US Forest Service as modified from the US Census states data 20111130 vector digital data http://data.fs.usda.gov/geodata/edw/datasets.php The State_Gen feature class is the generalized spatial representation of the United States, the District of Columbia, Puerto Rico, American Samoa, Guam, Northern Mariana Islands, and Virgin Islands. The data are an extract of the Census codes and boundaries from the following Census FTP site: ftp://ftp2.census.gov/geo/tiger/TIGER2015/. Since the Census data do not include the coastline detail, the coastal boundaries have been included through a spatial erase using the Census Hydrography data from the Census FTP site: ftp://ftp2.census.gov/geo/tiger/TIGER2015/AREAWATER/. After erasing the coastline, the data was generalized using the ESRI Simplify Polygon function. The State_Gen feature class is a US Forest Service Standard Reference Dataset and is the preferred spatial representation of US States. It should be used only for small-scale cartographic products. The purpose of the generalized State_Gen dataset is to improve map display and drawing performance in both ArcGIS applications and ArcGIS Server map services. To satisfy both performance improvement and geometry representation, the following parameters and geoprocessing method were used. Simplify the input features using the Douglas-Peucker simplification algorithm with a specified maximum offset tolerance of 375 meters. The output features will contain a subset of the original input vertices. Min scale refers to what scale the layer turns off when zooming out. Max scale refers to the scale the layer turns off at when zooming in. Min scale: 0, no minimum scale set, Max Scale: 1:4622325. The State_Gen feature class describes the generalized location and boundaries of the United States, the District of Columbia, and the US territories. It includes common identifiers for these entities so this data set can be used in conjunction with other data sets describing states. This feature class is a US Forest Service Standard Reference Dataset and is the preferred spatial representation of States for use by the US Forest Service. It should only be used for small-scale cartographic products. 2015 publication date Complete As needed -178.226818 146.081774 71.382691 -14.599463 ISO 19115 Topic Categories boundaries None USA US United States of America Intended for internal Forest Service use or for use by applications with a need to display state boundaries to external audiences. The USDA Forest Service makes no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liability or responsibility for the accuracy, reliability, completeness or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and land users should exercise due caution. The data are dynamic and may change over time. The user is responsible to verify the limitations of the geospatial data and to use the data accordingly. USFS Chief Information Office, Enterprise Data Warehouse physical Washington DC 20250 Please send an e-mail to the address below. data@fs.fed.us Esri ArcGIS 10.2.2.3602 Spatial data was visually inspected to ensure that no invalid gaps or polygon overlaps exist within the dataset. Topological tests using Esri ArcGIS were also done to ensure the same. For states with multi-polygon features only one attribute record will exist. The entire coastline was visually inspected to verify absence of slivers, and those found were deleted. Attribute data was also visually inspected for completeness. State_Gen attribute schema was checked to ensure correct US Forest Service schema names, data types, data length, precision, and scale were used. All features from the Census Bureau state dataset were included in the State_Gen dataset. However, due to the incorporation of the coastline and the subsequent generalization of the polygons, the area of some states will be smaller than the original Census Bureau state dataset. The following Census Bureau State attributes: REGION, DIVISION, LSAD, MTFCC, FUNCSTAT, ALAND, AWATER, INTPTLAT, and INTPTLON that are not part of the Forest Service State schema were dropped. Generalized data with a target scale of 1:740,000. Coordinates in the data have six implied decimal places, but the positional accuracy of these coordinates is not as great as the six decimal places suggest. The Generalized State dataset is created through a six part process. First, the state dataset is downloaded from the Census Bureau FTP site at ftp://ftp2.census.gov/geo/tiger/TIGER2015/. Second, Esri 'Add field' and 'Populate field' tools are run in order to change attribute names from Census Bureau attribute schema to that of Forest Service. Then, hydrography dataset for each county is downloaded from Census Bureau FTP site at ftp://ftp2.census.gov/geo/tiger/TIGER2015/AREAWATER/. All datasets are merged, and features that will form the coastline are selected. Finally, the erased state dataset is generalized using Esri's 'Simplify Polygon' python function with a 375 meters simplification tolerance parameter; the two fields automatically generated by the 'Simplify Polygon' tool are dropped. 