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FLORIDA GEOGRAPHIC DATA LIBRARY DOCUMENTATION TITLE: Florida (UTM 16) 1-meter NAIP Digital Ortho Photo Image (DOI) - 2010 Geodataset Name: NAIP_UTM16_2010 Geodataset Type: Raster Dataset Geodataset Feature: n/a Feature Count: n/a |
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GENERAL DESCRIPTION:
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DATA SOURCE(S): USDA-FSA-APFO Aerial Photography Field Office SCALE OF ORIGINAL SOURCE MAPS: GEODATASET EXTENT: Florida UTM Zone 16 (Panhandle) |
FEATURE ATTRIBUTE TABLES:
FEATURE ATTRIBUTE TABLES CODES AND VALUES:
32-bit pixels, 4 band color(RGBIR) values 0 - 255 |
NAIP 3.75 minute tile file names are based on the USGS quadrangle naming convention. |
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NAIP imagery is available for distribution within 60 days of the end of a flying season and is intended to provide current information of agricultural conditions in support of USDA farm programs. For USDA Farm Service Agency, the 1 meter GSD product provides an ortho image base for Common Land Unit boundaries and other data sets. The 1 meter NAIP imagery is generally acquired in projects covering full states in cooperation with state government and other federal agencies who use the imagery for a variety of purposes including land use planning and natural resource assessment. With an annual cycle, NAIP is also used for disaster response often providing the most current pre-event imagery. While suitable for a variety of uses the 2 meter GSD NAIP imagery is primarily intended to assess crop condition and compliance to USDA farm program conditions. The 2 meter imagery is generally acquired only for agricultural areas within state projects. |
FSA Digital Orthophoto Specs. |
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Imagery may be replaced to address defects found in a small number of products through quality assurance processes. Imagery containing defects that require the acquisition of new imagery, such as excessive cloud cover, specular reflectance, etc., will not be replaced within a NAIP project year. |
The Florida Geographic Data Library is a collection of Geospatial Data compiled by the University of Florida GeoPlan Center with support from the Florida Department of Transportation. GIS data available in FGDL is collected from various state, federal, and other agencies (data sources) who are data stewards, producers, or publishers. The data available in FGDL may not be the most current version of the data offered by the data source. University of Florida GeoPlan Center makes no guarantees about the currentness of the data and suggests that data users check with the data source to see if more recent versions of the data exist. Furthermore, the GIS data available in the FGDL are provided 'as is'. The University of Florida GeoPlan Center makes no warranties, guaranties or representations as to the truth, accuracy or completeness of the data provided by the data sources. The University of Florida GeoPlan Center makes no representations or warranties about the quality or suitability of the materials, either expressly or implied, including but not limited to any implied warranties of merchantability, fitness for a particular purpose, or non-infringement. The University of Florida GeoPlan Center shall not be liable for any damages suffered as a result of using, modifying, contributing or distributing the materials. A note about data scale: Scale is an important factor in data usage. Certain scale datasets are not suitable for some project, analysis, or modeling purposes. Please be sure you are using the best available data. 1:24000 scale datasets are recommended for projects that are at the county level. 1:24000 data should NOT be used for high accuracy base mapping such as property parcel boundaries. 1:100000 scale datasets are recommended for projects that are at the multi-county or regional level. 1:125000 scale datasets are recommended for projects that are at the regional or state level or larger. Vector datasets with no defined scale or accuracy should be considered suspect. Make sure you are familiar with your data before using it for projects or analysis. Every effort has been made to supply the user with data documentation. For additional information, see the References section and the Data Source Contact section of this documentation. For more information regarding scale and accuracy, see our webpage at: http://geoplan.ufl.edu/education.html |
