20201214 08122700 1.0 FGDC CSDGM MetadataVerify - ISD GIS FALSE Ortho_SoCo_SonomaVeg_2013 Local Area Network 6123217.000000 6463417.000000 1801402.000000 2217202.000000 1 Projected GCS_NAD_1983_2011 Linear Unit: Foot_US (0.304801) NAD_1983_StatePlane_California_II_FIPS_0402_Feet_2011 <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.7'><WKT>PROJCS[&quot;NAD_1983_StatePlane_California_II_FIPS_0402_Feet_2011&quot;,GEOGCS[&quot;GCS_NAD_1983_2011&quot;,DATUM[&quot;D_NAD_1983_2011&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic&quot;],PARAMETER[&quot;false_easting&quot;,6561666.666666666],PARAMETER[&quot;false_northing&quot;,1640416.666666667],PARAMETER[&quot;central_meridian&quot;,-122.0],PARAMETER[&quot;standard_parallel_1&quot;,38.33333333333334],PARAMETER[&quot;standard_parallel_2&quot;,39.83333333333334],PARAMETER[&quot;latitude_of_origin&quot;,37.66666666666666],UNIT[&quot;Foot_US&quot;,0.3048006096012192]]</WKT><XOrigin>-115211800</XOrigin><YOrigin>-93821500</YOrigin><XYScale>36983428.057351544</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.0032808333333333331</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision></ProjectedCoordinateSystem> 8 FALSE None 4 AMD TRUE continuous unsigned integer 4100 15000 1000 20 2048 20 75 0.01 10 600 300 Basic 1 NorthWest,Center,LockRaster,ByAttribute,Nadir,Viewpoint,Seamline,None None,JPEG,LZ77,LERC None None,Basic,Base-Top Height,Top-Top Shadow Height,Base-Top Shadow Height,3D -1 -1 0.8 1 NorthWest,Center,LockRaster,ByAttribute,Nadir,Viewpoint,Seamline,None None,JPEG,LZ77,LERC None,Basic,Full NaturalColorRGBI Name,MinPS,MaxPS,LowPS,HighPS,Tag,GroupName,ProductName,CenterX,CenterY,ZOrder,Shape_Length,Shape_Area 109350 0.5 2187 <_docversion_ Sync="TRUE">9 20201219 07085100 20201219 07085100 150000000 5000 WSI 503-505-5100 503-546-6801 421 SW 6th Ave, Suite 800 Portland OR 97204 US ArcGIS Metadata 1.0 Sonoma County Agricultural Preservation and Open Space District (707) 565-7369 747 Mendocino Ave, Suite 100 Santa Rosa CA 95401 US 2014-03-21 Sonoma County Vegetation Mapping and LiDAR Program remote-sensing image Ortho_SoCo_SonomaVeg_2013 <div style='text-align:Left;'><div><div><p><span>These data are LiDAR orthorectified aerial photographs (8-bit GeoTIFF format) within the Sonoma County Vegetation Mapping and LiDAR Program's project area. Imagery was collected in fall, 2013. The imagery coverage corresponds to the Sonoma County 2013 LiDAR survey data extent and encompasses approximately 1,047,999 acres. A GSD (Ground Sample Distance) resolution of 6 inches was used for each four-band color pixel. WSI recommends viewing the orthoimagery in ESRI ArcMap software using a raster catalog. For best results, stretch type should be set to 'None' and Gamma Stretch should not be applied (Layer Properties -&gt; Symbology Tab). The specified coordinate system for this dataset is California State Plane Zone II (FIPS 0402), NAD83 (2011), with units in US Survey Feet.