2016 Vector Simple FALSE 56 TRUE FALSE 8.98315284119521e-009 8.98315284119521e-009 Decimal Degrees D North American 1983 GRS 1980 6378137.0 298.257222101 BdyDesg_State_Gen A collection of geographic features with the same geometry type (such as point, line, or polygon), the same attributes, and the same spatial reference. http://support.esri.com/en/knowledgebase/GISDictionary/term/feature%20class Feature Class 56 OBJECTID Internal feature number. ESRI OID 4 10 0 Sequential unique whole numbers that are automatically generated. OBJECTID STATECODE 2010 Census state Federal Information Processing Standards (FIPS) code. ANSI String 2 0 0 List of U.S. State Codes http://www.census.gov/geo/reference/ansi_statetables.html STATECODE GNIS_ID The Geographic Names Information Systems (GNIS) code for this state. Geographic Names Information System String 8 0 0 List of Geographic Names Information System Codes http://geonames.usgs.gov/ GNIS_ID STATE_POSTAL_ABBR United States Postal Service state abbreviation US Postal Service String 2 0 0 List of U.S. State Abbreviations http://pe.usps.gov/text/pub28/28apb.htm STATE_POSTAL_ABBR STATENAME 2010 Census state name US Census String 100 0 0 List of U.S. State Names http://www.census.gov/geo/reference/ansi_statetables.html STATENAME GIS_ACRES The area of the feature in acres, calculated in North American Albers Equal Area Conic projection, North American Datum 1983 (NAD83). US Forest Service Double 8 38 8 Positive numbers GIS_ACRES SHAPE Feature geometry. ESRI Geometry 8 0 0 Coordinates defining the features. Shape SHAPE.AREA Not Used, SDO Geometry. Area of feature in internal units squared. ESRI Double 0 0 0 Positive real numbers that are automatically generated. SHAPE.AREA SHAPE.LEN Not used, SDO geometry. Length of feature in internal units. ESRI Double 0 0 0 Positive real numbers that are automatically generated. SHAPE.LEN USFS Chief Information Office, Enterprise Data Warehouse physical Washington DC 20250 Please send an e-mail to the address below. data@fs.fed.us The USDA Forest Service makes no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liability or responsibility for the accuracy, reliability, completeness or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and land users should exercise due caution. The data are dynamic and may change over time. The user is responsible to verify the limitations of the geospatial data and to use the data accordingly. 20170110 USFS Chief Information Office, Enterprise Data Warehouse physical Washington DC 20250 Please send an e-mail to the address below. data@fs.fed.us FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998 local time USFS Chief Information Office, Enterprise Data Warehouse Please send an e-mail to the address below. Washington DC 20250 SM.FS.data@usda.gov 20250319 ArcGIS Metadata 1.0 USFS Chief Information Office, Enterprise Data Warehouse Please send an e-mail to the address below. Washington DC 20250 SM.FS.data@usda.gov http://data.fs.usda.gov/geodata/edw/datasets.php Enterprise Geodatabase Feature Class S_USA.BdyDesg_State_Gen 2011-11-30 US Forest Service as modified from the US Census states data vector digital data <DIV STYLE="text-align:Left;"><DIV><P><SPAN>The State_Gen feature class is the generalized spatial representation of the United States, the District of Columbia, Puerto Rico, American Samoa, Guam, Northern Mariana Islands, and Virgin Islands. The data are an extract of the Census codes and boundaries from the following Census FTP site: ftp://ftp2.census.gov/geo/tiger/TIGER2015/. Since the Census data do not include the coastline detail, the coastal boundaries have been included through a spatial erase using the Census Hydrography data from the Census FTP site: ftp://ftp2.census.gov/geo/tiger/TIGER2015/AREAWATER/. After erasing the coastline, the