20210908 11321700 1.0 TRUE 150000000 5000 FGDC Census_2020 external 2dc5ba2f84d3ca1867d444710bb079a75059294c U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch 4600 Silver Hill Road, Stop 7400 Washington DC 20233-7400 geo.geography@census.gov US 301-763-1128 301-763-4710 True U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch external c903851b22bd04ebc729b9624c0bfd3c55752737 Delaware Division of Technology and Information - FirstMap 302-739-9560 801 Silver Lake Blvd Dover DE 19904 US DTI_GIS@delaware.gov Delaware Division of Technology and Information - FirstMap Delaware Division of Technology and Information - FirstMap True Delaware Division of Technology and Information - FirstMap In order for others to use the information in the Census MAF/TIGER database in a geographic information system (GIS) or for other geographic applications, the Census Bureau releases to the public extracts of the database in the form of TIGER/Line Shapefiles. <DIV STYLE="text-align:Left;">Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Block Groups (BGs) are clusters of blocks within the same census tract. Each census tract contains at least one BG, and BGs are uniquely numbered within census tracts. BGs have a valid code range of 0 through 9. BGs have the same first digit of their 4-digit census block number from the same decennial census. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. </DIV> The TIGER/Line Shapefile products are not copyrighted however TIGER/Line and Census TIGER are registered trademarks of the U.S. Census Bureau. These products are free to use in a product or publication, however acknowledgement must be given to the U.S. Census Bureau as the source.The boundaries in the TIGER/Line Shapefiles are for statistical data collection and tabulation purposes only, their depiction and designation for statistical purposes does not constitute a determination of jurisdictional authority or rights of ownership or entitlement and they are not legal land descriptions. Coordinates in the TIGER/Line shapefiles have six implied decimal places, but the positional accuracy of these coordinates is not as great as the six decimal places suggest. Census Tracts BlockGroups Blocks Delaware FirstMap 2020 Urban Area 20210908 /9j/4AAQSkZJRgABAQEAAAAAAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCADIASwDAREA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD3+gAo