</span></p></div></div></div> The Sonoma County Vegetation Mapping and LiDAR Program (http://sonomavegmap.org) and the University of Maryland (under grant NNX13AP69G from NASA’s Carbon Monitoring System, Dr. Ralph Dubayah, PI) contracted LiDAR and orthophoto data collection for all of Sonoma County in late 2013. Also included in the data collection were two areas in Mendocino County - the Soda Spring Creek-Dry Creek Watershed and Lake Mendocino. This fine scale data will help provide an accurate, up-to-date inventory of the county’s landscape features, ecological communities and habitats. Project funders include: NASA, the University of Maryland, the Sonoma County Agricultural Preservation and Open Space District, the Sonoma County Water Agency, the California Department of Fish and Wildlife, the United States Geological Survey, the Sonoma County Information Systems Department, the Sonoma County Transportation and Public Works Department, the Nature Conservancy, and the City of Petaluma. Sonoma County Vegetation Mapping and LiDAR Consortium, NASA, University of Maryland, Watershed Sciences, Inc., Tukman Geospatial LLC Sonoma County Mendocino Lake Dry Creek Sonoma County WSI Airborne Survey Light Detection and Ranging LiDAR Rectified Orthophotographs Ortho Digital Orthophoto Orthophotography high resolution color imagery color infrared CIR NIR near-infrared aerial photographs ISO 19115 Topic Categories imageryBaseMapsEarthCover Imagery Base Maps Earth Cover Sonoma County Mendocino Lake Dry Creek Sonoma County WSI Airborne Survey Light Detection and Ranging LiDAR Rectified Orthophotographs Ortho Digital Orthophoto Orthophotography high resolution color imagery color infrared CIR NIR near-infrared aerial photographs Data were provided by the University of Maryland and the Sonoma County Vegetation Mapping and LiDAR Program (http://sonomavegmap.org) under grant NNX13AP69G from NASA’s Carbon Monitoring System (Dr. Ralph Dubayah, PI). This data is available for unrestricted public use. However, users should acknowledge the source of the data in any reports, publications, or presentations where the data is used. <div style='text-align:Left;'><div><div><p><span>Data were provided by the University of Maryland and the Sonoma County Vegetation Mapping and LiDAR Program (http://sonomavegmap.org) under grant NNX13AP69G from NASA’s Carbon Monitoring System (Dr. Ralph Dubayah, PI). This data is available for unrestricted public use. However, users should acknowledge the source of the data in any reports, publications, or presentations where the data is used.