data was generalized using the ESRI Simplify Polygon function. The State_Gen feature class is a US Forest Service Standard Reference Dataset and is the preferred spatial representation of US States. It should be used only for small-scale cartographic products. The purpose of the generalized State_Gen dataset is to improve map display and drawing performance in both ArcGIS applications and ArcGIS Server map services. To satisfy both performance improvement and geometry representation, the following parameters and geoprocessing method were used. Simplify the input features using the Douglas-Peucker simplification algorithm with a specified maximum offset tolerance of 375 meters. The output features will contain a subset of the original input vertices. Min scale refers to what scale the layer turns off when zooming out. Max scale refers to the scale the layer turns off at when zooming in. Min scale: 0, no minimum scale set, Max Scale: 1:4622325.</SPAN></P></DIV></DIV> The State_Gen feature class describes the generalized location and boundaries of the United States, the District of Columbia, and the US territories. It includes common identifiers for these entities so this data set can be used in conjunction with other data sets describing states. This feature class is a US Forest Service Standard Reference Dataset and is the preferred spatial representation of States for use by the US Forest Service. It should only be used for small-scale cartographic products. USFS Chief Information Office, Enterprise Data Warehouse Please send an e-mail to the address below. Washington DC 20250 SM.FS.data@usda.gov USA United States of America US ISO 19115 Topic Categories boundaries USA boundaries United States of America US The USDA Forest Service makes no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liability or responsibility for the accuracy, reliability, completeness or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and land users should exercise due caution. The data are dynamic and may change over time. The user is responsible to verify the limitations of the geospatial data and to use the data accordingly. Intended for internal Forest Service use or for use by applications with a need to display state boundaries to external audiences. <DIV STYLE="text-align:Left;"><DIV><P><SPAN>The USDA Forest Service makes no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liability or responsibility for the accuracy, reliability, completeness or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and land users should exercise due caution. The data are dynamic and may change over time. The user is responsible to verify the limitations of the geospatial data and to use the data accordingly.</SPAN></P></DIV></DIV> Esri ArcGIS 13.3.0.52636 publication date 2015-01-01 -178.226818 146.081774 -14.599463 71.382691 1 -179.147236 179.778471 71.390383 -14.548578 Spatial data was visually inspected to ensure that no invalid gaps or polygon overlaps exist within the dataset. Topological tests using Esri ArcGIS were also done to ensure the same. For states with multi-polygon features only one attribute record will exist. The entire coastline was visually inspected to verify absence of slivers, and those found were deleted. Attribute data was also visually inspected for completeness. State_Gen attribute schema was checked to ensure correct US Forest Service schema names, data types, data length, precision, and scale were used. All features from the Census Bureau state dataset were included in the State_Gen dataset. However, due to the incorporation of the coastline and the subsequent generalization of the polygons, the area of some states will be smaller than the original Census Bureau state dataset. The following Census Bureau State attributes: REGION, DIVISION, LSAD, MTFCC, FUNCSTAT, ALAND, AWATER, INTPTLAT, and INTPTLON that are not part of the Forest Service State schema were dropped. Generalized data with a target scale of 1:740,000. Coordinates in the data have six implied decimal places, but the positional accuracy of these coordinates is not as great as the six decimal places suggest. The Generalized State dataset is created through a six part process. First, the state dataset is downloaded from the Census Bureau FTP site at ftp://ftp2.census.gov/geo/tiger/TIGER2015/. Second, Esri 'Add field' and 'Populate field' tools are run in order to change attribute names from Census Bureau attribute schema to that of Forest Service. Then, hydrography dataset for each county is downloaded from Census Bureau FTP site at ftp://ftp2.census.gov/geo/tiger/TIGER2015/AREAWATER/. All datasets are merged, and features that will form the coastline are selected. Finally, the erased state dataset is generalized using Esri's 'Simplify Polygon' python function with a 375 meters simplification tolerance parameter; the two fields automatically generated by the 'Simplify Polygon' tool are dropped. 