Description: Road networks were digitized by hand using NAIP 2012 imagery as a back drop. Specifically, the 2012 NAIP Midland Quadrangle was used, which is a subset of the NAIP Jefferson County Kansas file. The projection of this imagery is NAD83_UTM_Zone_15N, with a linear unit of 1 meter. Road types were catagorized as gravel or unimproved (2-track) and were specified by Dean Kettle before digitizing.This shape file was digitized by Ry Patton in November 2014.
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Copyright Text: You may use these data freely, however, when you use the data please acknowledge the Kansas Biological Survey at the University of Kansas as appropriate.
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Description: The initial objective for producing maps of changing forest cover was to obtain digital imagery completely covering the southern half of the Midland quad that went back in time as far as possible. All aerial photography used was taken in the summer with-on conditions. Recent digital imagery was obtained first, in the form of black and white digital orthophoto quarter quads (DOQQ's) from 1991 and color infrared (CIR) imagery in a digital format from 2002. The Kansas Data Access and Support Center (DASC) provided the 1991 DOQQ's at 1 m ground resolution in UTM NAD27 projection system. Two DOQQ's from 1991 were required to cover the southern half of the Midland Quad. The historical data that were located contained between 9 to 11 black and white aerial photography prints for each of the following years: 1941, 1954, 1966 and 1976. These hardcopy photographs were archived at the Douglas, Jefferson and Leavenworth County Planning and/or Farm Service Agency offices. All photographs were in a 24 by 24-inch enlarged format, which were originally flown at a scale of 1:20,000 and collected on 10 by 10-inch negatives covering 2.84 ground miles on a side. The agencies that possessed these photos would not allow prints to leave their facilities, so a laptop computer. The agencies that possessed these photos would not allow these prints to leave their facilities, so a laptop computer and small format (8.5 by 14 in) desk scanner were used to capture the images in a digital format. Each 24 square-inch photo print was scanned into 4 images (or fewer if part of the image fell outside the study area), each spanning approximately 1 square ground mile (one PLSS section). Using a 300 dpi scanning resolution, the images had a ground pixel size of approximately 0.64 m, which allowed for down sampling at the time of rectification to match the 1 m resolution of the 1991 and 2002 data sets. This process resulted in 24 images per study year from 1941 to 1976, one for each of the 24 PLSS sections in the study area. Data Preprocessing Prior to classification, the next objective involved pre-processing the digital aerial photography. Image geo-rectification was performed in the ERDAS Imagine software package using the Image Geometric Correction tool. Seven to ten ground control points (GCP's) per image were used to perform a second order polynomial transformation with an RMS error of 2 m or less. When resampling the imagery to 1 m ground resolution, the cubic convolution resampling method was used to maintain the spatial character of the data and avoid the jagged results characteristic of nearest neighbor resampling. The more recent historical photographs, from 1976 and 1966, were geo-rectified using the 1991 DOQQ as the reference image, while the older historical photographs from 1954 and 1941 used the newly geo-rectified 1966 imagery for reference. This shift in the reference imagery for the rectification of the older photography was done because it became increasingly difficult to identify GCP objects, such as roads and buildings, in common with the 1991 DOQQ. Once rectified, the yearly data sets were still made up of multiple individual images: 24 images for the 1941, 1954, 1966 and 1976 dates; and 2 images for 1991. Before classification, it was decided that mosaicking the images together into a complete dataset would be beneficial to reduce mismatch along the edges of images during classification. ERDAS Imagine's Mosaic tool was used to stitch all photos from each year together into a single raster dataset covering the study area. During mosaicking, images were cropped in overlapping areas, manual cut lines were drawn and feathering techniques were used to blend datasets together with the goal of reducing the visibility of seam lines. The mosaicking process resulted in six georeferenced aerial photography data sets from 1941 to 1991 with an approximate temporal interval of 10 years (Figure 2). Attempting to classify the entire study area for each year would have been unfeasible for several reasons. Of primary concern was the contrast difference between and within the original photographs. For example, the spectral information describing a tree object in a bright portion of the mosaic could be confused with the spectral information of a non-forest grassland object in a darker section. Also, the large amount of time required to manually check and clean up the results of the classification for the entire quad would make it difficult to break up the workflow on this project into discrete manageable pieces. For these reasons, the final preprocessing step divided up the complete mosaics into the 24 PLSS sections contained in the mosaic (Figure 3). This process resulted in 144 section-sized images (six years of 24 sections each), which were the basis of the classification procedure. Matthew D. Dunbar 's 2005 MasterThesis: Mapping, Analyzing, and Visualizing 60 Years of Forest Cover Change in Northeast Kansas. In 2007, the resulting images were converted to NAD83 by Jorgina Ross
Description: FSA National Agriculture Imagery Program (NAIP): FSA National Agriculture Imagery Program (NAIP) 2010. Projection/Datum: UTM Zone 14/NAD832010 MrSID compressed Farm Service Agency (FSA) NAIP 3 band color aerial imagery tiled by county in 1-meter resolution.
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Copyright Text: The Aerial Photography Field Office asks to be credited in derived products.
Description: This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP acquires 4-band digital ortho imagery from airbourne and/or space based platforms during the agricultural growing seasons in the U.S.. A primary goal of the NAIP program is to enable availability of ortho imagery within sixty days of acquisition. The NAIP provides 1 meter GSD ortho imagery rectified within +/- 6 meters to true ground at a 95% confidence level. The tiling format of NAIP imagery is based on a 3.75' x 3.75' quarter quadrangle with a 300 (plus or minus 30) pixel buffer on all four sides. The NAIP imagery is formatted to the UTM coordinate system using the North American Datum of 1983 (NAD83). The NAIP imagery may contain as much as 10% cloud cover per tile. This file was generated by compressing NAIP imagery that cover the county extent. Two types of compression may be used for NAIP imagery: MrSID and JPEG 2000. Target value for the compression ratio for 1 meter GSD is (15:1).The 2012 NAIP Midland Quadrangle Map is a subset of the 2012 NAIP Jefferson, County, Kansas file.
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Copyright Text: The USDA-FSA Aerial Photography Field Office asks to be credited in derived products.