</span></p></div></div></div> -123.548077 -122.345272 38.098597 39.246035 Ground condition during daylight hours orthophoto survey - UltraCam Eagle 260 megapixel camera 2013-10-01 2013-10-28 Version 6.2 (Build 9200) ; Esri ArcGIS 10.7.1.11595 1 -123.548161 -122.341434 39.249894 38.098596 Flight lines have been examined to ensure that there was at least 60% sidelap, there are no gaps between flight lines, and overlapping flight lines have consistent elevation values. All orthophotographs have been processed and reviewed for contracted accuracy and completeness. Orthophoto mosaics were reviewed at a scale of 1:2000 and reviewed against the LiDAR intensities to ensure no seam artifacts or offsets. Raw acquired images were radiometrically and geometrically corrected using the camera’s calibration files. The resulting radiometry is then manually edited by digitally adjusting output levels, exposure and intensity, atmospheric haze correction, and applying hotspot dodging. This ensures that each image has the appropriate tone, no pixels are clipped, and that each image frame is blended with its neighbors. Once radiometry has been edited, separate RGBI and Panchromatic images are blended together to form single pan-sharpened 4 band TIFF images. During the mosaicking stage, orthorectified frames are color balanced a second time using an automated global tilting method and in certain cases, further manual balancing. Despite these extensive radiometric blending techniques, occasional frame to frame radiometric discrepancy may exist within the final mosaics due to bi-directional solar reflectance, changing sun angle, or difficult atmospheric conditions. To assess the spatial accuracy of the orthophotographs, they were compared against check points identified from the LiDAR intensity images. The checkpoints were distributed evenly across the total acquired area, and were measured on surface features such as painted road lines and fixed high-contrast objects on the ground surface. Horizontal accuracy applies only to the portion of the swath that was orthorectified to the LiDAR-derived DEM. Outside of that, accuracy and radiometry at ortho seams are not guaranteed. The accuracy of the final mosaic was calculated in relation to the LiDAR-derived control points. The orthophoto horizontal accuracy is reported as the root-mean-square error (RMSE). 0.27 meters Acquisition. Orthophoto data acquisition was conducted from October 1 to October 28, 2013. The survey utilized a UltraCam Eagle 260 megapixel camera system mounted in a Cessna 208-B Grand Caravan. 2013-10-28 Processing. 1. Resolve GPS kinematic corrections for aircraft position data using kinematic aircraft GPS (collected at two hertz) and static ground GPS (one hertz) data collected over geodetic controls. 