2016-01-01 56 20170112 09565500 1.0 BdyDesg_State_Gen -179.147236 179.778471 -14.548578 71.390383 1 002 Geographic GCS_North_American_1983 Angular Unit: Degree (0.017453) <GeographicCoordinateSystem xsi:type='typens:GeographicCoordinateSystem' 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/3.3.0'><WKT>GEOGCS[&quot;GCS_North_American_1983&quot;,DATUM[&quot;D_North_American_1983&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433],AUTHORITY[&quot;EPSG&quot;,4269]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>999999999.99999988</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>8.98315284119521e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>4269</WKID><LatestWKID>4269</LatestWKID></GeographicCoordinateSystem> 20250319 10063600 20250319 10063600 150000000 5000 FGDC original metadata PD94bWwgdmVyc2lvbj0iMS4wIiBlbmNvZGluZz0idXRmLTgiPz4NCjxtZXRhZGF0YT4NCiAgPGlk aW5mbz4NCiAgICA8Y2l0YXRpb24+DQogICAgICA8Y2l0ZWluZm8+DQogICAgICAgIDxvcmlnaW4+ VVMgRm9yZXN0IFNlcnZpY2UgYXMgbW9kaWZpZWQgZnJvbSB0aGUgVVMgQ2Vuc3VzIHN0YXRlcyBk YXRhPC9vcmlnaW4+DQogICAgICAgIDxwdWJkYXRlPjIwMTExMTMwPC9wdWJkYXRlPg0KICAgICAg ICA8dGl0bGU+U19VU0EuU3RhdGVfR2VuPC90aXRsZT4NCiAgICAgICAgPGdlb2Zvcm0+dmVjdG9y IGRpZ2l0YWwgZGF0YTwvZ2VvZm9ybT4NCiAgICAgICAgPG9ubGluaz5odHRwOi8vZGF0YS5mcy51 c2RhLmdvdi9nZW9kYXRhL2Vkdy9kYXRhc2V0cy5waHA8L29ubGluaz4NCiAgICAgIDwvY2l0ZWlu Zm8+DQogICAgPC9jaXRhdGlvbj4NCiAgICA8ZGVzY3JpcHQ+DQogICAgICA8YWJzdHJhY3Q+VGhl IFN0YXRlX0dlbiBmZWF0dXJlIGNsYXNzIGlzIHRoZSBnZW5lcmFsaXplZCBzcGF0aWFsIHJlcHJl c2VudGF0aW9uIG9mIHRoZSBVbml0ZWQgU3RhdGVzLCB0aGUgRGlzdHJpY3Qgb2YgQ29sdW1iaWEs IFB1ZXJ0byBSaWNvLCBBbWVyaWNhbiBTYW1vYSwgR3VhbSwgTm9ydGhlcm4gTWFyaWFuYSBJc2xh bmRzLCBhbmQgVmlyZ2luIElzbGFuZHMuIFRoZSBkYXRhIGFyZSBhbiBleHRyYWN0IG9mIHRoZSBD ZW5zdXMgY29kZXMgYW5kIGJvdW5kYXJpZXMgZnJvbSB0aGUgZm9sbG93aW5nIENlbnN1cyBGVFAg c2l0ZTogZnRwOi8vZnRwMi5jZW5zdXMuZ292L2dlby90aWdlci9USUdFUjIwMTUvLiBTaW5jZSB0 aGUgQ2Vuc3VzIGRhdGEgZG8gbm90IGluY2x1ZGUgdGhlIGNvYXN0bGluZSBkZXRhaWwsIHRoZSBj b2FzdGFsIGJvdW5kYXJpZXMgaGF2ZSBiZWVuIGluY2x1ZGVkIHRocm91Z2ggYSBzcGF0aWFsIGVy YXNlIHVzaW5nIHRoZSBDZW5zdXMgSHlkcm9ncmFwaHkgZGF0YSBmcm9tIHRoZSBDZW5zdXMgRlRQ IHNpdGU6IGZ0cDovL2Z0cDIuY2Vuc3VzLmdvdi9nZW8vdGlnZXIvVElHRVIyMDE1L0FSRUFXQVRF Ui8uIEFmdGVyIGVyYXNpbmcgdGhlIGNvYXN0bGluZSwgdGhlIGRhdGEgd2FzIGdlbmVyYWxpemVk IHVzaW5nIHRoZSBFU1JJIFNpbXBsaWZ5IFBvbHlnb24gZnVuY3Rpb24uIFRoZSBTdGF0ZV9HZW4g ZmVhdHVyZSBjbGFzcyBpcyBhIFVTIEZvcmVzdCBTZXJ2aWNlIFN0YW5kYXJkIFJlZmVyZW5jZSBE YXRhc2V0IGFuZCBpcyB0aGUgcHJlZmVycmVkIHNwYXRpYWwgcmVwcmVzZW50YXRpb24gb2YgVVMg U3RhdGVzLiBJdCBzaG91bGQgYmUgdXNlZCBvbmx5IGZvciBzbWFsbC1zY2FsZSBjYXJ0b2dyYXBo aWMgcHJvZHVjdHMuIFRoZSBwdXJwb3NlIG9mIHRoZSBnZW5lcmFsaXplZCBTdGF0ZV9HZW4gZGF0 YXNldCBpcyB0byBpbXByb3ZlIG1hcCBkaXNwbGF5IGFuZCBkcmF3aW5nIHBlcmZvcm1hbmNlIGlu IGJvdGggQXJjR0lTIGFwcGxpY2F0aW9ucyBhbmQgQXJjR0lTIFNlcnZlciBtYXAgc2VydmljZXMu IFRvIHNhdGlzZnkgYm90aCBwZXJmb3JtYW5jZSBpbXByb3ZlbWVudCBhbmQgZ2VvbWV0cnkgcmVw cmVzZW50YXRpb24sIHRoZSBmb2xsb3dpbmcgcGFyYW1ldGVycyBhbmQgZ2VvcHJvY2Vzc2luZyBt ZXRob2Qgd2VyZSB1c2VkLiBTaW1wbGlmeSB0aGUgaW5wdXQgZmVhdHVyZXMgdXNpbmcgdGhlIERv dWdsYXMtUGV1Y2tlciBzaW1wbGlmaWNhdGlvbiBhbGdvcml0aG0gd2l0aCBhIHNwZWNpZmllZCBt YXhpbXVtIG9mZnNldCB0b2xlcmFuY2Ugb2YgMzc1IG1ldGVycy4gVGhlIG91dHB1dCBmZWF0dXJl cyB3aWxsIGNvbnRhaW4gYSBzdWJzZXQgb2YgdGhlIG9yaWdpbmFsIGlucHV0IHZlcnRpY2VzLiBN aW4gc2NhbGUgcmVmZXJzIHRvIHdoYXQgc2NhbGUgdGhlIGxheWVyIHR1cm5zIG9mZiB3aGVuIHpv b21pbmcgb3V0LiBNYXggc2NhbGUgcmVmZXJzIHRvIHRoZSBzY2FsZSB0aGUgbGF5ZXIgdHVybnMg b2ZmIGF0IHdoZW4gem9vbWluZyBpbi4gTWluIHNjYWxlOiAwLCBubyBtaW5pbXVtIHNjYWxlIHNl dCwgTWF4IFNjYWxlOiAxOjQ2MjIzMjUuPC9hYnN0cmFjdD4NCiAgICAgIDxwdXJwb3NlPlRoZSBT dGF0ZV9HZW4gZmVhdHVyZSBjbGFzcyBkZXNjcmliZXMgdGhlIGdlbmVyYWxpemVkIGxvY2F0aW9u IGFuZCBib3VuZGFyaWVzIG9mIHRoZSBVbml0ZWQgU3RhdGVzLCB0aGUgRGlzdHJpY3Qgb2YgQ29s dW1iaWEsIGFuZCB0aGUgVVMgdGVycml0b3JpZXMuIEl0IGluY2x1ZGVzIGNvbW1vbiBpZGVudGlm aWVycyBmb3IgdGhlc2UgZW50aXRpZXMgc28gdGhpcyBkYXRhIHNldCBjYW4gYmUgdXNlZCBpbiBj b25qdW5jdGlvbiB3aXRoIG90aGVyIGRhdGEgc2V0cyBkZXNjcmliaW5nIHN0YXRlcy4gVGhpcyBm ZWF0dXJlIGNsYXNzIGlzIGEgVVMgRm9yZXN0IFNlcnZpY2UgU3RhbmRhcmQgUmVmZXJlbmNlIERh