AKACgAoAKACgAoAKACgAoAr3y7rSQFioxyQcUAcvZGxa9illLB2Vx5s3TC/jQBGXkXUDFCBcI5YB AOB6E/rQA2PSWgmm+0Rz7CAsWFA3MRjnnpmgCO5srWz0yJblkSZ2J+VcuAPQ/wBKANKzHlhYI28w s4MgC/eOMj8e/wCFAGsiyQtHGzB/m3OQMc5zQBohVBJAGT1oAjltoZipkjVipyM9jQBLigCo9o5y Fk+UnOD2oAaVW3VYwxZkOfoO9AEhutzYiXcAMlicAUAJDeCSZo228YxtOaAJLpgtu+T26etAEHnG KHdjEhPO7uKAJYNzyGUMoQjG1ecn1zQBYoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAo ARXVxlWBHsaAFoAq3hcoI1C4cEEn6UAcfeJFAnnT28cxfeFPysASMDcPXigCRttvLGplmd/LJLgE EEEEA55PfrQBY/ti7eW3vLqODy87YlUk4Y8Zb09PY0AV5Y5L6+ZpVJYHdJHEGyD2O7pjjpmgDoIk 3SRlWV2DbjJ2d8H9MZoAuR2ManfJl5Cckk5GaALVABQAUAFADdqhiwUbj1OOTQBnJII0kbDeYW+4 wyWH0/rQAPbj7UQTIsfXKnAoAlLBZkilbBj+YOx6igC7ww7EGgAACjAAA9BQAtABQAUAFABQAUAF ABQAUAFABQAUAFABQAUAFABQAUAQyvu/dxsNx6+woArXBazIMC7i4wee470AIt7KsTbon3YyNw5+ lAEluA0AnmlJzk89FzQBjLs+zwOwncfaB8qxjaRuNABNa209wZI4THEz+XIZMghhyMc/WgCtpxij kuB5dw6KzsP3edzcn8sUAaDoseloLUsGlO91X7zCgC/LboIEktgSFIKqvp7UAXgcgHBGexoAWgAo AKACgBryJGhZ2CqO5oAoXpSV4JInTcuWBPfpxQBP5Lyyo7hdu35sdzQA6aygnkEkiknGOtADoI3i 3ITlAflPf6UATUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAUZ4wXMMIPmZ3cngc0AE Fu321pXB+VcD60AXSAQQe9AEK2qhNm99vTGaAMJYVjsbht+fLDPHH0AYE/8A1qAJvMlbUvsvlrJb upmkKHOGGOD9c5/CgBbK7t0urm38wqEcklQT975scfWgCSX7NHNDNBE8gRucDAGe/NAE80jQX6RW q7mcFnTPyj3+tAFiCeR5trA9OcrjFAFqgAoAKACgAIBGD0oArvZW7B8RKGYYJA5oASzWVA6SKcKR tJOc+tAFmgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAGeWnm+Zj58Yz7UAPoAK ACgDIh0y3uJbrzgz/vMAbiMDA9PrQBXWCytYZLdi8bRf8tCzYYe59aAJ9KkhiublF2Eu64MYyD8o 9KALOqTeXBGi4MruAiH+I+lAC2YX7ZdMMbjtzznBxzQBeoAKACgAoAKACgAoAKACgAoAKACgAoAK ACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgDJe9Fqb/AIk8z93kcMdo4oAqWmo+VHP HqCgF5mXfjgn0xQBXtL5EvLnFvKqAKyYXnhQD9KAL83724Hm4ZSsZP0JbP8ASgDVgtobZSsMYQE5 OKAJaACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKA CgAoAx7mYwy3UceTOXEiLg4JwB/SgCnY6bNJdTNcTosjN5qYjBOT15PPFAFmKB7OYSCUsk7lZt/O ccZ/TGKAFt7Jrv8A0hWVIzny15Jx3Bz0+lAF20uWDGCbIdeATQBdoAKACgAoAKACgAoAKACgAoAK ACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgCg8jR6o4SFpCYlPHbk96AI52 uSNsluPMA3pIhwE9QT/nNAEEYl1VMFRDEAN5/iLeoHYd6ANOztVs7cQozMAc5Y80AU9QkSCdTjd5 o2sB2PZvbHT8aALVrM5URzEeaB1HRh6igCzQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFA BQAUAFABQAUAFABQAUAFABQAUAFABQAUAUnkWHUJZH4UQL/M0AK5nuwEEJjiJ+YucN+AoAdPi2kW 