2. Develop a smoothed best estimate of trajectory (SBET) file that blends post-processed aircraft position with attitude data. Sensor heading, position, and attitude will be calculated throughout the survey. 3. Create an exterior orientation (EO) files for each photo image with omega, phi, and kappa. 4. Convert “Level 00” raw imagery into geometrically corrected “Level 02” image files. 5. Apply radiometric adjustments to “Level 02” image files to create “Level 03” Pan-sharpened tiffs. 6. Apply EO to photos, measure ground control points, and perform aerial triangulation. 7. Import DEM, orthorectify, and clip triangulated photos to specified area of interest. 8. Mosaic orthorectified imagery, blending seams between individual photos and correcting for radiometric differences between photos. 2014-03-21 680400 0.500000 831600 0.500000 2 1 0 6123217.000000 1801402.000000 6123217.000000 2217202.000000 6463417.000000 2217202.000000 6463417.000000 1801402.000000 6293317.000000 2009302.000000 Red 255.000000 2.000000 8 Green 255.000000 4.000000 8 Blue 255.000000 2.000000 8 Infrared 255.000000 0.000000 8 This raster data set represents high resolution orthophotographs acquired during an aerial survey. WSI 20201219 /9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCACFAMgDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwDZkge3 fDjjsR3pR+lSF54Li5S42SRkjy89QPT/AOvR5YdS0Rz6pnkfT1pJjGZphOT6UpppGeRSl8LIn8LJ FJxyaQilUjbzTW4HtVFDGSN5I3fcrxghHU8gHqPfpS3Oo3+k26NDdRzRSyH5CoyqdT1H+c1G5PY1 HJ+/i8tndRz90gEg9R9KTjcadgs7u61G3e6uYdmZCFI6FSSV/SpjxWXBINDurm6uHH2VYmKRhflk J6KfQ5xz7GmeHL6XUInjuJhJMHypwFDAjoPXHNJMDTbIqLPNXbiF0iDFCAeAe1UsEVQjRXEujt8o 3RyZB749P51RWtHRXR5JLaQErKBgDrnp/ImqNxE1vcPG3UHGfWkhsVcBRzTmY465qIMCRmlchCOM 0CAt8q/rVu2cAFGAIYdxms8tkipkfAptAaJvZ4XTy7eUKgG8jv8ATPaqz+I4JNVS3Nv5Cu2DKXHJ 9vaoTcLb7ZZTtGeOev0rEnvHa7Dm3XZ52JFIHyqDgc9vXmsmraFOTOw1SYw2lwUTdvTy0Hbn8qXT IIVgty20TOuEV2G449Kx7/VVvokWFf3K58zqGXHTA7+tZhmvUj/dRMJEOIXIxjvwfrmpWxMX+v5n oOoIr28CxQsmxdsgPPzdcisaCe3kR3Ese1JPLYlwMNnAFcVH/b+iML6K7dRI2HiADgL9D1p0VjFL E9xYXTS+bnc2Op9Paq2K5j0lrHCGHgu2MD86K4DTtC2jfdyLnktk/wCNFESYPQ3r9xHcIvlkCTOG ByCe9QbmTkZ49K1HEckR8wKwU557e9ZG9WztYN7g1aKZOJRL9/Ct/eHf60jKVPPWq55FSRSlPlcb k9KJfCyJ/CyQOpYqPvAAn8aCQOvSrs8Gnva/arVpBLkLJGxHA55/Os5iB61QyOTg8HiowaexA6Ub lx05oAjkjiuY/LmRXX0YVVt9New1CO409AVkcIYSxxnHb3PNXCcHOKv6fIwmwiI7j51D9Mjv+WaU loC3NZbWe6gE95gBzlUwRhOwPvWZf2ccKq0bZDHofT61wl3d3Wka0s8M63VwrZZUfcGB55IPQ5rr pJMnYmNo/ujA/AelSk0U2mFsz296kyA/Jg57ZBq/qgM8fmOqrIncHh1J4PPfOaq209xIq2SHKO+d pHfpmrOrupxtTGDt3E5zjr+HNN7oS2ZknJ7VJMHypPTApsWXkVcDLHFTXgZLhoiR8nHFUIjEXQki nD5AznG1VLc9P85pqMTxU2px/ZNHfcrtJKBjaMkAEHpSbsBlyX0Ut+sE6LLnKl2JJjbnIUEYxUtv opBLRrshAygJOQfXHp7Vd0y2t5EjlKncFDZcc59frV+4XzARwP0rPcpJPU477HqRvY0uZ1dQSflH AHAzkY5BzXW6ZcrDGIp402bRy+CGPOf5D86hNgWYMTg9ahMRgLLtkYYyQOc+wojZomCt+JpXtjb3 SNGCHRuq1mpo6p5kSOIoyCRsAyD7VLGGjb5CWX6cLV1ElkgcocsOhHJB+lPYtq5RY7YvKmLO3ALd 