dGFzZXQgYW5kIGlzIHRoZSBwcmVmZXJyZWQgc3BhdGlhbCByZXByZXNlbnRhdGlvbiBvZiBTdGF0 ZXMgZm9yIHVzZSBieSB0aGUgVVMgRm9yZXN0IFNlcnZpY2UuIEl0IHNob3VsZCBvbmx5IGJlIHVz ZWQgZm9yIHNtYWxsLXNjYWxlIGNhcnRvZ3JhcGhpYyBwcm9kdWN0cy48L3B1cnBvc2U+DQogICAg PC9kZXNjcmlwdD4NCiAgICA8dGltZXBlcmQ+DQogICAgICA8dGltZWluZm8+DQogICAgICAgIDxz bmdkYXRlPg0KICAgICAgICAgIDxjYWxkYXRlPjIwMTU8L2NhbGRhdGU+DQogICAgICAgIDwvc25n ZGF0ZT4NCiAgICAgIDwvdGltZWluZm8+DQogICAgICA8Y3VycmVudD5wdWJsaWNhdGlvbiBkYXRl PC9jdXJyZW50Pg0KICAgIDwvdGltZXBlcmQ+DQogICAgPHN0YXR1cz4NCiAgICAgIDxwcm9ncmVz cz5Db21wbGV0ZTwvcHJvZ3Jlc3M+DQogICAgICA8dXBkYXRlPkFzIG5lZWRlZDwvdXBkYXRlPg0K ICAgIDwvc3RhdHVzPg0KICAgIDxzcGRvbT4NCiAgICAgIDxib3VuZGluZz4NCiAgICAgICAgPHdl c3RiYz4tMTc4LjIyNjgxODwvd2VzdGJjPg0KICAgICAgICA8ZWFzdGJjPjE0Ni4wODE3NzQ8L2Vh c3RiYz4NCiAgICAgICAgPG5vcnRoYmM+NzEuMzgyNjkxPC9ub3J0aGJjPg0KICAgICAgICA8c291 dGhiYz4tMTQuNTk5NDYzPC9zb3V0aGJjPg0KICAgICAgPC9ib3VuZGluZz4NCiAgICA8L3NwZG9t Pg0KICAgIDxrZXl3b3Jkcz4NCiAgICAgIDx0aGVtZT4NCiAgICAgICAgPHRoZW1la3Q+SVNPIDE5 MTE1IFRvcGljIENhdGVnb3JpZXM8L3RoZW1la3Q+DQogICAgICAgIDx0aGVtZWtleT5ib3VuZGFy aWVzPC90aGVtZWtleT4NCiAgICAgIDwvdGhlbWU+DQogICAgICA8cGxhY2U+DQogICAgICAgIDxw bGFjZWt0Pk5vbmU8L3BsYWNla3Q+DQogICAgICAgIDxwbGFjZWtleT5VU0E8L3BsYWNla2V5Pg0K ICAgICAgICA8cGxhY2VrZXk+VVM8L3BsYWNla2V5Pg0KICAgICAgICA8cGxhY2VrZXk+VW5pdGVk IFN0YXRlcyBvZiBBbWVyaWNhPC9wbGFjZWtleT4NCiAgICAgIDwvcGxhY2U+DQogICAgPC9rZXl3 b3Jkcz4NCiAgICA8YWNjY29uc3Q+SW50ZW5kZWQgZm9yIGludGVybmFsIEZvcmVzdCBTZXJ2aWNl IHVzZSBvciBmb3IgdXNlIGJ5IGFwcGxpY2F0aW9ucyB3aXRoIGEgbmVlZCB0byBkaXNwbGF5IHN0 YXRlIGJvdW5kYXJpZXMgdG8gZXh0ZXJuYWwgYXVkaWVuY2VzLjwvYWNjY29uc3Q+DQogICAgPHVz ZWNvbnN0PlRoZSBVU0RBIEZvcmVzdCBTZXJ2aWNlIG1ha2VzIG5vIHdhcnJhbnR5LCBleHByZXNz ZWQgb3IgaW1wbGllZCwgaW5jbHVkaW5nIHRoZSB3YXJyYW50aWVzIG9mIG1lcmNoYW50YWJpbGl0 eSBhbmQgZml0bmVzcyBmb3IgYSBwYXJ0aWN1bGFyIHB1cnBvc2UsIG5vciBhc3N1bWVzIGFueSBs ZWdhbCBsaWFiaWxpdHkgb3IgcmVzcG9uc2liaWxpdHkgZm9yIHRoZSBhY2N1cmFjeSwgcmVsaWFi aWxpdHksIGNvbXBsZXRlbmVzcyBvciB1dGlsaXR5IG9mIHRoZXNlIGdlb3NwYXRpYWwgZGF0YSwg b3IgZm9yIHRoZSBpbXByb3BlciBvciBpbmNvcnJlY3QgdXNlIG9mIHRoZXNlIGdlb3NwYXRpYWwg ZGF0YS4gIFRoZXNlIGdlb3NwYXRpYWwgZGF0YSBhbmQgcmVsYXRlZCBtYXBzIG9yIGdyYXBoaWNz IGFyZSBub3QgbGVnYWwgZG9jdW1lbnRzIGFuZCBhcmUgbm90IGludGVuZGVkIHRvIGJlIHVzZWQg YXMgc3VjaC4gIFRoZSBkYXRhIGFuZCBtYXBzIG1heSBub3QgYmUgdXNlZCB0byBkZXRlcm1pbmUg dGl0bGUsIG93bmVyc2hpcCwgbGVnYWwgZGVzY3JpcHRpb25zIG9yIGJvdW5kYXJpZXMsIGxlZ2Fs IGp1cmlzZGljdGlvbiwgb3IgcmVzdHJpY3Rpb25zIHRoYXQgbWF5IGJlIGluIHBsYWNlIG9uIGVp dGhlciBwdWJsaWMgb3IgcHJpdmF0ZSBsYW5kLiAgTmF0dXJhbCBoYXphcmRzIG1heSBvciBtYXkg bm90IGJlIGRlcGljdGVkIG9uIHRoZSBkYXRhIGFuZCBtYXBzLCBhbmQgbGFuZCB1c2VycyBzaG91 bGQgZXhlcmNpc2UgZHVlIGNhdXRpb24uICBUaGUgZGF0YSBhcmUgZHluYW1pYyBhbmQgbWF5IGNo YW5nZSBvdmVyIHRpbWUuICBUaGUgdXNlciBpcyByZXNwb25zaWJsZSB0byB2ZXJpZnkgdGhlIGxp bWl0YXRpb25zIG9mIHRoZSBnZW9zcGF0aWFsIGRhdGEgYW5kIHRvIHVzZSB0aGUgZGF0YSBhY2Nv cmRpbmdseS48L3VzZWNvbnN0Pg0KICAgIDxwdGNvbnRhYz4NCiAgICAgIDxjbnRpbmZvPg0KICAg ICAgICA8Y250b3JncD4NCiAgICAgICAgICA8Y250b3JnPlVTRlMgQ2hpZWYgSW5mb3JtYXRpb24g T2ZmaWNlLCBFbnRlcnByaXNlIERhdGEgV2FyZWhvdXNlPC9jbnRvcmc+DQogICAgICAgIDwvY250 b3JncD4NCiAgICAgICAgPGNudGFkZHI+DQogICAgICAgICAgPGFkZHJ0eXBlPnBoeXNpY2FsPC9h ZGRydHlwZT4NCiAgICAgICAgICA8Y2l0eT5XYXNoaW5ndG9uPC9jaXR5Pg0KICAgICAgICAgIDxz dGF0ZT5EQzwvc3RhdGU+DQogICAgICAgICAgPHBvc3RhbD4yMDI1MDwvcG9zdGFsPg0KICAgICAg ICA8L2NudGFkZHI+DQogICAgICAgIDxjbnR2b2ljZT5QbGVhc2Ugc2VuZCBhbiBlLW1haWwgdG8g dGhlIGFkZHJlc3MgYmVsb3cuPC9jbnR2b2ljZT4NCiAgICAgICAgPGNudGVtYWlsPmRhdGFAZnMu ZmVkLnVzPC9jbnRlbWFpbD4NCiAgICAgIDwvY250aW5mbz4NCiAgICA8L3B0Y29udGFjPg0KICAg IDxuYXRpdmU+TWljcm9zb2Z0IFdpbmRvd3MgU2VydmVyIDIwMDggUjIgVmVyc2lvbiA2LjEgKEJ1 aWxkIDc2MDEpIFNlcnZpY2UgUGFjayAxOyBFc3JpIEFyY0dJUyAxMC4yLjIuMzYwMjwvbmF0aXZl Pg0KICA8L2lkaW5mbz4NCiAgPGRhdGFxdWFsPg0KICAgIDxsb2dpYz5TcGF0aWFsIGRhdGEgd2Fz IHZpc3VhbGx5IGluc3BlY3RlZCB0byBlbnN1cmUgdGhhdCBubyBpbnZhbGlkIGdhcHMgb3IgcG9s eWdvbiBvdmVybGFwcyBleGlzdCB3aXRoaW4gdGhlIGRhdGFzZXQuIFRvcG9sb2dpY2FsIHRlc3Rz IHVzaW5nIEVzcmkgQXJjR0lTIHdlcmUgYWxzbyBkb25lIHRvIGVuc3VyZSB0aGUgc2FtZS4gRm9y IHN0YXRlcyB3aXRoIG11bHRpLXBvbHlnb24gZmVhdHVyZXMgb25seSBvbmUgYXR0cmlidXRlIHJl Y29yZCB3aWxsIGV4aXN0LiBUaGUgZW50aXJlIGNvYXN0bGluZSB3YXMgdmlzdWFsbHkgaW5zcGVj dGVkIHRvIHZlcmlmeSBhYnNlbmNlIG9mIHNsaXZlcnMsIGFuZCB0aG9zZSBmb3VuZCB3ZXJlIGRl bGV0ZWQuIEF0dHJpYnV0ZSBkYXRhIHdhcyBhbHNvIHZpc3VhbGx5IGluc3BlY3RlZCBmb3IgY29t cGxldGVuZXNzLiBTdGF0ZV9HZW4gYXR0cmlidXRlIHNjaGVtYSB3YXMgY2hlY2tlZCB0byBlbnN1 cmUgY29ycmVjdCBVUyBGb3Jlc3QgU2VydmljZSBzY2hlbWEgbmFtZXMsIGRhdGEgdHlwZXMsIGRh