IN THE FIELD

Known elevations (i.e., checkpoints) within five (5) land use categories were determined

using a Trimble survey grade global positioning system. In some blocks there was insufficient

area to collect checkpoints in a certain land use. In these cases that land use category would not

have any checkpoints collected. If a GPS signal is not possible because of the inability to attain

satellites, (for example, in forested areas) an elevation using the GPS is established in an

adjacent open area and then a total station used to traverse into and out from the area to establish

the checkpoint elevation. Checkpoints were collected within the following land use categories:

Low grass, bare earth;

High grass, weeds, crops;




Brush, low trees;

Forested; and

Urban – developed.

Land use was based upon the National Land Cover Dataset (2001) as shown in Figure 2.

Land use categories are consistent with those recommended by various reference documents as

described within Section 2.1.

Houston Engineering performed the checkpoint survey relative to National Spatial

Reference System (NSRS) monuments and generally used the same NSRS monuments and

control points as those used by the contractor for the collection of the LiDAR data. A total of

thirty-six control points were used by Houston Engineering during the checkpoint survey in

Block L-D2. Figure 3 shows the control network used to obtain checkpoint elevations.

Checkpoint locations were generally placed on flat terrain, removed from severe slopes and

breaklines, consistent with National Digital Elevation Program (NDEP) guidelines

(http://www.ndep.gov/TechSubComm.html). The GPS base station was established over these

monument and control points and in some cases, monuments and control points were “checked”

as an additional quality assurance measure.

The quality of a checkpoint can be inferred from the instrument Position Dilution of

Precision (“PDOP”). PDOP can be further broken down into Horizontal Dilution of Precision

(“HDOP”) and Vertical Dilution of Precision (“VDOP”) components. Generally the smaller the

PDOP, HDOP and VDOP numbers, the higher the data quality. HDOP and VDOP values from

the GPS measurements made during the survey of the checkpoints are presented in appendix

section of this report.

A minimum of 20 checkpoints (preferably 30) for each land use category is desirable

(because RMSE(z) computations are based on the assumption of a normality of the errors).

During the RFP process, the collection areas were envisioned as the quality assurance unit.

Subsequent to contract award, specific blocks within the collect areas became the quality

assurance unit. Changing the quality assurance unit to blocks resulted in fewer than 20 points for

http://www.ndep.gov/TechSubComm.html




each land use within a block. A minimum of 20 check points were collected for the dominant

land use (i.e., land use 2, high grass, weeds and crops) typically comprising 90% of the area

within a block (see Table 1). Figure 4 shows the checkpoint locations by land use for the entire

project area. The checkpoints were used to compute the vertical RMSE(z) LiDAR values for

computing the RMSE(z) were obtaining from a triangular irregular network (TIN) derived from

the LiDAR bare earth products.

There is a presumption that the checkpoint survey values are free of error and that

discrepancies between the LiDAR and checkpoint elevations are attributable to the LiDAR

technology. This assumption is considered valid provided the technology used to obtain the

checkpoint elevations yield accuracy at least three times greater than the expected accuracy of

LiDAR. It should be recognized that the checkpoint survey is in fact not free of error - the

PDOP values provide some indication of the quality of the checkpoint elevations.

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´0 30 60 90 12015 Miles

InterstateDelivery BlocksLow Grass, Bare EarthHigh Grass, Weeds, CropsBrush, Low TreesForestedUrban - DevelopedWater

Sources:National Land Cover Dataset 2001MN DOTND GIS HubUS TIGER Data Figure 2

Figure 2. Land Use Within the LiDAR Project Area

August 31, 2010Block L-D2 LiDAR 3rd Party Quality Assessment ReportHEI Project No. 4875-007

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I

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F

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B

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§̈¦I 29

·

Legend"/ Mn DOT VRS CORS StationsGF HEI_Control_PTSGF MN_HARN_PTSGF ND_HARN_PTSGF SD_HARN_PTSGF FURGO CONTROL PTS

Five Mile Buffer

RiversLakesInterstatesMnDNR LIDAR Collect BoundaryLiDAR Delivery Blocks

Monument and Control LocationsUsed to Establish Checkpoints* Lettered polygons are Horizon - Furgo's

LIDAR delivery blocks

Figure 3


Figure 3. Monument and Control Locations

used to Establish Checkpoints

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Page 12 of 51

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Lake of the Woods

Lower Red Lake

Upper Red Lake

Devils Lake

I

JF

AE

K

B

C

O

G

N

L-D2

H-D1

M

Legend^ MnDNR LIDAR Check Points (approx. 456)^ Fargo LIDAR Check Points (appox. 160)