6KsSabNHctDeeZHIF+ZJQBz6qRx696KUZaEQV1deZeYBHIxwa5+5sv7Klmlt4zIkhLtu4x+IrqGj DfWq80YK81ZRzNtfw3Q2ghJehjY8g4yfrVlTjiqmoaBbTSPJCBDK2AWXgYzz071X+2vZtDbTI7sp CvK3yjB6Hnr2H50pPRmc/hZqpI0bBlPSpjtnICDa5/hzwfpmqtvJHcRCSJ1dD0IqVo8D6VZQxkIJ BBB9DQgFTrMsqhZvvDo/cfX1pGh2Ec8HoR0NAEbD5aS5hk/sC/mjk8s4WMt6KT836VKV4qtqWo3V roVxb2yRszsDudQdo7nn8PzpO9gIfCuk2/kX8iCKSWJVeMg5I9cfhV1l2kg1jeHZbuO+spvOMPms Vlyow574HYcjn1roJ04DVKeo+ha0hYoJftkq79hwiZxubtWddzPNM5Yg/MTx05PatCy5hUENxJyB 0weKqNaMsjK3BBxTW43sMsAo1CDcQAHByfrRq0bJfyZzhsEE9xiljhb7Qq85JFa9x5F2xS4H7mEH EuQpHr+FPZitdFTR7IODPKMqPuj1PrVfxNdG3MMaIxaUN8wGcDir13reladHEgmV93AWIhiBg8kf hXL6trNrfvFNHeGGWPLKrcEDuPT/ABqHqPZGloTxtbPE7N57HCeZ346etWFuYfNWORwrsSFychsY 6Hp3FZWgNYXUU2y5DksOpOUcd8/j+ntT2sTp91uYiSJmyzdweeR9KFoJaJG4MueQxHrS7NxwMVX0 q/JAtZpFM6+3Uev69q0pkLxbI3VZeCC3Pfn07VMRxen3l/TYo51KvHGNvy8DqPcUsNtotxqc9tMz wLZfvXIkKbmxwVwe27+XvTLEmKQIkib+pbpkVpNa2l35kzIsdy24B1HJGMfMKE7Mpq6MK60y0u7R pbS6lYGLzUmuiTjaevIwBn6+vPYrSuoIotN2NuZYIVBwoGQM5OB2oojrqZwVlb1/Mp9DVW6kVGVS eXOB9assRjBNZjJNdEGJC/lMzMSfujkZ/WtEUytMPmzVe4toruExyqPVW7g1JJLk00Mc0pfCzOfw sis7GOytFSN9+WO9sY+YcdPoBU/tUu4uixLEcAFt47HuCPyqEnnrVIqxBjr6ipIpzGNp+Zf7p6U0 4Epz3pGX0pgWtgdS8WSO6nqP8ajBCuH2hgDyp6EelRRu0bBlJBHcVNapbgSLtAeSRnZicZJ60AR3 kM8say6WvlzZ/hQvtHpjvWXpss9lfTHUrqVhMxXDZKh+vAHTrXUWjLAHiSZBKcNtc7cgf/rrk9ct 7ywvZGvIn8uefejqoYqMcnPQ9u/as1o9Bva51TXAtrOVyAFVSXIPI9+a5+71vUL6ZILcrGEQFpQo Znyowc4/zmr2l6j/AGneyIYvJtWiOBIwLv2+mDmuV1D7Ra6lchZljAk2AquAoBwPxo3YNuxsLq8m jzobmb7W8q5Ks20oPfjP4VtyXElzoE7wSB5G67OcDOSOOlYM2ltqen2upMommCbSDwThjhv5VzZ1 vUNKjktbBxFcSSfvAADwPqOtFr6IL23L9xcQQhpJC7OUBjjLEE8AdenrTLbQhqlpNOzLFPIRuwOg 9vQYrHS5mibzZJXnkbG5Cc7T1/AZrttN8oqXe3a2lcKhG7IOM8j86aXKJalfQ9BTTruSVZAcqAAM 84/z+tdJMBNCYXQMpXBGfbkVJDbRpEx9up7UxYjaoSQZGyTxTK2K1vELUNIYSzBfkyeV/Hntmkur bUW8qbTr0yoiBWDRjcT3JB59Kle4V5AqhgemVpTyw/eFWHcHBqIqxMdv67jbTVruxiMl1a7pVZlY xnHTGMA9etbdtdSPAso35cBhu4IrOae6MbNujlXaR+8Tkj0/Shb1zEDHHDHgfdJ/T2otctM1bSRm ut5JJ7g85HOaKyrK01NdZW/V9yMOYnfAC44GPqP1opRaRMVdff8AmWpX4ODzVO8u5J2XzW4VQnAx x/nmpZ25qhK24+taIbGlcuc9T1+vekf5SBTudme4/wA/y/lUTHJolsyJ/CyRJZVjbyGCyEYG7oRn kH8KSRDG9RqxByOlWpR50AkzllGPfH+eKfUoqSEFlP50pyOB0qN+VyOtSKcp70xDDz0pu7ByOtOb g+9Rn72KALlteqpVZo1kQf3hyPpV3UoU1LTjBFJaxRAeaUY5PHcZ6dxmsYLzXM3kbXGvTtseJ0IC S45PAGBz71MktwuXbwy2enicXUZbCqgR8cHPtkcc/iKrR2lwBFNJKZElG5mYFzt/OnzWsZtXkvTK 8ybfLbIJbn7uO3HPvXWeFrM3emEkFVVuMj5cY7VN9BpXdhbO8jvLSGW3OyEp+7VuOPSm3Oh6fPex zyQlpGGWCHaHPvircugxK6LGoCLwAvGPaklka1ZUuGAUHEbgc0ehXqZv/CL2T3v2yKIxvu3bD90f hVubThB8zJkg9QelaMNyORIpIGMMD1H0qY4mtySec/eA4zRsFkUYpfLfaPuHAH1qw67+RTBAeHYL 70/ovU/gcZqhEX2Zcs2MNUkcCA5Kn16dKCfnJ9u1Sh/k3EjFStiYbfeQSKFUBv1pbG086bBQGFTk kH9KVszSKqqSScDHetm1t1iiC8HHUjvVFFu1jUznC8lRx+dFRLIbafcp7DH60VCFC9jlp5uKqLkt uP4VPLhiPSomYCtAuKDzx36fX/PFQt97A6dqfuoZejf5/wA5/nSl8LIn8LGDgYqzasxfyxnHOcen