Data Management Plan

These files contain 3-band RGB orthorectified mosaic imagery tiles generated from data collected using a Phase One iXM-150F digital camera. This full frame medium-format aerial survey camera collected imagery data in tandem with a bathymetric lidar sensor and a hyperspectral imager on a single remote sensing platform. Native imagery data is not generally in a format accessible to most Geographic Information Systems (GIS). Specialized in-house and commercial software packages were used to process the native imagery data into 3-band orthorectified mosaic imagery that can be imported into GIS software for visualization and further analysis. Trajectories were transformed into positional coordinates using the HTDP (Horizontal Time-Dependent Positioning) software to maintain consistency with the NGS (National Geodetic Survey) reference to the North American Datum of 1983 (NAD83) and the North American tectonic plate coordinates realized from the National Adjustment of 2011, or NAD83 (2011). Horizontal positions, provided in decimal degrees of latitude and longitude, are referenced to NAD83 (2011) at the 2010.00 epoch. Vertical positions, provided in meters, are referenced to the NAD83 (2011) ellipsoid. NGS hybrid geoid model GEOID12B was used to transform the vertical positions from ellipsoidal heights to orthometric heights referenced to the North American Datum of 1988 (NAVD88). The imagery data are in TIF files tiled using 1 km boxes defined by the Military Grid Reference System (MGRS). The file naming convention references the year, effort, area, box number, and data product type. An example file name is, 2022_StampSands_MI_Superior_16TDT0324_RGB.tif, where 2022 is the year of data collection, NCMP is the effort under which data were collected, FL is the area of data collection, 16TDT0324 is the box number and RGB is the data product type.

Process Steps:

• 2022-11-01 00:00:00 - Phase One iXM-150F data were converted from raw Intelligent Image Quality (IIQ) files created during the data collection to unrectified TIF images using the Capture One Processing Engine (COPE) which is a command line file processing utility developed by Phase One as part of their software development toolkit (SDK). A Smoothed Best Estimate of Trajectory (SBET) solution was resolved from the raw aircraft GNSS-IMU positional data using the Applanix POSPac Mobile Mapping Suite (MMS) software package. The Exterior Orientation (EO) parameters and camera misalignments for the imagery were then computed using the Leica IPAS CO+ software package where the values were checked against the known current calibration values for this camera installation. A Digital Elevation Model (DEM) was generated from lidar data collected concurrently with the imagery using an adjacent sensor in tandem with the digital camera on a single remote sensing platform. The unrectified TIF files, EO data, DEM file, SimActive Tile Definition File (TDF), and camera calibration file were given as input to the SimActive Correlator3D software package for processing. Using Correlator3D, the data went through Aerial Triangulation (AT), orthorectification, color balancing, and mosaicking. The mosaic data were exported from Correlator3D as TIF files tiled according to 1 km MGRS grid cells. The mosaic image files were compressed using Geospatial Data Abstraction Library (GDAL) tools by applying the LZW lossless compression method. The compressed mosaic image files were finalized using GDAL and the Esri ArcGIS Desktop software package. GDAL was used to calculate statistics and build pyramids, while ArcGIS was used to create metadata for each image tile. The data processing workflow, including software packages, algorithms and parameters are provided in detail, within this metadata as Process Steps.
• 2022-11-01 00:00:00 - After collection, the navigation data was refined with the Applanix POSPac Mobile Mapping Suite (MMS) software package. A copy of the raw POS data from the Applanix POS AV 610 system was used as input for the navigation post-processing. A reference to the Applanix POSPac Trimble Post-Processed CenterPoint RTX (PP-RTX) correction service was downloaded for kinetic processing. POSPac PP-RTX is a cloud based global GNSS correction service which utilizes Trimble’s RTX technology to provide centimeter level post-processed positioning accuracy without base stations. The Trimble RTX technology utilizes data from a dedicated global network of tracking stations to compute corrections to satellite orbit and clock information as well as atmospheric delay models. After PP-RTX completed, the lever arms and mounting angles were verified to match the values of the current camera installation. At this stage, an automated primary GNSS lever arm calibration was performed to check the auto-calibration values against the original lever arm values to ensure no unexpected offset or drift in the misalignment values had occurred. Using the original lever arm values, the data was then processed using the integrated GNSS-IMU and other aiding sensor data to compute forward-reverse processing, run smoother processing to compute smoothed states, write a Smoothed Best Estimate of Trajectory (SBET) file, and generate Quality Control (QC) reports. The QC reports were then reviewed with special attention paid to the error RMS from each of the north, east, and down positions as referenced by the smoothed performance metrics; Position Dilution of Precision (PDOP) error caused by the relative position of the satellites; and the forward-reverse separation throughout the flight as refined by PP-RTX. Upon satisfactory review, an SBET file was exported from POSPac MMS using the default World Geodetic System 1984 (WGS 84) method where the position data was referenced to the ITRF00 datum with an epoch targeting the mission date. An ITRF (International Terrestrial Reference Frame) is a realization of the ITRS (International Terrestrial Reference System) which through various scales, rotations, and rates applied to its origin are updated for geodetic use as time goes on by producing new solutions every few years. Over time, the WGS 84 reference coordinate system used by the Global Positioning System (GPS) has had several re-adjustments to keep it in line with ITRF updates.
• 2022-11-01 00:00:00 - POSPac MMS transformations are based on the NNR-MORVEL56 (No-Net-Rotation Mid-Ocean Ridge VELocity) tectonic plate model. NNR-MORVEL56 is a set of angular velocities that describe the motions of 56 plates relative to a no-net-rotation reference frame. This SBET file was then transformed from the ITRF00 datum with an epoch corresponding to the mission date to the North American Datum of 1983 (NAD83) and the North American tectonic plate coordinates realized from the National Adjustment of 2011, or NAD83 (2011) at the 2010.00 epoch. The National Geodetic Survey (NGS) has produced several adjustment realizations to NAD83, including NAD83 (2011). While WGS 84 is updated to match ITRF realizations, NAD83 is tied to the North American tectonic plate where its coordinates have been gradually drifting farther from the WGS 84 and ITRF adjustments with the passage of time. Trajectories were transformed into positional coordinates using the HTDP (Horizontal Time-Dependent Positioning) software to maintain consistency with the NGS (National Geodetic Survey) reference to the North American Datum of 1983 (NAD83) and the North American tectonic plate coordinates realized from the National Adjustment of 2011, or NAD83 (2011). Horizontal positions, provided in decimal degrees of latitude and longitude, are referenced to NAD83 (2011) at the 2010.00 epoch. Vertical positions, provided in meters, are referenced to the NAD83 (2011) ellipsoid. NGS hybrid geoid model GEOID12B was used to transform the vertical positions from ellipsoidal heights to orthometric heights referenced to the North American Datum of 1988 (NAVD88).
• 2022-11-01 00:00:00 - The copy of the raw Phase One iXM-150F data was converted from raw Intelligent Image Quality (IIQ) files created during the data collection to unrectified TIF images using the Capture One Processing Engine (COPE) which is a command line file processing utility developed by Phase One as part of their software development toolkit (SDK). Using custom Python scripts, associated data was extracted from the raw camera data to derive the event file, photo ID file, preliminary Exterior Orientation (EO) file, KML (Keyhole Markup Language) files and scaled JPEG images resampled from the TIF images. The KML and JPEG data was used to check the imagery for major collection issues such as coverage discrepancies before further processing. Using Leica’s IPAS CO+ software package, the SBET file was converted to a solution file format usable by IPAS CO+. This solution file, event file, photo ID file, and valid lever arm misalignment values were used by IPAS CO+ to create and export the finalized Exterior Orientation (EO) values as a text file. Using a custom Python script, this text file was then restructured into a format usable by Correlator3D. The unrectified TIF imagery was then subjected to image processing using the SimActive Correlator3D software package. The TIF images, concurrent DEM image, EO file, SimActive Tile Definition File (TDF), and camera installation file were used to build a project in Correlator3D. Aerial Triangulation (AT), orthorectification, color balancing, mosaicking, and tiling were done in a preliminary manner and the data was reviewed. The AT report was reviewed to ensure a satisfactory quality assessment and limited projection error. The automatically generated seamlines were manually adjusted to correct unsatisfactory mosaicking patterns. Next, the corrected mosaic data were exported from Correlator3D as TIF files tiled according to 1 km MGRS grid cells. The mosaic image files were compressed using Geospatial Data Abstraction Library (GDAL) tools by applying the LZW lossless compression method. GDAL was then used to calculate statistics and build pyramids on the compressed mosaic image tiles. The Esri ArcGIS Desktop software package was then used to create metadata for each image tile.

These data have been developed from the best available sources. Although efforts have been made to ensure that the data are accurate and reliable, errors and variable conditions originating from physical sources used to develop the data may be reflected in the data supplied. Users must be aware of these conditions and bear responsibility for the appropriate use of the information with respect to possible errors, scale, resolution, rectification, positional accuracy, development methodology, time period, environmental and climatic conditions and other circumstances specific to these data. The user is responsible for understanding the accuracy limitations of the data provided herein. The burden for determining fitness for use lies entirely with the user. The user should refer to the accompanying metadata notes for a description of the data and data development procedures.