HEI Check Points! Low Grass, Bare Earth! High Grass, Weeds, Crops! Brush, Low Trees! Forested! Urban - Developed

InterstateLiDAR Delivery BlocksRivers

MN DNR LIDAR ProjectLakes

GrandForks

*Lettered polygons are Horizon - Furgo's LIDAR delivery blocks

Figure 4

Figure 4. Check Point Locations within the Project Area


Fargo§̈¦94

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Page 13 of 51




Table 1 Number of Checkpoints by Land Use and Block

Block A Land Use Collected Points within the block NLCD Proportion of Area (%)* % of Block** Land Use Descriptions

1 14 0.70% 20.29% Low Grass, Bare Earth

2 24 89.73% 34.78% High Grass, Weeds, Crops

3 5 0.23% 7.25% Brush, Low Trees

4 12 3.99% 17.39% Forested

5 14 5.11% 20.29% Urban - Developed

Sub-Total 69

Block B

Land Use Collected Points within the block NLCD Proportion of Area (%)* % of Block** Land Use Descriptions



3 7 0.00% 16.67% Brush, Low Trees

4 7 1.04% 16.67% Forested


Sub-Total 42

Block C





4 7 2.77% 18.92% Forested


Sub-Total 49





Block E





4 9 2.73% 13.85% Forested


Sub-Total 65

Block F





4 12 0.98% 17.39% Forested


Sub-Total 69

Block G





4 14 1.06% 23.33% Forested


Sub-Total 60





Block H-D1





4 15 1.19% 20.55% Forested


Sub-Total 73

Block L-D2


1 20 1.96% 22.99 Low Grass, Bare Earth

2 29 83.51% 33.33 High Grass, Weeds, Crops

3 9 0.30% 10.34 Brush, Low Trees

4 11 3.44% 12.64 Forested


Sub-Total 87

Block N





4 8 2.93% 14.04% Forested


Sub-Total 57





Block O





4 8 0.40% 13.79% Forested


Sub-Total 58

Total***

Land Use Collected Points within the block Average NLCD Proportion of Area (%)* % of Block** Land Use Descriptions



3 40 0.03% 6.43% Brush, Low Trees

4 102 1.99% 16.40% Forested

5 119 4.85% 19.13% Urban - Developed

Sub-Total 622

* Data based on National Land Cover Dataset (2001)

** The percent of checkpoints within the block.

*** Blocks K, J, M, and I have not yet completely collected. Totals are planned total checkpoints.




2.6 CHAIN OF CUSTODY

The work flow process for quality assuring the LIDAR products included following

chain-of-custody procedures to ensure data integrity, a visual assessment of the LIDAR bare

earth product for select tiles, completeness checks, and computing the RMSE(z) for vertical

accuracy. Upon receipt of the LiDAR products, Houston Engineering checks for completeness

of files and ensures naming conventions conformed to the tile naming convention. The Chain of

Custody Form (see Appendix A) tracks progress through the QA process.

2.7 COMPUTING THE RMSE(Z)

The vertical accuracy calculations were generated using Coherent’s LP360 software

program. The LiDAR surface elevations are calculated by interpolating from the bare earth LAS

files delivered by the vendor. A Triangular Irregular Network (TIN) is created around each

checkpoint, using LiDAR points. Then the triangle that covers the checkpoint location

horizontally is selected. The location on the surface of this triangle that matches the sample

location then provides the elevation. This elevation is a linear interpolation of the elevations of

the 3 triangle vertices; or more simply, it is the point in 3D on the TIN triangle at the sample

location’s X and Y. The RMSE(z) is computed as:

n

RMSE(z) = Sqrt [(∑ (ZLidar(i) – Zcheckpoint(i))2)/n] where n is the total number of checkpoints and i

i=1

represents any given checkpoint

2.8 VISUAL ASSESSMENT

The goal of the visual assessment is to inspect for three general issues; data voids greater

than 1,000,000 sq. meters, appropriate LiDAR point classification and anomalies in the bare

earth products. Anomalies include penetration problems, spikes, and vegetation artifacts.

Houston Engineering randomly selected a minimum 5% of the tiles within each block and

visually reviewed the bare earth point LAS files using the LP360 software.




2.9 CRITERIA FOR ACCEPTANCE

The sole criteria for acceptance of the LiDAR product is a per block RMSE(z) of 15 cm or

less for the bare earth data as defined within the Request for Proposal for those checkpoints

collected by Houston Engineering, Inc. Any other issues that are identified by the assessment

will be reported in the report for informational purposes.