eqo5NOErQuHBwR6U2i0RTjZIRjinRMGQg9qnvwZgkoweOStZ6sUamtUDJXYg4P4UrLnBFRPICaes irGWdsBRkk9AKBExTGBjNZmqbLd1uTLGCeAjk5J9AM5/KtG3uI7m3SWJtyOMqfauW11l1G6iMUbA W+QZc4wSe35CpautQZraXaRXerwlwZEc/vC5yWA65/Ku6sru3trcWcaGOJQQqs39a8wIdrpjbs/n AYZ42IHTHbtXZWvmS2EDSMxl24bd1yOtRYpM3zKgyoBH41FL5cwAdFbPr2qkkrBBlSw9uo+lTg8A nG3pk/1qhgbdfuIDsI4INRcxyMI5Nrjnn0+lTrEikOjscngemKiuo2H3WB3etAiNLoy/KxGT3q1C gkUruUADPvWQsgZirJhgcHtir1mjiQYYnNAxr7ixAfByOVPSpYUGQXb5fT8asNEWkd02qR17jNT2 sCyXAyB5fVsevp+NTF6Ex2+8uWdgkeJtp+fhc/zq0seJPmWrBkHC4Ax2oMnzcdB1qiis1uXmwe4H Pp1oqzy0rEf3Rz+JoqEhQ2+84KQ4PFQMalk61D1NbIQAkGnhs/Ln3phNC8emRSlsyJ/CxT8v4VFK 3GPzp8nqOn+cf59qqyvg1Qyxb30kCGIEbGPXGcfhWXJqSS3vk+W+4sRv2gA++BUpbHf6VlyWc1o/ mGbAcZU/3VU849/1qZaajuWrzUIrIAP80rfcjB5NZk9hdajcGe4uNtvgMioSQuKWOP7VdSX90FXa f3eAfu84qhqGvWTLLGgDpKuMOGGwgYz9f/rUnJv4QNGeJYGile6ZcthWjbjoAcgfT6VrWcYuhmE7 Y0chywHz46kVytnH9pkaWN18w9Cq5GMd6tNqOp2MscUPzR7tzAADcfep5b6XGmjtdI0q3S9aaGRX hVcbGGDn1A7/AFrb8lFkIIJ9DjmuXs9Rtr+FGt5FLbdxUHDKe9XotSu1fas5YYAwwBos0XobqQhf Ug+lWAoAJUAnHQ96xft00y7nLHb6AZA9sVraRbyX0qM0h8kDc8mOgp7biNO20Weez8+EICTxGx5b HXbWVPItmpEqSblPIxzmumE3mOMZVU4Uf3RTr23ttVi23J8ubGFnA6+zDuKhSuNo4O4nFyGdQQG6 ZGCKbYx3JmMafOxBK+orWvNOksLgwzKo4yhHKsPUGmWn+iS+YsRZnXZgCrEOsHkQulwrMXIVFYci tmFFtk/d9Ryc1HpyrLumdCCo43Hp16VoPCvljanJxURJht9/5iQyrJgnBcdqkIU/NkAelUyjBhtG MdxUkhbht2V+lNMuxOHVZGxz8o6/jRVcSHzyQv8ACP60UR2Ijt95wzEMcgjHtUbcVECynNSCTIxw K1AiJINPjPIpxVdhP8X6VFg7s570pfCyJ/Cx00gWN8/wjNU870DEbQRnBq2lpvP2hmXy1+Vk3YY5 9BRcQIzAwBvL7Bjk49TVDKccLSt6Ack1QvpzcSpbxFjChySRgZIzg+/Sq5nut91GlzIyyOUPy5AX PygA++Prmtbw/o5uoypZ1jYZmbbznHPXocgVEpDWpjataGS0hkQlbcHB6bTxn/GuVlsZr+czbcBv ujIGBjiut8Zrcf2rFYGQx2yRqyEngnuT78Gs+xjMMTMCSAvykgjcoB4HH60L3UN7mdp11No11tZQ w6neMg12V5oq37R3Abajru2DjJxmsK+s42jJ3KySEkOD1Pbn1r0Dwrpt3qGk2kKxI+E2E7sAY460 m0wWujOF0mxmt9bMiLgHKNGeo/ziupji3zAgduldW/hE2Ex/eW3mnnlzuAPuRSWuhW8EhluZwfSO Lk/n0H60uddWUotIo6Vok19n5ljAI3SN0H/1/auk88RwLYQBjFEcbn6uf8OvHvT0dbZFdY9iAfu0 HQepz3NRKo8zzBnNZuTZVrC/aFjO053Y7inm4KoqoN0rnCj3qU222BpZP+A5HWm2duwlMkoAlwML /dFLYC9Hao1v5Fwq3Ebj5w47+oPas648OXKSIbBy0Lno5GU+vt9K27SFpWz0UCr2c7hjIFOLYPyM aXS5Ld/kbzEVF3YHI5POKSRNyjBBHc+1akESLcSSZA+QZbp3aqRmstRmuI7GZfMjwHOPkYntn1qo bXM4/wCZQDBAcc57UmzMbDg57Z6USQvEzK6FX7rUTs0MZLYA75qrF3I1yJW7DAyfzoqq9yzucDC4 GFI+vWilHYiO33nGNj0puABnmiitOVEcqEWTAxj9amCg0UUpRXKyZxXKyM48zGKWeQ21u8y8kYAH 1OM/rRRT5UVyoraXbLJeRzu7s7tsOTx37fhmuqtIRERFEFRAcAAUUVjyq5cIL+mc943023S0iu5Q ZWZsMCcZBycfpXMaRFDbagqhXbDMmWf/AOtRRRbQfIr/APBGz2dv5qfK2xpBtXdwuQOR717D8PbM HQTLGVXEjKAVz079RRRUyQuRX/4J1N1YG9XDvGHHRxGc/wA654WzeZy64Hbb/wDXooqXFWTKjFf0 x0zSFsblAwOAv/16dZQmW5jQlME91/8Ar0UUcqHyr+my7dmSS6WNmTCDP3Tz+tOEcgOQ6Z6Z2f8A 16KKHFCUF/TZctvO+55iY6fcP+NTqszNjzEyo67D/jRRTSBwX9M5TxHezrcfZwyhFRMhQRkn157Z rStbNbFk0+LZsXJLbTlm7seaKKdtCIQVvv6mh5T3R8pjGAANp2HK8euaxbmF1naN3R9rFc7PT8aK KqKHyL+mV2tcyElhwufu/X3oooojFWJhFW+8/9k=