4H3eEce3Y0AMvn862MEEmJJflDK3K+9AEVnbJZyG2dS7MvErHJYe9AD5Ymt1GSWiXkMB80f+IoAs W8/mDY+BIByPX3FAE9ABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFAB QAUAFABQAUAFAGdfWzT39ttmaPqThQc45HWgCcwXSjK3ZYjsyAA/kKAMCbUjduY7t/KUOyFVzt4z +ecdKAL3h9IkWdAFMiPw2ckqelAGif8AkKJ7Qt/MUAWWUMpU9DxQBSij3RiLO2eHo3qP8KALMM3m Aqw2yL95aAJaACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKA CgAoAqzf8f8Aa/R/5CgC1QBkanDFHcRyvHGI2PJboG9fy4oAoQ3cv/CQPHEgt0lhVVkdPlZlJyBz 7igDVSOWDU42kmMiOhRcjkHIP9DQBo0AVJONTgx3jfPvyKAJLiJiPNj4kTke49KAJIpBLErr0NAD 6ACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgCjftJHPay xru2sQR6g0APF1KPne3ZY/rkj6igCve3AuYjHbwPOwIyyYGzP1PXFAGVcyXL30cHlBUHLF23EL6k dPyoAtm8MS+TO25oyCjqcsD2+v1oA07aeUlUuUVZGGV2nII/xoALj5rmBU++rZPsvf8ApQBaoAqj /RrrH/LKU8ezf/XoAtUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUA FABQAUAFAFW94EB/6bKP1oAtUAZxt3XUJQkzQiUBhtUckDHcUAUdQ06a2tJ5xfSEKu7lVyPxxQBS t1KX080O6RYohtL4y69Pw9fwoAvQ39zPeW8cts0SceXK38Xc89OlAGpF/wAhK5/3E/rQBaoAjmiE 0TIeM9COooAbbSmSLD8SKdrD3oAmoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACg AoAKACgAoAKACgAoAqag4jiidjhVmQk/jQAvmXM/3EESH+Jj835UAV5rTbeW/wDpE+W3DO7noT6U AZupyCK7MUzXE1uq5ZCchz6fy/OgCtp6x3scbPDJapMpcNv5XJzs9v8A61AFvSyWv/sjMWEBL57Y PSgDYb5NTjx/y0jbd+GMfzNAFqgAoAqzZgnE4+43yyf0P+fWgC1QAUAFABQAUAFABQAUAFABQAUA FABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQBV1AhbJ3Jxs+bP0oAnjkSRAyMrD1BzQBVuXZb yNmjYxxgkFRnJIxQBQ1a/tbjTmZCzPtJTgg8e3WgCneNN5iska/Y7iTOCQdx69u3FAF7T3mXVpA6 Da0QxtwAuDQBpzxOZEmjxvQEYPcHr/KgB8UyyrkcEcFT1BoAkoARlDqVYZB60AV7djHI9uxzt5Qn uv8AnigCzQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFAFXUhn TbkH/nmaAFNlbuFbZtOP4SR/KgBptZ0+aO6kYjor4x/KgClbWsstuhIjJ2suSPuHNADl0+FbxFuA GXrEASFB7igCSG1Wx1JpAx8qZdoB/hOc4oA0qAK1yDFIlwo6HDgdxQBZBBAI6GgBrusalnYKo6k0 AUJ7ndJHPDGzqh+d8YXb357460AaAIIBHQ0ALQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUA FABQAUAFABQAUAFABQAUAQXqF7GdB1KEUAV4jeMkc+UYFeYgePrnuaAJG1CKNSZ1khwM/Ov+GaAK 9rcPG05FvMwkkLqeMYwPf2oAaz/bbWS4kYxrEx2KOxHrQBJeThtNwzATmHzFJ7NjOfzoAjt7+W4S I24WR3QMwZsBKAFnvpvstwkllMGVDnbgg8dRzQBLby3M9vF5aCJNg+Z+T09P/r0ATrZx7g8pMrjo W7fSgCdkVkKEAqRgigCvaMQrQucvGcc9x2NAFmgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAo AKACgAoAKACgAoAKACgAoARhuUj1FAFewO6whP8As0APupkggLSDKnjB754oAyrlJbaCHDfvXGFI 5x7D160ATJp4TQzE+5W2mRuf4upoAz7qa6dbaJoIlR1RAz8kqeDmgCbRNq3U026JknO2Pyl4G3/9 dAG66h0ZT0YYNAENu5T/AEd+GX7p/vCgCxQAUAVZx5NzHOOjfI/9D+HNAFqgAoAKACgAoAKACgAo AKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAD0oAq6d/yD4P92gCyVDDDAEehoAz/ALJb xalAY4wCqsTye+MUAEkyXl8lthvKUF2bsxBxj9f0oAdqcIeBNgUOZEUEjIHNAFRNJaDyBnftXEhX 5VP4UAXLSWRpmRcvAPuuRjH496ALFxGHj3bgjLyrHtQAW84mUg4Drwy56UATUAMmjE0TRt0YUAR2 kjSQgOf3iHa/1FAE9ABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQ Bl2UUUgeP7RMGRyu0SEY/CgC19iX/nvc/wDf00AVY7KNtUm3STOBEnDOSOrUAXntoZEVDGML93H8 P0oApGKe5laDzh5MZDbwPmyOcf8A16AJ1sX3fPdzso+6AxXH1PegCvDZbLq6SO4nUnDLmQkA464+ tADfJ811g1KQvzlQeEf8P8aALZso4P3lpEkbjqFGAw9KAJY7qKTjcFfoVY4INADDexjUBZlW3lN2 7tQAjHyL4N/BN8p/3h0/TNAFqgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgA oAKACgAoAo28Ecwn3LhhM2GHBFAEnmy2/wAkitJ/dZR1+vpQBHp0on+0yAEfviOfoKALF1OLaBpM EnoqgZJP0oAjsWj8nCOGfOX9QTQA+S8tonKPPGrDqCwzQBSaZ59QYWcsTboTlgc7ecZoAZFaia1a S5Z55idpP93HpigCOz1UxN5LiWWJeDJsOU/3qAMiecXE15Pay7pwxCt1GMen9RQBpafbRwQxSmWW ScyqZDI2SBz09qANbUP+PQnuGXB/4EKALVABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAF ABQAUAFABQAUAFABQBnw3UMEtxFI+H8wtjHrQBJJqEaKfMR4wQdpcYBOKAMqzu5LR75UZZI9wkV1 GdpI5B/KgDQS5jubpN7bVj5TIxuOOtAFuW1gn5kiVqAM5Zo7IT2wjQmJd4Zj1B6ZP4GgBLG+tobF GjQtI6+YyxjON3PX0yaAEFpqbNNNHPHF5j71j+8CMDvQBRvIRbjypEuJZZj+9UNuGMHnt/k0ASJB FBDEbQ4mQDI/hUHoCP0oAzr+9+zRQiVZEmV2H7s5U9OM+lAHWXylrN8dip/Ig0ATqwZQw6EZoAWg AoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgCrCQt9c5wOEOT75oAoa3 KEeFHUsshCDAzgk4P6GgCPSLY2j3DxgeX5pUgKFyABg/qaALU941xEAtu3kt1kK7vyHWgCzBPbRw qn2heB/G2D+tAGRrWnOHa8jf90RmVQMnjofp1oA0rIC40gKjIVdCEKAYwenSgBLQ3j2sbK8RwNoB HXHHNAFS5dmuLh5lAmhjARQeGz3/AEFAFCKCeaOcQyJb7gu9SCGDEDJ/D8qALFrpUbm4t5t7LHGu 0FuAeeRQBrpIZdJEh6tDn9KAJrb/AI9Yf9wfyoAloAKACgAoAKACgAoAKACgAoAKACgAoAKACgAo AKACgAoAKACgAoAKACgAoApqiyXl2jdCqf1oAyb6zuZboRRTNJcIPkLj5VB6n64oASyt5nS5hnvZ lLPublRgEY9PY0AbnmRWsKozk4GB6mgCogjvZiJoxEOojZcM3uaAJZLSVY2SGX92wwUcZwPb/wCv QBSgg+yDYolgAICv2Hse2KAL2mkiyVXZSysQSOAeaAKOuIpUNDKFuWwAM9Rnv7UAZ10L2WR4fMUX JQlCw27c8ZHr+NADrG9kt9QeO7CIVi/eSmT73px+dAGxpksV5o0YhcMPL8skdjjBoAtWb77SM4xg bfyOP6UAT0AFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAUJplt758n 5pI/lHqR/wDroAWHT0MYkkyLhuXkU4OfT6dqAMfULaysdUSWYCaNxh0c7iB6/QUAb8Fvax/PBHGP daAHywxzrtkQMPegCrLE1oyTrLKyKcOrPkYPegCLWlle3iWPkF8MN2M+nP1xQBj/ANmm0k2oxaeU gvFIu8KPUegoAtvZwWg877QVlcbQkadfbrzQAhsDBEz3MzsVUsAOw9MfSgB0KNJMyTRQQQyxDb82 ScZ7Y680AX9GVFsNsYACuw474NAE1icRPH/ccj8zn+tAFqgAoAKACgAoAKACgAoAKACgAoAKAP/Z