SECTION 3.0

Quality Assurance Results

and

Conclusions for Block L-D2

3.1 BLOCK DESCRIPTION

High grass, weeds and crops comprise approximately 83% of the land use within Block

L-D2. Urban (5.6%), forested (3.4%), low grass and bare earth (2%) and brush and low trees (<

1%) comprise the remaining land uses within Block L-D2 (Figure 5). Control points used to

collect checkpoints used within Block L-D2 numbered thirty-six as shown in Figure 6. Control

points utilized by the checkpoint survey included National Geodetic Survey (NGS), Minnesota

Department of Transportation (MnDOT) and HEI control networks. Eighty-seven checkpoints

were collected within Block L-D2 and used during completion of the QA process (Figure 7).

The hatched area shown in Figure 7 depicts the Big Stone County portion of the block that was

appended to this report.

3.2 RESULTS

3.2.1 Vertical Accuracy

Table 2 shows the block RMSE(z) derived from all checkpoints across all land uses and

by land use. Table 2 also shows the PDOP values as an index of the quality of the individual

quality assurance checkpoints. Figure 8 graphically presents the RMSE(z) values by land class.

Appendix B shows the difference in elevation between each checkpoint and the elevation

derived from the LiDAR bare earth TIN. Appendix C provides a summary of vertical accuracy

across all Blocks collected to date.

Table 2 shows the block RMSE(z) derived from all checkpoints across all land uses and

by land use. Calculation of the RMSE(z) assumes that the vertical errors are normally distributed

with a mean of zero. The mean difference is 3.8 cm and the skewness coefficient is +1.6 cm

which indicates the vertical errors are positive and skewed right. Table 2 shows that the

normality of the errors seems reasonable for Block L-D2 based on the small skewness value.

Figure 8 graphically presents the RMSE(z) values by land use.




Table 2 Vertical Accuracy Statistics per NSSDA/FEMA Guidelines by Land Class for Block L-D2

Land Class

# of

Check

Points

Mean

Absolute

Difference

(cm)

Median

Absolute

Difference

(cm)

Skew

Std. Dev.

(cm)

Min

Absolute

Difference

(cm)

Max

Absolute

Difference

(cm)

Mean

Difference

(cm)

95%

Confidence

Interval

Value (cm)

95th

Percentile

Value RMSE(z)

(cm)

Low Grass,

Bare Earth 20 4.6 3.1 1.1 4.4 0.0 14.9

1.9 +/-12.3

14.0 6.3

High Grass,

Weeds, Crops 29 10.2 10.7 0.4 6.5 0.3 22.8

8.9 +/-23.5

21.7 12.0

Brush,

Low Trees 9 14.6 12.2 1.1 8.1 6.4 29.9

9.5 +/-32.2

28.1 16.4

Forested 11 6.1 6.7 -1.1 2.8 0.4 9.2 4.3 +/-13.0 8.8 6.7

Urban 18 7.8 5.6 2.9 8.5 1.3 38.1 -5.6 +/-22.3 19.3 11.4

All Points

87 8.3 6.6 1.6 7.0 0.0 38.1

3.8 +/-21.2

21.6 10.8

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Flensburg

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Freeport

Garfield

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GroveCity

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Herman

Hewitt

Hoffman

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Holloway

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Johnson

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Kensington

Kent

Kerkhoven

Kingston

LakeHenry

Lastrup

Litchfield

LittleFalls

LongBeach

LongPrairie

Louisburg

Lowry

MapleLake

MeireGrove

Melrose

Milan

MillervilleMiltona

Minnesota, State of

Morris

Motley

Murdock

Nashua

Nelson

NewLondon

NewMunich

Norcross

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Osakis

Ottertail

ParkersPrairie

Pennock

Pierz

Pillager

PleasantLake

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Regal

Rice

Richmond

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SaintCloudSaint

Joseph

SaintMartin

SaintRosa Saint

Stephen

Sartell

SaukCentre

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Sobieski

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Spicer

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Swanville

Tenney

Tintah

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Underwood

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Urbank

Verndale

Villard

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Watkins

Wendell

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Wheaton

Willmar

ColfaxAbercrombie

Dwight

Wahpeton

Fairmount

GreatBend

Hankinson

Mantador

Mooreton

´

0 9 184.5Miles


Figure 5. Landuse Within

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#0 CitiesInterstateUS HighwaysState HighwaysRiversCounties

Low Grass, Bare EarthHigh Grass, Weeds, CropsBrush, Low TreesForestedUrban - DevelopedWater

Figure 5. Landuse Within Block L-D2Scale: Drawn by: Checked by: Project No.: Date: Sheet:AS SHOWN SMW 4875-007 8/31/2010 1 of 1