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The imagery was collected using ADS40-SH51 and ADS40-SH52 digital sensors. Collection was performed using a combination of twin-engine aircraft flying at an average flying height of 17,500 and 27,000 ft above mean terrain with 23% sidelap, giving the collected data nominal ground sampling distance of 0.55 and 0.85 meters, respectively. Based-upon the CCD Array configuration present in the ADS40 digital sensor, imagery for each flight line is 12,000-pixels in width. Red, Green, Blue, Near-Infrared and Panchromatic image bands were collected. Collected data was downloaded to portable hard drives and shipped to the processing facility daily. Raw flight data was extracted from external data drives using GPro software. Airborne GPS / IMU data was post-processed using IPAS, PosPac and/or TerraPos software and reviewed to ensure sufficient accuracy for project requirements. Using Pictovera software, planar rectified images were generated from the collected data for use in image quality review. The planar rectified images were generated at five meter resolution using a two standard deviation histogram stretch. Factors considered during this review included but were not limited to the presence of smoke and/or cloud cover, contrails, light conditions, sun glint and any sensor or hardware-related issues that potentially could result in faulty data. When necessary, image strips identified as not meeting image quality specifications were re-flown to obtain suitable imagery. Aerotriangulation blocks were defined primarily by order of acquisition and consisted of four to seventeen strips. Image tie points providing the observations for the least squares bundle adjustment were selected from the images using an autocorrelation algorithm. Photogrammetric control points consisted of photo identifiable control points, collected using GPS field survey techniques. The control points were loaded in to a softcopy workstation and measured in the acquired image strips. A least squares bundle adjustment of image pass points, control points and the ABGPS was performed to develop an aerotriangulation solution for each block using Pictovera software. Upon final bundle adjustment, the triangulated strips were ortho-rectified to the USGS NED DEM for the project area. The images were re-sampled from the raw resolution of 0.55 meters and 0.85 meters to the required resolution of 1.0 meters. Positional accuracy was reviewed in the rectified imagery by visually verifying the horizontal positioning of the known photo-identifiable survey locations using ArcGIS software. The red, green, blue, and NIR bands were combined to generate a final ortho-rectified image strip. The ADS40 sensor collects twelve bit image data which requires radiometric adjustment for output in standard eight bit image channels. The ortho-rectified image strips were produced with the full 12 bit data range, allowing radiometric adjustment to 8 bit range to be performed on a strip by strip basis during the final mosaicking steps. The imagery was mosaicked using manual seamline generation in Orthovista Seam Editor (OVSE). The 12 bit data range was adjusted for display in standard eight bit image channels by defining a piecewise histogram stretch using OrthoVista software. A constant stretch was defined for each image collection period, and then strip by strip adjustments were made as needed to account for changes in sun angle and azimuth during the collection period. Strip adjustments were also made to match the strips histograms as closely as possible to APFO specified histogram metrics and color balance requirements. Automated balancing algorithms were applied to account for bi-directional reflectance as a final step before the conversion to 8 bit data range. APFO specified DOQQs were extracted from the final mosaic in GeoTIFF format. 4-Band DOQQs were produced and 3-Band RGB CCMs were created. DOQQs corresponding to an individual CCM were reviewed for overall color balance within the CCM. Local corrections were made where necessary to ensure uniformity within the CCM. In the case of DOQQs occurring in more than one CCM, a separate version of the image was generated and balanced for each CCM it occurred in. Process Date: 20110105 |
Projection UTM Zone 16N Datum NAD83 Units METERS Spheroid 1st Standard Parallel 0 2nd Standard Parallel 0 Central Meridian -87 Latitude of Projection's Origin 0 False Easting (meters) 500000 False Northing (meters) 0
DATA SOURCE CONTACT (S):
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USDA-FSA-APFO Aerial Photography Field Office Georectifed Image 2222 West 2300 South Salt Lake City, Utah 84119-2020 801-844-2922 |
Name: FLORIDA GEOGRAPHIC DATA LIBRARY
Abbr. Name: FGDL
Address: Florida Geographic Data Library
431 Architecture Building
PO Box 115706
Gainesville, FL 32611-5706
Web site: http://www.fgdl.org
Contact FGDL:
Technical Support: http://www.fgdl.org/fgdlfeed.html
FGDL Frequently Asked Questions: http://www.fgdl.org/fgdlfaq.html
FGDL Mailing Lists: http://www.fgdl.org/fgdl-l.html
For FGDL Software: http://www.fgdl.org/software.html