MULTI – SOURCE I2I VERIFICATION (ORTHO + LIDAR INTENSITY)

Absolute Accuracy Verification: .125 Foot (GSD) RGB Image DataTuck Mapping, Co-Acquired Ortho and LiDARRMSE X = 0.11 | RMSE Y = 0.06 | CE90 = 0.18 | CE95 = 0.21 (Feet)

Relative Accuracy Verification: .25 Foot (GSD) Pan Intensity ImageTuck Mapping, Co-Acquired Ortho and LiDARRMSE X = 0.14 | RMSE Y = 0.08 | CE90 = 0.23 | CE95 = 0.27 (Feet)

SUMMARY AND CONCLUSIONS

Current trends in acquisition and use of high-resolution orthophoto and LiDAR data present challenges in areas of automated, efficient, consistent, and scalable methods of data accuracy verification. Frequency of updates as well as multi-resolution and multi-source data means that new methods must be validated not only for absolute verification of data against surveyed checkpoint, but also for relative accuracy between data sets to assure co-alignment and agreement of data. New methods presented for extracting iChips from high-accuracy reference data is shown to provide a systematic and practical basis for relative accuracy verification. Embedding iChips with symbols at survey checkpoints and the photo identified locations makes use of iChip data and extraction of necessary information easy and effective. The methods presented provide a sound basis for standardizing collections of iChips for accuracy verification programs.

PROCEDURE FOR USING I2I TOOLS

STEP 1: Load Test Image Data Set and iChips as ReferenceSelect the First iChip and Zoom for Desired Level of DetailNote that the Data Table is Absent of Location Data

STEP 2: Zoom and Pan on iChip as DesiredSelect Survey Checkpoint Location on iChipsData Table X & Y for Survey Locations are Populated

STEP 3: Zoom on Test Data Location as NeededSelect Corresponding Photo Location on Ortho Test DataData Table X & Y for Image Derived Locations are Populated

SAMPLE TEST CASES

Absolute Accuracy Verification: 0.25 Foot (GSD) RGB Image DataSioux Falls, South Dakota, USGS Eros Data Center Test RangeRMSE X = 0.28 | RMSE Y = 0.17 | CE90 = 0.48 | CE95 = 0.55 (Feet)

Absolute Accuracy Verification: 0.50 Foot (GSD) CIR Image DataSioux Falls, South Dakota, USGS Eros Data Center Test RangeRMSE X = 0.40 | RMSE Y = 0.32 | CE90 = 0.78 | CE95 = 0.89 (Feet)

Relative Accuracy Verification (I2I): 0.50 Foot (GSD) CIR Image DataSioux Falls, South Dakota, USGS Eros Data Center Test RangeRMSE X = 0.47 | RMSE Y = 0.31 | CE90 = 0.84 | CE95 = 0.96 (Feet)

ABSTRACT

Rapidly evolving mapping technologies and information necessitate the practical application and standardization of new core technologies for the verification of map content for updates and maintenance. Automated methods that speed and inform the verification process are emerging that offer the ability to more effectively conduct absolute as well as relative geolocation accuracy verification. These methods combine the use of checkpoint data, point-to-image analysis, and image-to-image analysis for absolute and relative accuracy verification of orthophotos.

Checkpoint data collection and offset analysis, once a tedious and laborious process, may now be completed via mostly automated processing. The absolute accuracy of high resolution orthophotos may be verified in an automated processing environment using point-to-image (P2I) methods. As part of the automated processing, georeferenced image chips (iChips) may be extracted for desired areas around each checkpoint location. The iChips would include the full resolution and contents of the original image and would be “embedded” with marker symbols at photo identified features and their surveyed locations. These iChips may be used for enhanced image-to-image (I2I) relative accuracy verification of new image collections.

Novel methods of relative accuracy verification are presented using reference data embedded with absolute accuracy information to provide results closely approximating those achieved through absolute accuracy checkpoint analysis methods. Utilizing iChips embedded with marker symbols at surveyed checkpoints enables the selection of the survey marker symbols in the iChip as the reference location and the corresponding feature in the new imagery as the test location for offset analysis. P2I absolute accuracy verification are presented and compared with iChip enabled I2I methods demonstrating the benefits of this fused methodology for geolocation accuracy verification.

INTRODUCTION

The quantification of geolocation accuracy and uncertainty is most frequently conducted based on absolute or relate measurements of offset. For absolute quantification, survey-grade locations of ground features are acquired and employed as checkpoints against which image derived locations for the feature are compared to determine offset in X and Y. In relative assessments, similar features are identified in a reference and a test image set and offset is compared between the two data sets and used to compute accuracy statistics.

Both absolute and relative accuracy and agreement are important to determine the usefulness and quality of data for intended purposes. The determination of relative accuracy may be of specific interest in cases such as the following:

Multi – Temporal Images: Collections of Images Taken Over Time.

Multi – Resolution Images: Collections of Images Collected at Different Resolutions.

Multi – Source Images: Images Acquired by Different Sensor Platforms for a Common Area of Interest (AOI).

Summary of Process Workflow

1) Conduct Absolute Accuracy Analysis Using Surveyed Checkpoints, Offset Analysis, and Statistical Calculation. 2) Generate Georeferenced Image Chips (iChips) for Checkpoint Locations with Symbol Markers Showing Survey Locations.

3) Conduct Relative Accuracy Assessment Using iChips as Reference Data and Identifying Photo Locations in Test Image Data.

Acknowledgements:

USGS EDC Data Verification TeamTuck MappingIADIWG

Fusing Absolute and Relative Methods for Enhanced Geolocation Accuracy VerificationChuck O’Hara, Spatial Information Solutions, Starkville, MS / Mississippi State University, Geosystems Research InstituteGreg Stensaas, U.S. Geological Survey, Sioux Falls, SD

Image-to-Image (I2) Tools Image-to-Image (I2) Tools accuracy analyst accuracy analyst TMTM

ASPRSNovember 14 – 19, 2010 Orlando, Florida

Collection of Image Chips (iChips) from Orthophoto and LiDAR Intensity DataTuck Mapping Data Sets Co-Collected During Helicopter Data Acquisition Mission