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Avon

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Beardsley

Belgrade

Bellingham

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Bertha

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Browerville

BrownsValley

Buckman

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Campbell

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Chokio

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ClearLake

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Clitherall

Clontarf

Cokato

ColdSpring

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DarwinDassel

De Graff

DeerCreek

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Dumont

EagleBend

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0 10 205Miles

January 21, 2010Block L-D2 LiDAR 3rd Party Quality Assessment ReportHEI Project No. 4875-005

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Figure 6. Control Points Within

Block L-D2

"/ Mn DOT VRS CORS Stations#0 Cities

InterstateUS HighwaysState HighwaysBlock L-D2Rivers

Checkpoints (Based Stations Used)! DAKOMIN! DUMONT! MUSTINKA! MnDOT 0608F! VRS BASE! WHAPPORT! WHEAPORT! Z 103

Base Stations#* 0608 A#* 0608E#* 0608F#* 2614 C#* DAKOMIN#* DUMONT#* J108 RESET#* LOYD#* MNDOT 0608 T#* MNDOT 0609 AC#* MNDOT 0609 D#* MNDOT 0609 Q#* MNDOT 12 JKP

#* MNDOT 2609 K#* MNDOT 2609AB#* MNDOT 5603 W#* MNDOT 7501 B1#* MNDOT 7503 G RESET#* MNDOT ALMORA 2#* MNDOT KARP#* MNDOT POST OFFICE#* MNDOT SILVER#* MNDOT UNDERWOOD#* MUSTINKA#* WHAPPORT#* WHEAPORT#* Z 103

Note: Several checkpoints utilized the MN DOT CORS/VRS Network.The MN DOT CORS/VRS Base Stations and Checkpoints using the CORS/VRS network are depicted on the map.

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Figure 6. Control Network Within Block L-D2Scale: Drawn by: Checked by: Project No.: Date: Sheet:AS SHOWN SMW 4875-007 9/1/2010 1 of 1

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September 1, 2010Block L-D2 LiDAR 3rd Party Quality Assessment ReportHEI Project No. 4875-007

Figure 7. Checkpoints Within

Block L-D2

Note: The majority of Block L-D2 was delivered in January 2010. The remaing portion of Big Stone County was delivered in Spring of 2010.

The Union of these two installments is the focus of this report.

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Figure 7. Checkpoints Within Block L-D2Scale: Drawn by: Checked by: Project No.: Date: Sheet:AS SHOWN SMW 4875-007 9/1/2010 1 of 1

#0 CitiesBlock L-D2 - Currently Collected

! LOW GRASS, BARE EARTH (1)! HIGH GRASS, WEEDS, CROPS (2)! BRUSH, LOW TREES (3)! FORESTED (4)! URBAN/DEVELOPED (5)

Big Stone County - Collected Spring 2010 (added to report)InterstateUS HighwaysState HighwaysRivers

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Page 24 of 51



Block L-D2 LiDAR 3rd Party Quality Assessment Report HEI Project No R09.4875-007 September 10, 2010 Page 25 of 51

Based upon the quality assurance review, the data for this Block exhibit the following

characteristics:

2 Fundamental Vertical Accuracy (cm) 12.3

3 Supplemental Vertical Accuracy (cm) 22.6

4 Consolidated Vertical Accuracy (cm) 21.6

5 Number of Blunders 5

2 Equal to the 95-percentile confidence interval value for low grass and bare earth land class.

3 Equal to the 95-percentile error value for all land classed excluding low grass and bare earth.

4 Equal to the 95-percentile error value for all land classes.

5 Blunder defined as specific error value exceeding 3 times the standard deviation.

Figure 8 RMSE(z) by Land Class in Block L-D2




Figure 9 Histogram of Residual Difference within Block L-D2

The actual difference between the measured checkpoint elevation and the elevation

derived from the LiDAR TIN is a residual. Figure 9 shows an analysis of the residuals for

Block L-D2 based on the signed difference. The chart shows the residuals are bimodally

distributed about zero. Figure 10 shows the absolute values of the residuals. This figure shows

that the absolute value (and therefore errors), tend to be normally distributed. Figure 11

geographically represents the difference between the checkpoint elevations and the TIN

elevations derived from the bare earth .las files. The figure also shows the locations of blunders

within the block which are defined as a difference between the measured checkpoint elevation

and the elevation determined from the bare earth product which exceeds 3 times the standard

deviation.

3.2.2 Visual Assessment

The visual assessment included a review of 106 tiles (approximately 5 %) of the total

2,101 tiles in the first delivered portion, and 16 of 272 tiles in the Big Stone portion (Figure 12).

In summary, Houston Engineering, Inc. found no major anomalies with the visual assessment. A

few minor anomalies were found and are described below and shown in Appendix D. The

potential anomalies included a few areas where there were data voids of the LiDAR points;

additionally there were was an occurrence of poor penetration of a forested area. There was also

an instance where a few data spikes were present in a given area of a tile.




