gov.noaa.nmfs.inport:69226 eng UTF8 dataset Office for Coastal Management resourceProvider NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information pointOfContact 2023-09-28T00:00:00 ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for imagery and gridded data ISO 19115-2:2009(E) 2 row 1250 column 1250 point 0 2021 Rocky Creek, MI Natural Color, Color Infrared and Hyperspectral Imagery publication NOAA/NMFS/EDM 69226 https://www.fisheries.noaa.gov/inport/item/69226 WWW:LINK-1.0-http--link Full Metadata Record View the complete metadata record on InPort for more information about this dataset. information imageDigital Wild rice (Zizania palustris and Zizania aquatica - also known as manoomin) plays an integral role in the wetland ecosystems of the Great Lakes and is central to the culture, identity, and livelihood of the Anishinaabeg and other Indigenous peoples throughout the region. As manoomin faces increasing threats from climate change, invasive species, land use change, and other stressors, efforts are underway to protect and restore wild rice populations and habitat. To support these efforts and help improve mapping and monitoring of wild rice in the Lake Michigan and Lake Huron basins, NOAA's Office for Coastal Management, in collaboration with tribal partners, identified twelve Areas of Interest (AOI) as pilot sites for airborne hyperspectral imagery and field data collection, which took place in August and September 2021. AOI/Pilot Sites 1. Christiana Creek, MI 2. Fletcher Pond, MI 3. Flowerfield Creek, MI 4. French Farm Lake, MI* 5. Hamlin Lake, MI 6. Indiana Dunes, IN 7. Manistee River, MI 8. Miller Woods, IN 9. Nottawa Creek, MI 10. Potagannissing, MI 11. Rocky Creek, MI 12. Tawas Lake, MI *Imagery is not available on NOAA's Digital Access Viewer. To request imagery and associated vector and field data for this site, please contact: Jon Mauchmar Wildlife Technician Little Traverse Bay Bands of Odawa Indians Natural Resources Department - Inland Fish & Wildlife Program Office: 231-242-1670 jmauchmar@ltbbodawa-nsn.gov Data was created by Galileo Group, Inc in 2021 for NOAA's 2021 Lake Michigan-Huron Manoomin project covering the Lake Michigan and Huron basins. The purpose of this project was to use airborne hyperspectral data along with ground-based GPS points, geotagged digital imagery, and field spectrometry to delineate wild rice and other vegetative species of interest at twelve Areas of Interest (AOI) in the Lake Michigan and Huron basins. Funded through the Great Lakes Restoration Initiative, this project is a continuation of NOAA's 2018 Lake Superior Manoomin Project, which included airborne hyperspectral imagery and field data collection at six sites in the Lake Superior basin. Galileo Group, Inc. flew and processed the data. completed NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information pointOfContact NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information custodian unknown EARTH SCIENCE > SPECTRAL/ENGINEERING > INFRARED WAVELENGTHS > INFRARED IMAGERY EARTH SCIENCE > SPECTRAL/ENGINEERING > VISIBLE WAVELENGTHS > VISIBLE IMAGERY theme Global Change Master Directory (GCMD) Science Keywords 17.0 CAMERAS instrument Global Change Master Directory (GCMD) Instrument Keywords 14.9 Airplane > Airplane platform Global Change Master Directory (GCMD) Platform Keywords 14.9 MI Michigan Rocky Creek US place U.S. Department of Commerce GLRI Great Lakes Restoration Initiative color infrared hyperspectral natural color orthoimage rectified image theme DOC/NOAA/NOS/OCM > Office of Coastal Management, National Ocean Service, NOAA, U.S. Department of Commerce dataCentre Global Change Master Directory (GCMD) Data Center Keywords 2017-04-24 publication 8.5 Imagery project InPort otherRestrictions Cite As: Office for Coastal Management, [Date of Access]: 2021 Rocky Creek, MI Natural Color, Color Infrared and Hyperspectral Imagery [Data Date Range], https://www.fisheries.noaa.gov/inport/item/69226. NOAA provides no warranty, nor accepts any liability occurring from any incomplete, incorrect, or misleading data, or from any incorrect, incomplete, or misleading use of the data. It is the responsibility of the user to determine whether or not the data is suitable for the intended purpose. otherRestrictions otherRestrictions Access Constraints: None | Use Constraints: None. However, users should be aware that temporal changes may have occurred since this data set was collected and that 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. | Distribution Liability: Users must assume responsibility to determine the appropriate use of these data. DATA SHOULD NOT BE USED FOR LEGALLY BINDING APPLICATIONS. unclassified NOAA Data Management Plan (DMP) NOAA/NMFS/EDM 69226 https://www.fisheries.noaa.gov/inportserve/waf/noaa/nos/ocm/dmp/pdf/69226.pdf