dGEgbGVuZ3RoLCBwcmVjaXNpb24sIGFuZCBzY2FsZSB3ZXJlIHVzZWQuPC9sb2dpYz4NCiAgICA8 Y29tcGxldGU+QWxsIGZlYXR1cmVzIGZyb20gdGhlIENlbnN1cyBCdXJlYXUgc3RhdGUgZGF0YXNl dCB3ZXJlIGluY2x1ZGVkIGluIHRoZSBTdGF0ZV9HZW4gZGF0YXNldC4gSG93ZXZlciwgZHVlIHRv IHRoZSBpbmNvcnBvcmF0aW9uIG9mIHRoZSBjb2FzdGxpbmUgYW5kIHRoZSBzdWJzZXF1ZW50IGdl bmVyYWxpemF0aW9uIG9mIHRoZSBwb2x5Z29ucywgdGhlIGFyZWEgb2Ygc29tZSBzdGF0ZXMgd2ls bCBiZSBzbWFsbGVyIHRoYW4gdGhlIG9yaWdpbmFsIENlbnN1cyBCdXJlYXUgc3RhdGUgZGF0YXNl dC4gVGhlIGZvbGxvd2luZyBDZW5zdXMgQnVyZWF1IFN0YXRlIGF0dHJpYnV0ZXM6IFJFR0lPTiwg RElWSVNJT04sIExTQUQsIE1URkNDLCBGVU5DU1RBVCwgQUxBTkQsIEFXQVRFUiwgSU5UUFRMQVQs IGFuZCBJTlRQVExPTiB0aGF0IGFyZSBub3QgcGFydCBvZiB0aGUgRm9yZXN0IFNlcnZpY2UgU3Rh dGUgc2NoZW1hIHdlcmUgZHJvcHBlZC48L2NvbXBsZXRlPg0KICAgIDxwb3NhY2M+DQogICAgICA8 aG9yaXpwYT4NCiAgICAgICAgPGhvcml6cGFyPkdlbmVyYWxpemVkIGRhdGEgd2l0aCBhIHRhcmdl dCBzY2FsZSBvZiAxOjc0MCwwMDAuIENvb3JkaW5hdGVzIGluIHRoZSBkYXRhIGhhdmUgc2l4IGlt cGxpZWQgZGVjaW1hbCBwbGFjZXMsIGJ1dCB0aGUgcG9zaXRpb25hbCBhY2N1cmFjeSBvZiB0aGVz ZSBjb29yZGluYXRlcyBpcyBub3QgYXMgZ3JlYXQgYXMgdGhlIHNpeCBkZWNpbWFsIHBsYWNlcyBz dWdnZXN0LjwvaG9yaXpwYXI+DQogICAgICA8L2hvcml6cGE+DQogICAgPC9wb3NhY2M+DQogICAg PGxpbmVhZ2U+DQogICAgICA8cHJvY3N0ZXA+DQogICAgICAgIDxwcm9jZGVzYz5UaGUgR2VuZXJh bGl6ZWQgU3RhdGUgZGF0YXNldCBpcyBjcmVhdGVkIHRocm91Z2ggYSBzaXggcGFydCBwcm9jZXNz LiAgRmlyc3QsIHRoZSBzdGF0ZSBkYXRhc2V0IGlzIGRvd25sb2FkZWQgZnJvbSB0aGUgQ2Vuc3Vz IEJ1cmVhdSBGVFAgc2l0ZSBhdCBmdHA6Ly9mdHAyLmNlbnN1cy5nb3YvZ2VvL3RpZ2VyL1RJR0VS MjAxNS8uIFNlY29uZCwgRXNyaSAnQWRkIGZpZWxkJyBhbmQgJ1BvcHVsYXRlIGZpZWxkJyB0b29s cyBhcmUgcnVuIGluIG9yZGVyIHRvIGNoYW5nZSBhdHRyaWJ1dGUgbmFtZXMgZnJvbSBDZW5zdXMg QnVyZWF1IGF0dHJpYnV0ZSBzY2hlbWEgdG8gdGhhdCBvZiBGb3Jlc3QgU2VydmljZS4gIFRoZW4s IGh5ZHJvZ3JhcGh5IGRhdGFzZXQgZm9yIGVhY2ggY291bnR5IGlzIGRvd25sb2FkZWQgZnJvbSBD ZW5zdXMgQnVyZWF1IEZUUCBzaXRlIGF0IGZ0cDovL2Z0cDIuY2Vuc3VzLmdvdi9nZW8vdGlnZXIv VElHRVIyMDE1L0FSRUFXQVRFUi8uIEFsbCBkYXRhc2V0cyBhcmUgbWVyZ2VkLCBhbmQgZmVhdHVy ZXMgdGhhdCB3aWxsIGZvcm0gdGhlIGNvYXN0bGluZSBhcmUgc2VsZWN0ZWQuICBGaW5hbGx5LCB0 aGUgZXJhc2VkIHN0YXRlIGRhdGFzZXQgaXMgZ2VuZXJhbGl6ZWQgdXNpbmcgRXNyaSdzICdTaW1w bGlmeSBQb2x5Z29uJyBweXRob24gZnVuY3Rpb24gd2l0aCBhIDM3NSBtZXRlcnMgc2ltcGxpZmlj YXRpb24gdG9sZXJhbmNlIHBhcmFtZXRlcjsgdGhlIHR3byBmaWVsZHMgYXV0b21hdGljYWxseSBn ZW5lcmF0ZWQgYnkgdGhlICdTaW1wbGlmeSBQb2x5Z29uJyB0b29sIGFyZSBkcm9wcGVkLjwvcHJv Y2Rlc2M+DQogICAgICAgIDxwcm9jZGF0ZT4yMDE2PC9wcm9jZGF0ZT4NCiAgICAgIDwvcHJvY3N0 ZXA+DQogICAgPC9saW5lYWdlPg0KICA8L2RhdGFxdWFsPg0KICA8c3Bkb2luZm8+DQogICAgPGRp cmVjdD5WZWN0b3I8L2RpcmVjdD4NCiAgICA8cHR2Y3RpbmY+DQogICAgICA8c2R0c3Rlcm0+DQog ICAgICAgIDxzZHRzdHlwZT5HVC1wb2x5Z29uIGNvbXBvc2VkIG9mIGNoYWluczwvc2R0c3R5cGU+ DQogICAgICAgIDxwdHZjdGNudD41NjwvcHR2Y3RjbnQ+DQogICAgICA8L3NkdHN0ZXJtPg0KICAg IDwvcHR2Y3RpbmY+DQogIDwvc3Bkb2luZm8+DQogIDxzcHJlZj4NCiAgICA8aG9yaXpzeXM+DQog ICAgICA8Z2VvZ3JhcGg+DQogICAgICAgIDxsYXRyZXM+OC45ODMxNTI4NDExOTUyMWUtMDA5PC9s YXRyZXM+DQogICAgICAgIDxsb25ncmVzPjguOTgzMTUyODQxMTk1MjFlLTAwOTwvbG9uZ3Jlcz4N CiAgICAgICAgPGdlb2d1bml0PkRlY2ltYWwgRGVncmVlczwvZ2VvZ3VuaXQ+DQogICAgICA8L2dl b2dyYXBoPg0KICAgICAgPGdlb2RldGljPg0KICAgICAgICA8aG9yaXpkbj5EIE5vcnRoIEFtZXJp Y2FuIDE5ODM8L2hvcml6ZG4+DQogICAgICAgIDxlbGxpcHM+R1JTIDE5ODA8L2VsbGlwcz4NCiAg ICAgICAgPHNlbWlheGlzPjYzNzgxMzcuMDwvc2VtaWF4aXM+DQogICAgICAgIDxkZW5mbGF0PjI5 OC4yNTcyMjIxMDE8L2RlbmZsYXQ+DQogICAgICA8L2dlb2RldGljPg0KICAgIDwvaG9yaXpzeXM+ DQogIDwvc3ByZWY+DQogIDxlYWluZm8+DQogICAgPGRldGFpbGVkPg0KICAgICAgPGVudHR5cD4N CiAgICAgICAgPGVudHR5cGw+U19VU0EuU3RhdGVfR2VuPC9lbnR0eXBsPg0KICAgICAgICA8ZW50 dHlwZD5BIGNvbGxlY3Rpb24gb2YgZ2VvZ3JhcGhpYyBmZWF0dXJlcyB3aXRoIHRoZSBzYW1lIGdl b21ldHJ5IHR5cGUgKHN1Y2ggYXMgcG9pbnQsIGxpbmUsIG9yIHBvbHlnb24pLCB0aGUgc2FtZSBh dHRyaWJ1dGVzLCBhbmQgdGhlIHNhbWUgc3BhdGlhbCByZWZlcmVuY2UuPC9lbnR0eXBkPg0KICAg ICAgICA8ZW50dHlwZHM+aHR0cDovL3N1cHBvcnQuZXNyaS5jb20vZW4va25vd2xlZGdlYmFzZS9H SVNEaWN0aW9uYXJ5L3Rlcm0vZmVhdHVyZSUyMGNsYXNzPC9lbnR0eXBkcz4NCiAgICAgIDwvZW50 dHlwPg0KICAgICAgPGF0dHI+DQogICAgICAgIDxhdHRybGFibD5PQkpFQ1RJRDwvYXR0cmxhYmw+ DQogICAgICAgIDxhdHRyZGVmPkludGVybmFsIGZlYXR1cmUgbnVtYmVyLjwvYXR0cmRlZj4NCiAg ICAgICAgPGF0dHJkZWZzPkVTUkk8L2F0dHJkZWZzPg0KICAgICAgICA8YXR0cnR5cGUgU3luYz0i VFJVRSI+T2JqZWN0IElEPC9hdHRydHlwZT4NCiAgICAgICAgPGF0dHdpZHRoIFN5bmM9IlRSVUUi PjQ8L2F0dHdpZHRoPg0KICAgICAgICA8YXRwcmVjaXMgU3luYz0iVFJVRSI+MTA8L2F0cHJlY2lz Pg0KICAgICAgICA8YXR0c2NhbGUgU3luYz0iVFJVRSI+MDwvYXR0c2NhbGU+DQogICAgICAgIDxh dHRyZG9tdj4NCiAgICAgICAgICA8dWRvbT5TZXF1ZW50aWFsIHVuaXF1ZSB3aG9sZSBudW1iZXJz IHRoYXQgYXJlIGF1dG9tYXRpY2FsbHkgZ2VuZXJhdGVkLjwvdWRvbT4NCiAgICAgICAgPC9hdHRy