3.2.3 Concurrence With the Specification

This quality assurance review shows that the RMSE(z) of 10.8 cm determined for the

Block L-D2 bare earth LiDAR product (Filtered LAS files) is equal to or less than the

specification of 15 cm and therefore achieves the required specification. Appendix B shows the

difference between each checkpoint elevation and the elevation derived from the TIN derived

from the bare earth LiDAR data.

Figure 10 Histogram of Residual Difference Within Block L-D2

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Figure 11. Checkpoint Results and Blunders

Within Block L-D2¬«29

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Notes:*A Blunder is defined as a difference between the measuredcheckpoint elevation and the elevationdetermined from the bare earth productswhich exceeds 3 times the standard deviation.* The difference (in cm) is computed by taking the checkpoint elevation and subtracting the tin elevation from the bare earth las files. All differences are absolute values.

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Figure 11. Checkpoints Results and Blunders Within Block L-D2Scale: Drawn by: Checked by: Project No.: Date: Sheet:AS SHOWN SMW 4875-007 9/1/2010 1 of 1

kj Blunder (5)Absolute Difference (in cm)!. 0.0- 15.0!. 15.1 - 38.1#0 Cities

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Dalton

Danvers

DarwinDassel

De Graff

DeerCreek

Donnelly

Doran

Dumont

EagleBend

EdenValley

ElbowLake

Elizabeth

Elmdale

Elrosa

Evansville

Farwell

FergusFalls

Flensburg

Forada

FortRipley

Foxhome

Freeport

Garfield

Genola

Gilman

Glenwood

Graceville

Greenwald

GreyEagle

GroveCity

Hancock

Harding

Henning

Herman

Hewitt

Hoffman

Holdingford

Holloway

HowardLake

Johnson

Kandiyohi

Kensington

Kent

Kerkhoven

Kingston

LakeHenry

Lastrup

Litchfield

LittleFalls

LongBeach

LongPrairie

Louisburg

Lowry

MapleLake

MeireGrove

Melrose

Milan

MillervilleMiltona

Minnesota, State of

Morris

Motley

Murdock

Nashua

Nelson

NewLondon

NewMunich

Norcross

Odessa

Ortonville

Osakis

Ottertail

ParkersPrairie

Pennock

Pierz

Pillager

PleasantLake

Randall

Regal

Rice

Richmond

Rockville

Roscoe

Royalton

SaintAnthony

SaintCloudSaint

Joseph

SaintMartin

SaintRosa Saint

Stephen

Sartell

SaukCentre

SaukRapids

Sedan

Sobieski

SouthHaven

Spicer

SpringHill

Staples

Starbuck

Sunburg

Swanville

Tenney

Tintah

ToddCounty

Underwood

Upsala

Urbank

Verndale

Villard

Vining

WaitePark

Watkins

Wendell

WestUnion

Westport

Wheaton

Willmar

Abercrombie

Dwight

Wahpeton

Fairmount

GreatBend

Hankinson

Mantador

Mooreton

´

0 10 205Miles


Figure 12. Delivery Block L-D2

Tiles Reviewed¬«29

¬«78§̈¦94

£¤59

¬«27

£¤75

£¤59¬«27

¬«55

¬«127

¬«11

¬«7

£¤12

¬«9

QC_TILESQC Not Performed on Tile

ReviewedSeam Check Performed on TileSeam Check and QC Performed on TileQC Performed on Tile

#0 CitiesInterstateUS HighwaysState HighwaysRivers

Figure 12. Tiles Reviewed Within Block L-D2Scale: Drawn by: Checked by: Project No.: Date: Sheet:AS SHOWN SMW 4875-007 9/1/2010 1 of 1

lvue

Typewritten Text

Page 29 of 51




Appendix A

Chain of Custody Form

RRBMI Chain of Custody Form

Project Name: RRBMI Block L-D2 QA / QC Priority Area: 3 Block: L-D2 and Big Stone

# Tiles in Block: 2,373

LiDAR Production Company: Fugro-Horizons Horizontal Coord: UTM 14 NAD83 Vertical Datum: NAVD 88

Correspondence Note Recd./Checked By: Date Correspondence Ref. # Pass

Initial Delivery of LiDAR products for Block SMW 1/19/2010 Y

QC check for file completeness SMW 1/19/2010 Y

QC check for proper naming conventions and completeness

RAW LIDAR (LAS Files) SMW 1/19/2010 Y

Filtered Bare Earth Data (LAS Files) SMW 1/19/2010 Y

Bare Earth DEM 1meter (ASCII GRID Files) SMW 1/19/2010 Y

1st Return LIDAR (LAS Files) SMW 1/19/2010 Y

Metadata Record SMW 1/19/2010 Y

LIDAR Report SMW 1/19/2010 Y

Survey Report SMW 1/19/2010 Y

Flight Logs and JPEGs SMW 1/19/2010 Y

COE Requirement Files SMW 1/19/2010 Y

Hybrid Images (TIFF Files) SMW 1/19/2010 Y

Vertical Accuracy Assessment SMW 1/19/2010 Y




Appendix A

Chain of Custody Form (continued)