WWW:LINK-1.0-http--link NOAA Data Management Plan (DMP) NOAA Data Management Plan for this record on InPort. information crossReference grid eng; US imageryBaseMapsEarthCover ArcGIS 10.3; Microsoft Windows 10; Microsoft Office; Intergraph's suite of photogrammetric products including GeoMedia OrthoPro -85.82583333333 -85.71944444444 41.98666666667 42.03277777778 | Currentness: Ground Condition 2021-08-08 PLEASE READ - For access to the classification vectors for wild rice and other aquatic vegetation, and field data, including geotagged photos, field spectrometer readings, and stalk density measurements, please contact: Jennifer Kanine, PhD, CWB Director Department of Natural Resources (269) 782-9602 main; (269) 462-4214 desk Pokagon Band of Potawatomi NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information distributor https://coast.noaa.gov/htdata/raster7/imagery/GL_RC_CIR_2021_9749 WWW:LINK-1.0-http--link Bulk Download Simple download of data files. download https://coast.noaa.gov/dataviewer/#/imagery/search/where:ID=9748 WWW:LINK-1.0-http--link Customized Download Create custom data files by choosing area, map projection, file format, etc. download https://coast.noaa.gov/htdata/raster7/imagery/GL_RC_HSI_2021_9747 WWW:LINK-1.0-http--link Bulk Download download https://coast.noaa.gov/htdata/raster7/imagery/GL_RC_RGB_2021_9748 WWW:LINK-1.0-http--link Bulk Download download https://coast.noaa.gov/dataviewer/#/imagery/search/where:ID=9749 WWW:LINK-1.0-http--link Customized Download download https://coast.noaa.gov/dataviewer/#/imagery/search/where:ID=9747 WWW:LINK-1.0-http--link Customized Download download dataset Representativeness Geo-accuracy was checked and confirmed to meet pre-established quality standards by systematic comparison of specific geo-locations acquired in the field with a GPS unit and high resolution RGB imagery of known geo-accuracy. Accuracy Radiometry is verified by visual inspection of the digital orthophoto. Slight systematic radiometric differences may exist between adjacent orthoimage files; these are due primarily to differences in source image capture dates and sun angles along flight lines. These differences can be observed in an image's general lightness or darkness when it is compared to adjacent orthoimage file coverages. Tonal balancing may be performed over a group of images during the mosaicking process which may serve to lighten or darken adjacent images for better color tone matching. Horizontal Positional Accuracy Geo-accuracy was checked and confirmed to meet pre-established quality standards by systematic comparison of specific geo-locations acquired in the field with a GPS unit and high resolution RGB imagery of known geo-accuracy. Completeness Report Orthoimages are visually inspected for completeness to ensure that no gaps or image misplacements exist within and between adjacent images. These images are derived by mosaicking multiple images to ensure complete coverage. Source imagery is cloud free. Photography was flown during leaf-off in deciduous vegetation regions. Conceptual Consistency All GeoTIFF tagged data and image file sizes are validated using commercial GIS software to ensure proper loading before being archived. This validation procedure ensures correct physical format and field values for tagged elements. Seamlines and tile edges are visually inspected. Seamline mismatches are not corrected unless the overall displacement exceeds one meter. Airborne Hyperspectral Data Collection - An AISA KESTREL 10 Visual through Near Infrared (VNIR) Hyperspectral Imaging Sensor System (400 - 1,000 nm spectral range) was utilized by Galileo Group Inc. (Galileo) for airborne collection operations. A total of 178 spectral bands for the VNIR (Visible Near Infrared) range were collected with a spectral resolution of around 3.5 nm and a Ground Sampling Distance (GSD) of 1.0m. The FOV (Field of View) was 40 degrees. An Oxford Solutions Survey+ 2nd Generation GPS/IMU simultaneously collected navigation and attitude data. TerraStar-C from Novatel Inc. was utilized for all airborne collection operations to further enhance spatial accuracy. TerraStar is a Real Time Kinetic (RTK) airborne correction service that improves horizontal (~4-5 cm RMS) and vertical accuracy (~6.5 cm RMS). The sensor system was installed in a Cessna 172 Skyhawk which was used as the airborne imaging platform for the duration of the project. Ground Truthing Data Collection - Ground truthing was conducted primarily onboard a canoe and along the shoreline where accessible. An ASD FieldSpec Pro VNIR (400-1000nm) was utilized to collect spectrometry of wild rice when found. A Trimble Pro XRT DGPS system and two handheld digital cameras with integrated GPS were used to collect GPS points and geo-tagged imagery of target species and landmarks of interest. A specially modified iPhone 6 equipped with a Galileo custom created ground truthing application (ARMADA) and linked with a sub-meter accuracy Trimble Bluetooth antenna was utilized as a secondary GPS point logging device. 