ZG9tdj4NCiAgICAgIDwvYXR0cj4NCiAgICAgIDxhdHRyPg0KICAgICAgICA8YXR0cmxhYmw+U1RB VEVDT0RFPC9hdHRybGFibD4NCiAgICAgICAgPGF0dHJkZWY+MjAxMCBDZW5zdXMgc3RhdGUgRmVk ZXJhbCBJbmZvcm1hdGlvbiBQcm9jZXNzaW5nIFN0YW5kYXJkcyAoRklQUykgY29kZS48L2F0dHJk ZWY+DQogICAgICAgIDxhdHRyZGVmcz5BTlNJPC9hdHRyZGVmcz4NCiAgICAgICAgPGF0dHJ0eXBl IFN5bmM9IlRSVUUiPlRleHQ8L2F0dHJ0eXBlPg0KICAgICAgICA8YXR0d2lkdGggU3luYz0iVFJV RSI+MjwvYXR0d2lkdGg+DQogICAgICAgIDxhdHByZWNpcyBTeW5jPSJUUlVFIj4wPC9hdHByZWNp cz4NCiAgICAgICAgPGF0dHNjYWxlIFN5bmM9IlRSVUUiPjA8L2F0dHNjYWxlPg0KICAgICAgICA8 YXR0cmRvbXY+DQogICAgICAgICAgPGNvZGVzZXRkPg0KICAgICAgICAgICAgPGNvZGVzZXRuPkxp c3Qgb2YgVS5TLiBTdGF0ZSBDb2RlczwvY29kZXNldG4+DQogICAgICAgICAgICA8Y29kZXNldHM+ aHR0cDovL3d3dy5jZW5zdXMuZ292L2dlby9yZWZlcmVuY2UvYW5zaV9zdGF0ZXRhYmxlcy5odG1s PC9jb2Rlc2V0cz4NCiAgICAgICAgICA8L2NvZGVzZXRkPg0KICAgICAgICA8L2F0dHJkb212Pg0K ICAgICAgPC9hdHRyPg0KICAgICAgPGF0dHI+DQogICAgICAgIDxhdHRybGFibD5HTklTX0lEPC9h dHRybGFibD4NCiAgICAgICAgPGF0dHJkZWY+VGhlIEdlb2dyYXBoaWMgTmFtZXMgSW5mb3JtYXRp b24gU3lzdGVtcyAoR05JUykgY29kZSBmb3IgdGhpcyBzdGF0ZS48L2F0dHJkZWY+DQogICAgICAg IDxhdHRyZGVmcz5HZW9ncmFwaGljIE5hbWVzIEluZm9ybWF0aW9uIFN5c3RlbTwvYXR0cmRlZnM+ DQogICAgICAgIDxhdHRydHlwZSBTeW5jPSJUUlVFIj5UZXh0PC9hdHRydHlwZT4NCiAgICAgICAg PGF0dHdpZHRoIFN5bmM9IlRSVUUiPjg8L2F0dHdpZHRoPg0KICAgICAgICA8YXRwcmVjaXMgU3lu Yz0iVFJVRSI+MDwvYXRwcmVjaXM+DQogICAgICAgIDxhdHRzY2FsZSBTeW5jPSJUUlVFIj4wPC9h dHRzY2FsZT4NCiAgICAgICAgPGF0dHJkb212Pg0KICAgICAgICAgIDxjb2Rlc2V0ZD4NCiAgICAg ICAgICAgIDxjb2Rlc2V0bj5MaXN0IG9mIEdlb2dyYXBoaWMgTmFtZXMgSW5mb3JtYXRpb24gU3lz dGVtIENvZGVzPC9jb2Rlc2V0bj4NCiAgICAgICAgICAgIDxjb2Rlc2V0cz5odHRwOi8vZ2VvbmFt ZXMudXNncy5nb3YvPC9jb2Rlc2V0cz4NCiAgICAgICAgICA8L2NvZGVzZXRkPg0KICAgICAgICA8 L2F0dHJkb212Pg0KICAgICAgPC9hdHRyPg0KICAgICAgPGF0dHI+DQogICAgICAgIDxhdHRybGFi bD5TVEFURV9QT1NUQUxfQUJCUjwvYXR0cmxhYmw+DQogICAgICAgIDxhdHRyZGVmPlVuaXRlZCBT dGF0ZXMgUG9zdGFsIFNlcnZpY2Ugc3RhdGUgYWJicmV2aWF0aW9uPC9hdHRyZGVmPg0KICAgICAg ICA8YXR0cmRlZnM+VVMgUG9zdGFsIFNlcnZpY2U8L2F0dHJkZWZzPg0KICAgICAgICA8YXR0cnR5 cGUgU3luYz0iVFJVRSI+VGV4dDwvYXR0cnR5cGU+DQogICAgICAgIDxhdHR3aWR0aCBTeW5jPSJU UlVFIj4yPC9hdHR3aWR0aD4NCiAgICAgICAgPGF0cHJlY2lzIFN5bmM9IlRSVUUiPjA8L2F0cHJl Y2lzPg0KICAgICAgICA8YXR0c2NhbGUgU3luYz0iVFJVRSI+MDwvYXR0c2NhbGU+DQogICAgICAg IDxhdHRyZG9tdj4NCiAgICAgICAgICA8Y29kZXNldGQ+DQogICAgICAgICAgICA8Y29kZXNldG4+ TGlzdCBvZiBVLlMuIFN0YXRlIEFiYnJldmlhdGlvbnM8L2NvZGVzZXRuPg0KICAgICAgICAgICAg PGNvZGVzZXRzPmh0dHA6Ly9wZS51c3BzLmdvdi90ZXh0L3B1YjI4LzI4YXBiLmh0bTwvY29kZXNl dHM+DQogICAgICAgICAgPC9jb2Rlc2V0ZD4NCiAgICAgICAgPC9hdHRyZG9tdj4NCiAgICAgIDwv YXR0cj4NCiAgICAgIDxhdHRyPg0KICAgICAgICA8YXR0cmxhYmw+U1RBVEVOQU1FPC9hdHRybGFi bD4NCiAgICAgICAgPGF0dHJkZWY+MjAxMCBDZW5zdXMgc3RhdGUgbmFtZTwvYXR0cmRlZj4NCiAg ICAgICAgPGF0dHJkZWZzPlVTIENlbnN1czwvYXR0cmRlZnM+DQogICAgICAgIDxhdHRydHlwZSBT eW5jPSJUUlVFIj5UZXh0PC9hdHRydHlwZT4NCiAgICAgICAgPGF0dHdpZHRoIFN5bmM9IlRSVUUi PjEwMDwvYXR0d2lkdGg+DQogICAgICAgIDxhdHByZWNpcyBTeW5jPSJUUlVFIj4wPC9hdHByZWNp cz4NCiAgICAgICAgPGF0dHNjYWxlIFN5bmM9IlRSVUUiPjA8L2F0dHNjYWxlPg0KICAgICAgICA8 YXR0cmRvbXY+DQogICAgICAgICAgPGNvZGVzZXRkPg0KICAgICAgICAgICAgPGNvZGVzZXRuPkxp c3Qgb2YgVS5TLiBTdGF0ZSBOYW1lczwvY29kZXNldG4+DQogICAgICAgICAgICA8Y29kZXNldHM+ aHR0cDovL3d3dy5jZW5zdXMuZ292L2dlby9yZWZlcmVuY2UvYW5zaV9zdGF0ZXRhYmxlcy5odG1s PC9jb2Rlc2V0cz4NCiAgICAgICAgICA8L2NvZGVzZXRkPg0KICAgICAgICA8L2F0dHJkb212Pg0K ICAgICAgPC9hdHRyPg0KICAgICAgPGF0dHI+DQogICAgICAgIDxhdHRybGFibD5HSVNfQUNSRVM8 L2F0dHJsYWJsPg0KICAgICAgICA8YXR0cmRlZj5UaGUgYXJlYSBvZiB0aGUgZmVhdHVyZSBpbiBh Y3JlcywgY2FsY3VsYXRlZCBpbiBOb3J0aCBBbWVyaWNhbiBBbGJlcnMgRXF1YWwgQXJlYSBDb25p YyBwcm9qZWN0aW9uLCBOb3J0aCBBbWVyaWNhbiBEYXR1bSAxOTgzIChOQUQ4MykuPC9hdHRyZGVm Pg0KICAgICAgICA8YXR0cmRlZnM+VVMgRm9yZXN0IFNlcnZpY2U8L2F0dHJkZWZzPg0KICAgICAg ICA8YXR0cnR5cGUgU3luYz0iVFJVRSI+RG91YmxlPC9hdHRydHlwZT4NCiAgICAgICAgPGF0dHdp ZHRoIFN5bmM9IlRSVUUiPjg8L2F0dHdpZHRoPg0KICAgICAgICA8YXRwcmVjaXMgU3luYz0iVFJV RSI+Mzg8L2F0cHJlY2lzPg0KICAgICAgICA8YXR0c2NhbGUgU3luYz0iVFJVRSI+ODwvYXR0c2Nh bGU+DQogICAgICAgIDxhdHRyZG9tdj4NCiAgICAgICAgICA8dWRvbT5Qb3NpdGl2ZSBudW1iZXJz PC91ZG9tPg0KICAgICAgICA8L2F0dHJkb212Pg0KICAgICAgPC9hdHRyPg0KICAgICAgPGF0dHI+ DQogICAgICAgIDxhdHRybGFibD5TSEFQRTwvYXR0cmxhYmw+DQogICAgICAgIDxhdHRyZGVmPkZl YXR1cmUgZ2VvbWV0cnkuPC9hdHRyZGVmPg0KICAgICAgICA8YXR0cmRlZnM+RVNSSTwvYXR0cmRl ZnM+DQogICAgICAgIDxhdHRydHlwZSBTeW5jPSJUUlVFIj5HZW9tZXRyeTwvYXR0cnR5cGU+DQog ICAgICAgIDxhdHR3aWR0aCBTeW5jPSJUUlVFIj40PC9hdHR3aWR0aD4NCiAgICAgICAgPGF0cHJl Y2lzIFN5bmM9IlRSVUUiPjA8L2F0cHJlY2lzPg0KICAgICAgICA8YXR0c2NhbGUgU3luYz0iVFJV