RRBMI Chain of Custody Form

Project Name: RRBMI Block L-D2 QA / QC Priority Area: 3 Block: L-D2 and Big Stone # Tiles in Block: 2,373

LiDAR Production Company: Fugro-Horizons Horizontal Coord: UTM 14 NAD83 Vertical Datum: NAVD 88

Correspondence Note Recd./Checked By: Date Ending on: Correspondence Ref. # Pass

Visual QA/QC Assessment

Data Voids 8/31/2010

Classification Issues 8/31/2010

Anomalies 8/31/2010

Flight Line Seams 8/31/2010

Metadata Review QC'ed as part of Block A

LIDAR Report Review QC'ed as part of Block A

Pass/Fail Notice Given to LiDAR Vendor TBD

Final LiDAR Products Archived on External Hard Drive TBD

Final LiDAR Products Sent to USGS for Dissemination TBD




Appendix B

Vertical Accuracy Computations by HEI Checkpoints (6 pages)

Block L-D2 HEI Survey Checkpoints (UTM 14 NAD83, NAVD 88)

LiDAR Elevation

s Results

PT ID X Coord Y Coord Z Elev.

(m) Landuse Class

Max PDOP Value

Max HDOP Value

Max VDOP Value

*Z from LiDAR Bare

Earth TIN (m)

Delta Z (m)

Absolute Difference

(cm)

Exceed Blunder Criteria

(Y/N)

4005 681442.435 5032379.6 335.369 BARE EARTH 0.0 1.1 1.3 335.385 0.016 1.6 N

4014 722301.183 5042244.656 353.967 BARE EARTH 0.0 1.0 1.4 353.898 -0.069 6.9 N

4030 741475.243 5072026.796 370.682 BARE EARTH 0.0 0.7 1.2 370.658 -0.024 2.4 N

4039 767883.722 5113513.401 444.387 BARE EARTH 0.0 0.8 1.4 444.327 -0.06 6.0 N

4045 791668.053 5127461.099 439.749 BARE EARTH 0.0 1.0 1.2 439.749 0 0.0 N

4047 782685.678 5128120.457 448.374 BARE EARTH 0.0 1.0 1.1 448.373 -0.001 0.1 N

4052 759368.697 5120927.357 434.052 BARE EARTH 0.0 1.2 2.1 434.201 0.149 14.9 N

1043 696789.636 5114390.788 297.409 BARE EARTH 2.8 1.4 2.4 297.4 -0.009 0.9 N

1040 694242.358 5114059.182 296.56 BARE EARTH 2.4 1.2 2.1 296.7 0.14 14.0 N

1035 710007.783 5098406.799 308.187 BARE EARTH 1.7 1.0 1.3 308.25 0.063 6.3 N

1033 689566.097 5088053.185 309.017 BARE EARTH 1.6 1.0 1.3 308.992 -0.025 2.5 N

1024 683521.543 5076754.35 325.314 BARE EARTH 2.4 1.3 2.1 325.323 0.009 0.9 N

1019 693353.276 5078446.511 302.215 BARE EARTH 1.9 1.0 1.7 302.219 0.004 0.4 N

1012 718632.49 5062322.468 329.67 BARE EARTH 2.2 1.1 1.9 329.762 0.092 9.2 N

1007 696372.883 5048066.314 336.57 BARE EARTH 2.3 1.2 1.9 336.552 -0.018 1.8 N

1006 699119.072 5049193.188 336.255 BARE EARTH 3.4 1.8 2.9 336.293 0.038 3.8 N





LiDAR Elevation

s Results


(m) Landuse Class

Max PDOP Value

Max HDOP Value

Max VDOP Value

*Z from LiDAR Bare

Earth TIN (m)

Delta Z (m)

Absolute Difference

(cm)


(Y/N)