2022-12-01T00:00:00 Processing Level 1a Radiometric Correction 1. Dark Noise Removal- Dark image data was acquired for every raw image at the end of every flight line by the sensor control software closing the shutter and recording 3 seconds of dark noise. To remove sensor noise the mean value of every line of the dark data was subtracted from the corresponding line of the raw data (dark noise removal or dark current removal). 2. Calibration from RAW data to radiance data using calibration file- After the dark noise removal, the raw data was calibrated to radiance units using a sensor specific calibration file. Every spatial and spectral pixel is multiplied with the corresponding value in the calibration file. The calibration values for each pixel on the CCD are calculated using an integrating sphere in the laboratory. The radiance units are equal to (mW/cm^2*str*um)*1000.00. 3. Smile Correction- Spectral smile is defined as changes in wavelength over the field of view (FOV). Smile correction was performed by proprietary algorithms. 4. Crosstrack Correction- A crosstrack correction was performed using proprietary algorithms in order to normalize illumination in the across-track direction of each flight line. 5. Quality Control- Quality control was accomplished using ASD measurements, established radiometric quality protocols and systematic manual evaluations. Processing Level 1b Atmospheric Correction 1. Model-based Atmospheric Correction- The radiance data were converted to reflectance using the Atmospheric & Topographic Correction (ATCOR-4) software package. ATCOR uses the Modtran 4, a complex radiative transfer model, to correct for atmospheric absorption (O2, O3, and CO2), scattering (Mie and Rayleigh) and path radiance effects. The calibrated radiance data was then converted to reflectance pixel count (reflectance ranges 0.0 to 1.0 multiplied by 10000) using modeled solar irradiance and solar angle data from the time of acquisition. The reflectance pixel counts were then converted to 16-bit reflectance data. The reflectance units are equal to Reflectance*10000. 2. Quality Control- The quality control was accomplished using established atmospheric correction quality protocols and systematic manual evaluations. Ground based spectrometer data at impervious and spectrally intransient surfaces such as asphalt were utilized for rigorous QA/QC of the reflectance data. Spectral curves from the ground spectrometer data were compared to the final reflectance results and found to be sufficiently consistent. Further parameter adjustment was then applied to the data to maximize spectral consistency between the flight lines. 2022-12-01T00:00:00 Processing Level 2 Geometric Correction 1. Calculation of the sensor offset (Boresight correction) - During the aerial acquisition, four special Boresight flight lines were flown to geometrically calibrate the sensor and GPS/INS. The Boresight parameters were calculated using four overlapping flight lines flown in a crosshair pattern. 15 to 20 Ground Control Points per flight line pair (GCPs) were identified and used to calculate geometric correction values for Roll (0.180527), Pitch (-0.0533453) and Yaw (0.00885310). These values were then used as input parameters for the geometric correction process. 2. GPS/INS Data- The GPS/INS Data was encoded and processed for the use in the georectification process. 3. GLT files (Geographic Lookup Table)- A GLT file contains the geographic location of every pixel in the unrectified reflectance data. A GLT file was generated for every flight line using the GPS/INS Data, the Boresight Correction parameters and a Digital Elevation Model (DEM). Processing Level 3 Orthorectification 1. Georectification using GLT data- The unrectified reflectance data was then Georectified into North American Datum of 1983 (NAD83) and projected into the Universal Transverse Mercator (UTM) coordinate system using the corresponding GLT file. A DEM was used to correct for surface elevation variation across the scene. 2. Mosaicking- Individual flight lines for each AOI were combined into a single mosaic image which covered the entire AOI. This image was then masked to the AOI boundary and tiled according to the tiling scheme vectors included with this delivery. 3. Quality Control- Geo-accuracy was checked and confirmed to meet pre-established quality standards by systematic comparison of specific geo-locations acquired in the field with a GPS unit and high resolution RGB imagery of known geo-accuracy. 2022-12-01T00:00:00 Data Processing Galileo Group, Inc. originator 2018