RSI+MDwvYXR0c2NhbGU+DQogICAgICAgIDxhdHRyZG9tdj4NCiAgICAgICAgICA8dWRvbT5Db29y ZGluYXRlcyBkZWZpbmluZyB0aGUgZmVhdHVyZXMuPC91ZG9tPg0KICAgICAgICA8L2F0dHJkb212 Pg0KICAgICAgPC9hdHRyPg0KICAgICAgPGF0dHI+DQogICAgICAgIDxhdHRybGFibD5TSEFQRS5B UkVBPC9hdHRybGFibD4NCiAgICAgICAgPGF0dHJkZWY+Tm90IFVzZWQsIFNETyBHZW9tZXRyeS4g QXJlYSBvZiBmZWF0dXJlIGluIGludGVybmFsIHVuaXRzIHNxdWFyZWQuPC9hdHRyZGVmPg0KICAg ICAgICA8YXR0cmRlZnM+RVNSSTwvYXR0cmRlZnM+DQogICAgICAgIDxhdHRydHlwZSBTeW5jPSJU UlVFIj5Eb3VibGU8L2F0dHJ0eXBlPg0KICAgICAgICA8YXR0d2lkdGggU3luYz0iVFJVRSI+MDwv YXR0d2lkdGg+DQogICAgICAgIDxhdHByZWNpcyBTeW5jPSJUUlVFIj4wPC9hdHByZWNpcz4NCiAg ICAgICAgPGF0dHNjYWxlIFN5bmM9IlRSVUUiPjA8L2F0dHNjYWxlPg0KICAgICAgICA8YXR0cmRv bXY+DQogICAgICAgICAgPHVkb20+UG9zaXRpdmUgcmVhbCBudW1iZXJzIHRoYXQgYXJlIGF1dG9t YXRpY2FsbHkgZ2VuZXJhdGVkLjwvdWRvbT4NCiAgICAgICAgPC9hdHRyZG9tdj4NCiAgICAgIDwv YXR0cj4NCiAgICAgIDxhdHRyPg0KICAgICAgICA8YXR0cmxhYmw+U0hBUEUuTEVOPC9hdHRybGFi bD4NCiAgICAgICAgPGF0dHJkZWY+Tm90IHVzZWQsIFNETyBnZW9tZXRyeS4gTGVuZ3RoIG9mIGZl YXR1cmUgaW4gaW50ZXJuYWwgdW5pdHMuPC9hdHRyZGVmPg0KICAgICAgICA8YXR0cmRlZnM+RVNS STwvYXR0cmRlZnM+DQogICAgICAgIDxhdHRydHlwZSBTeW5jPSJUUlVFIj5Eb3VibGU8L2F0dHJ0 eXBlPg0KICAgICAgICA8YXR0d2lkdGggU3luYz0iVFJVRSI+MDwvYXR0d2lkdGg+DQogICAgICAg IDxhdHByZWNpcyBTeW5jPSJUUlVFIj4wPC9hdHByZWNpcz4NCiAgICAgICAgPGF0dHNjYWxlIFN5 bmM9IlRSVUUiPjA8L2F0dHNjYWxlPg0KICAgICAgICA8YXR0cmRvbXY+DQogICAgICAgICAgPHVk b20+UG9zaXRpdmUgcmVhbCBudW1iZXJzIHRoYXQgYXJlIGF1dG9tYXRpY2FsbHkgZ2VuZXJhdGVk LjwvdWRvbT4NCiAgICAgICAgPC9hdHRyZG9tdj4NCiAgICAgIDwvYXR0cj4NCiAgICA8L2RldGFp bGVkPg0KICA8L2VhaW5mbz4NCiAgPGRpc3RpbmZvPg0KICAgIDxkaXN0cmliPg0KICAgICAgPGNu dGluZm8+DQogICAgICAgIDxjbnRvcmdwPg0KICAgICAgICAgIDxjbnRvcmc+VVNGUyBDaGllZiBJ bmZvcm1hdGlvbiBPZmZpY2UsIEVudGVycHJpc2UgRGF0YSBXYXJlaG91c2U8L2NudG9yZz4NCiAg ICAgICAgPC9jbnRvcmdwPg0KICAgICAgICA8Y250YWRkcj4NCiAgICAgICAgICA8YWRkcnR5cGU+ cGh5c2ljYWw8L2FkZHJ0eXBlPg0KICAgICAgICAgIDxjaXR5Pldhc2hpbmd0b248L2NpdHk+DQog ICAgICAgICAgPHN0YXRlPkRDPC9zdGF0ZT4NCiAgICAgICAgICA8cG9zdGFsPjIwMjUwPC9wb3N0 YWw+DQogICAgICAgIDwvY250YWRkcj4NCiAgICAgICAgPGNudHZvaWNlPlBsZWFzZSBzZW5kIGFu IGUtbWFpbCB0byB0aGUgYWRkcmVzcyBiZWxvdy48L2NudHZvaWNlPg0KICAgICAgICA8Y250ZW1h aWw+ZGF0YUBmcy5mZWQudXM8L2NudGVtYWlsPg0KICAgICAgPC9jbnRpbmZvPg0KICAgIDwvZGlz dHJpYj4NCiAgICA8ZGlzdGxpYWI+VGhlIFVTREEgRm9yZXN0IFNlcnZpY2UgbWFrZXMgbm8gd2Fy cmFudHksIGV4cHJlc3NlZCBvciBpbXBsaWVkLCBpbmNsdWRpbmcgdGhlIHdhcnJhbnRpZXMgb2Yg bWVyY2hhbnRhYmlsaXR5IGFuZCBmaXRuZXNzIGZvciBhIHBhcnRpY3VsYXIgcHVycG9zZSwgbm9y IGFzc3VtZXMgYW55IGxlZ2FsIGxpYWJpbGl0eSBvciByZXNwb25zaWJpbGl0eSBmb3IgdGhlIGFj Y3VyYWN5LCByZWxpYWJpbGl0eSwgY29tcGxldGVuZXNzIG9yIHV0aWxpdHkgb2YgdGhlc2UgZ2Vv c3BhdGlhbCBkYXRhLCBvciBmb3IgdGhlIGltcHJvcGVyIG9yIGluY29ycmVjdCB1c2Ugb2YgdGhl c2UgZ2Vvc3BhdGlhbCBkYXRhLiAgVGhlc2UgZ2Vvc3BhdGlhbCBkYXRhIGFuZCByZWxhdGVkIG1h cHMgb3IgZ3JhcGhpY3MgYXJlIG5vdCBsZWdhbCBkb2N1bWVudHMgYW5kIGFyZSBub3QgaW50ZW5k ZWQgdG8gYmUgdXNlZCBhcyBzdWNoLiAgVGhlIGRhdGEgYW5kIG1hcHMgbWF5IG5vdCBiZSB1c2Vk IHRvIGRldGVybWluZSB0aXRsZSwgb3duZXJzaGlwLCBsZWdhbCBkZXNjcmlwdGlvbnMgb3IgYm91 bmRhcmllcywgbGVnYWwganVyaXNkaWN0aW9uLCBvciByZXN0cmljdGlvbnMgdGhhdCBtYXkgYmUg aW4gcGxhY2Ugb24gZWl0aGVyIHB1YmxpYyBvciBwcml2YXRlIGxhbmQuICBOYXR1cmFsIGhhemFy ZHMgbWF5IG9yIG1heSBub3QgYmUgZGVwaWN0ZWQgb24gdGhlIGRhdGEgYW5kIG1hcHMsIGFuZCBs YW5kIHVzZXJzIHNob3VsZCBleGVyY2lzZSBkdWUgY2F1dGlvbi4gICBUaGUgZGF0YSBhcmUgZHlu YW1pYyBhbmQgbWF5IGNoYW5nZSBvdmVyIHRpbWUuICBUaGUgdXNlciBpcyByZXNwb25zaWJsZSB0 byB2ZXJpZnkgdGhlIGxpbWl0YXRpb25zIG9mIHRoZSBnZW9zcGF0aWFsIGRhdGEgYW5kIHRvIHVz ZSB0aGUgZGF0YSBhY2NvcmRpbmdseS48L2Rpc3RsaWFiPg0KICA8L2Rpc3RpbmZvPg0KICA8bWV0 YWluZm8+DQogICAgPG1ldGQ+MjAxNzAxMTA8L21ldGQ+DQogICAgPG1ldGM+DQogICAgICA8Y250 aW5mbz4NCiAgICAgICAgPGNudG9yZ3A+DQogICAgICAgICAgPGNudG9yZz5VU0ZTIENoaWVmIElu Zm9ybWF0aW9uIE9mZmljZSwgRW50ZXJwcmlzZSBEYXRhIFdhcmVob3VzZTwvY250b3JnPg0KICAg ICAgICA8L2NudG9yZ3A+DQogICAgICAgIDxjbnRhZGRyPg0KICAgICAgICAgIDxhZGRydHlwZT5w aHlzaWNhbDwvYWRkcnR5cGU+DQogICAgICAgICAgPGNpdHk+V2FzaGluZ3RvbjwvY2l0eT4NCiAg ICAgICAgICA8c3RhdGU+REM8L3N0YXRlPg0KICAgICAgICAgIDxwb3N0YWw+MjAyNTA8L3Bvc3Rh bD4NCiAgICAgICAgPC9jbnRhZGRyPg0KICAgICAgICA8Y250dm9pY2U+UGxlYXNlIHNlbmQgYW4g ZS1tYWlsIHRvIHRoZSBhZGRyZXNzIGJlbG93LjwvY250dm9pY2U+DQogICAgICAgIDxjbnRlbWFp bD5kYXRhQGZzLmZlZC51czwvY250ZW1haWw+DQogICAgICA8L2NudGluZm8+DQogICAgPC9tZXRj Pg0KICAgIDxtZXRzdGRuPkZHREMgQ29udGVudCBTdGFuZGFyZCBmb3IgRGlnaXRhbCBHZW9zcGF0 aWFsIE1ldGFkYXRhPC9tZXRzdGRuPg0KICAgIDxtZXRzdGR2PkZHREMtU1RELTAwMS0xOTk4PC9t ZXRzdGR2Pg0KICAgIDxtZXR0Yz5sb2NhbCB0aW1lPC9tZXR0Yz4NCiAgPC9tZXRhaW5mbz4NCjwv bWV0YWRhdGE+ dataset EPSG 6.5(3.0.1)