1009 707224.308 5050077.745 342.109 BARE EARTH 2.2 1.3 1.8 342.048 -0.061 6.1 N

1047 678928.804 5123295.442 292.395 BARE EARTH 2.0 1.0 1.7 292.445 0.05 5.0 N

1000 701851.308 5039257.035 358.757 BARE EARTH 2.5 1.3 2.1 358.769 0.012 1.2 N

1002 700645.386 5043096.663 352.83 BARE EARTH 2.3 1.4 1.8 352.908 0.078 7.8 N

4037 741140.632 5113205.57 399.944 BRUSH, LOW TREES 0.0 0.8 0.9 399.88 -0.064 6.4 N

4044 792519.22 5122142.243 434.252 BRUSH, LOW TREES 0.0 0.8 1.0 434.551 0.299 29.9 Y

4048 774370.399 5128249.824 462.224 BRUSH, LOW TREES 0.0 0.9 1.2 462.349 0.125 12.5 N

4056 728476.823 5125240.521 371.859 BRUSH, LOW TREES 0.0 0.5 0.6 372.024 0.165 16.5 N

1028 715548.198 5084031.074 311.856 BRUSH, LOW TREES 0.0 0.8 1.4 311.978 0.122 12.2 N

1021 692683.248 5075194.956 306.076 BRUSH, LOW TREES 2.0 1.0 1.7 306.008 -0.068 6.8 N

1034 707654.453 5098093.056 304.015 BRUSH, LOW TREES 1.8 1.0 1.4 304.134 0.119 11.9 N

1008 698012.475 5048785.162 330.848 BRUSH, LOW TREES 2.3 1.2 1.9 331.101 0.253 25.3 Y

1046 685528.459 5120043.605 293.849 BRUSH, LOW TREES 2.0 1.1 1.7 293.754 -0.095 9.5 N

4007 697104.57 5028319.521 332.458 FORESTED 0.0 3.1 3.4 332.395 -0.063 6.3 N





LiDAR Elevation

s Results


(m) Landuse Class

Max PDOP Value

Max HDOP Value

Max VDOP Value

*Z from LiDAR Bare

Earth TIN (m)

Delta Z (m)

Absolute Difference

(cm)


(Y/N)

4029 742750.122 5080176.245 358.921 FORESTED 0.0 0.7 1.1 358.917 -0.004 0.4 N

4033 746791.687 5084135.397 371.992 FORESTED 0.0 1.1 1.5 372.069 0.077 7.7 N

4040 775339.33 5115829.415 452.208 FORESTED 0.0 1.1 1.7 452.292 0.084 8.4 N

4053 757313.139 5119223.828 414.821 FORESTED 0.0 1.5 2.2 414.913 0.092 9.2 N

1015 700236.975 5066094.05 316.894 FORESTED 1.8 1.1 1.4 316.974 0.08 8.0 N

1001 700733.587 5040315.332 363.014 FORESTED 3.2 1.8 2.6 362.981 -0.033 3.3 N

1027 715386.132 5082429.849 313.786 FORESTED 0.0 4.2 6.4 313.853 0.067 6.7 N

1029 715093.316 5085606.805 311.565 FORESTED 4.4 2.7 3.4 311.631 0.066 6.6 N

1037 709984.92 5102419.356 309.053 FORESTED 5.1 2.9 4.1 309.076 0.023 2.3 N

1042 696577.212 5115717.819 296.915 FORESTED 3.1 1.6 2.6 296.995 0.08 8.0 N

4001 679594.811 5044458.095 341.587 HIGH GRASS, WEEDS, CROPS 0.0 0.8 1.3 341.637 0.05 5.0 N



4013 722243.492 5035852.11 337.475 HIGH GRASS, WEEDS, CROPS 0.0 1.1 1.6 337.385 -0.09 9.0 N







LiDAR Elevation

s Results


(m) Landuse Class

Max PDOP Value

Max HDOP Value

Max VDOP Value

*Z from LiDAR Bare

Earth TIN (m)

Delta Z (m)

Absolute Difference

(cm)


(Y/N)










1020 693277.748 5079757.445 304.07 HIGH GRASS, WEEDS, CROPS 1.9 1.0 1.7 304.291 0.221 22.1 Y







LiDAR Elevation

s Results


(m) Landuse Class

Max PDOP Value

Max HDOP Value

Max VDOP Value

*Z from LiDAR Bare

Earth TIN (m)

Delta Z (m)

Absolute Difference

(cm)


(Y/N)


1030 715562.293 5085717.809 311.811 HIGH GRASS, WEEDS, CROPS 2.2 1.2 1.8 312.039 0.228 22.8 Y










4008 701426.294 5019481.023 334.026 URBAN 0.0 1.0 1.4 334.061 0.035 3.5 N

4010 722959.17 5012578.04 298.904 URBAN 0.0 1.2 2.3 298.969 0.065 6.5 N





LiDAR Elevation

s Results


(m) Landuse Class

Max PDOP Value

Max HDOP Value

Max VDOP Value

*Z from LiDAR Bare

Earth TIN (m)

Delta Z (m)

Absolute Difference

(cm)


(Y/N)

4021 740785.574 5052904.147 345.677 URBAN 0.0 1.0 1.9 345.622 -0.055 5.5 N

4025 734059.502 5097611.709 368.434 URBAN 0.0 0.4 0.4 368.305 -0.129 12.9 N

4027 741274.37 5088752.077 354.872 URBAN 0.0 0.6 0.9 354.712 -0.16 16.0 N

4032 748903.848 5080467.726 376.94 URBAN 0.0 0.7 1.2 376.892 -0.048 4.8 N

4035 746067.74 5109205.066 394.407 URBAN 0.0 1.0 1.1 394.323 -0.084 8.4 N

4041 783613.434 5117057.45 445.922 URBAN 0.0 1.5 2.0 445.935 0.013 1.3 N

4055 738045.94 5117986.606 418.498 URBAN 0.0 0.7 1.1 418.117 -0.381 38.1 Y

4057 722171.752 5130201.29 369.734 URBAN 0.0 0.6 0.9 369.659 -0.075 7.5 N

1014 700500.393 5065912.104 317.252 URBAN 2.7 1.6 2.2 317.155 -0.097 9.7 N

1026 717553.98 5083406.714 317.729 URBAN 2.4 1.3 2.0 317.671 -0.058 5.8 N

1038 694192.654 5117552.38 296.937 URBAN 2.2 1.2 1.9 296.954 0.017 1.7 N

1036 707362.035 5098644.513 304.128 URBAN 1.9 1.0 1.6 304.101 -0.027 2.7 N

1017 694290.25 5075401.767 310.573 URBAN 2.0 1.0 1.7 310.558 -0.015 1.5 N

1011 699001.706 5053401.316 332.12 URBAN 4.8 2.9 3.8 332.185 0.065 6.5 N

1005 700263.376 5049637.642 338.963 URBAN 2.2 1.2 1.8 338.908 -0.055 5.5 N

1048 684429.12 5127820.848 293.852 URBAN 3.2 1.8 2.7 293.834 -0.018 1.8 N

*Note: Z from LIDAR was extracted using Coherent's LP360 software using the TIN method. Elevations were extracted from the Bare Earth LAS files.




Appendix C

Comparison of Vertical Accuracy by Block

Block

No. of

Checkpoints RMSE(z)

(cm)

Minimum

Absolute

Difference

(cm)

Maximum

Absolute

Difference

(cm)

Median

Absolute

Difference

(cm)

Mean

Absolute

Difference

(cm)

Std.

Dev.

(cm)

Skew 95th

Percentile

Value

95% CI

(cm)

A 69 9.6 0.1 28.6 6.4 9.1 6.2 1.1 19.3 +/-18.9

B 58 13.4 0.2 30.4 9.8 9.9 7.1 0.8 24.3 +/-26.3

C 49 8.4 0.1 17.3 5.4 6.9 4.9 0.6 16.1 +/-16.5

E 65 10.6 0.2 34.3 6.8 8.1 6.9 1.4 22.9 +/-20.7

F Not Completed

G 60 10.3 0.1 42.0 6.2 7.4 7.2 2.4 18.6 +/-20.2

H-D1 73 9.5 0.3 37.5 6.0 7.4 6.1 2.0 16.8 +/-18.7

I Not Completed

J Not Completed

K Not Completed

L-D2 87 10.8 0.0 38.1 6.6 8.3 7.0 1.6 21.6 +/-21.2

M Not Completed

N Not Completed

O 58 9.5 0.1 23.1 6.0 7.7 5.6 0.7 17.2 +/-18.6

All

Blocks Not Completed




Appendix D

Visual Assessment Screenshots

This void line runs through most of the block and is between 6 and 7 feet wide

Here is a farm crossing bridge that hasn’t been removed




Appendix D

Visual Assessment Screenshots (continued)

Here is a 2009 aerial view of the area in the previous screen capture




Appendix D


A 3-D view of possible elevation spikes




Appendix D


A second look at the possible elevation spikes, including a cross sectional view




Appendix D


Shown is a large data void, the approximate area is 13,128 sq. meters




Appendix D


Here is another larger area of poor penetration; the total area is approximately 65,753 sq meters




Appendix D


Here is an area where the point density is low in the forested area




Appendix D


Shown is the 2009 aerial of the same location as the previous screenshot




Appendix D


Shown is a smaller data void, the approximate area is 4,051 sq meters




Appendix D


Big Stone




Appendix E

CD-ROM containing an ESRI Shapefile,

HEI Checkpoints, and Photos

Block L-D2 LiDAR 3rd Quality Assessment Report...2.7 Computing the RMSE (z) 18 2.8 Visual Assessment...

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