20191118 14034000 1.0 TRUE This dataset is the result of a 2019 park tree study which involved 394 sample plots across 44 Arlington parks. The data are organized by park and include the most common species found at each park, the approximate level of interest or uniqueness of the tree species, an objective classification of the best time to view the trees, and relative presence of select tree categories (oak, elm, ash, maple, conifer, nut, fruit, thorn, and bloom species). The data may be filtered to only sampled parks using the field "Sample2019". Trees per acre were estimated for all 98 parks using a combination of sample plots, tree inventories, and estimated tree cover. FAB Forestry Arlington Parks Parks & Recreation Recreation Tree Data Trees Urban Forestry Arlington, TX Park Tree data from 2019 study. This layer provides an estimate of the number of trees per acre for 98 Arlington parks. Also included are the ten most common species and relative presence of trees in defined categories for 44 parks. Jeremy Priest, Jamie Najar; Arlington Forestry and Beautification Public /9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCACFAMgDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD3+iii gAooooAKKKKACiiigAooooAKKKKACiiigAooooAjmmS3geaUkRoNzEAnA+got7iK6t47iBw8Uihk Ydwa5PxzqOo2yQWlupW1uVKySKuSx6bPbj8/zrp9Ps10/T7e0V2cQoE3N3xWMK3NUlBL4f1FfUs0 UUVsMKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA8/fxdrmrzZ0eyZI4sF1VPMJ z0yccdD0qaz8Ua7a362+padJI9ywEUYURlR0OMjnt1PFaNpZv4aj22lmVWbAfneMqDzkuMd60o9J kur621DUzGbm3LiNIAQgB6ZzyT37dfbJ8XDOvVd3KSmrXTSta/8AkJwa1uZujeL2vtTXTb2z+zXJ 3A/MQARzjBGRxXRpNb3ayxxTo+35H8uTlT+HQ1ymq3a3+u28V5ZRJa20rK8k4DK65HJJHA49e9aj aSl3fxz2l2yabJGWdLWTaGcAKpDLyABzgHGV9znvw1SUlJN81na9rdv6uaTpyhbm66kMVrfapfmG 5lZbCxlUo4Klp5FLc56rjKg+uPeujqpb2f2CKGC0QGLezStI5LHIJznnJLY69s1brpirb7kBRRRV AFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUjMEQsxwoGSailuYoZoIZGIknYrGME5I UsfpwD1qYgEEEZB7UAVbS8s9Ut/OtpEniDY3behH1qZfO8993l+TgbMZ3Z75rnPAkF5b6DKl7BPB L9qkISZSCF4x17V09RBuUU3uaVYezm4XvYqSQx6pZ3Fre2h8iTdG8bnh1/D/AD/Oiz0yz08KLS3W ELGsQC5wFX7o/DNW6ofbpZNWeyhiTbCqvK7tg4bOAoHXp3xTtbczt1LksgiTewYjIHyjJ5OP60+i iqAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAqvfXaWFnLcurMEGdqDJY+g/wA8VJLc QwDM00cYwTl2A4HU81FLBaalBGXCzxA7kKtwTgjOR14JpX6Aclps/izWvEtnPqmlQaTp9qzyohlE ksnyFMEg4x8wPQdK7GN52uJleFVhUL5cgfJf1yMcY47nPtRcXEVrF5szbV3KgOCeWYKBx6kgUT28 VzGEmXcoOcZI/lSSaXcUY8q11JabtYBtr8k5BYZxTFcJMLdYXCBMhwBsHONv1pQZRIAQrIcksOMd MDHfvz7VQxVZJ4sq2UYEZU4/XtWJp9mF8Q3VzbxE221Y/ONxuBYDkAd+oznoQaU3lzq18YLB3Wzj cefMfkyASGROMkn1B4xV3R9MTR7Q2cTySR+Y8is5yRuYnGe/XrWek2muhfwp33NCiq0c0008bxoh s3iDiQkhtx6DbjpinNOxSbyYWeSNtoVvkDHAPBPbnqM9DWlybE9FRwGYwqZ1RZf4hGxZR9CQM/lU lAgooooAKKKKACiiigAooooAKKKKACiiigAooooAxdR0+DXbaTfFJbywyFI5ZUxnHcDup7VVVJfD 3hl40jf7bIpYsmSqOcDcWIIGOPy+prpKRlDKVYZBGCD3rD6vT9p7VL3rWuae1lycl9OxX0+SWbTr aSZkaZolMjIMAtjnGffNTyMyROyIXYKSEBA3H05rk7YX8Hi22tYZbmXT7ZTG5DErypxv7Zz39q66 qpVOdO620MxFJKAsu0kcjPSq1xdtDFdslrNK8Ee9VVf9acE7VPc8Y/EVNB5phXzwgl/i2dKyvFGp rpWhyTkzb9yBFhPzsdwJA/DOfatG7K7KhBzkox3ZqW6JHCPLQorEyFTnILEsevuTTpvN8mTydnm7 Ts3527scZx2zVfTL46lpkF79nltxMu8Ry/eA7Z+o5/Gp4LiG5j8yCVZEyRuQ5GR1oTuhNOLs+g21 +0/Z1+1mIzfxeSCF/DPNTVDHcrJdTW4Vw0QUliODuz0/KpqYMKKKKBBRRRQAUUUUAFFFFABRRRQA UUUUAFFFFABUNuZyJPPVQRIwTb3XsevWi6me3tZZo4HndFJWKMjc59BnAzUwOQDjHtSAZKrvHtjk 8tsj5sA8Z56+2aec4OOtFFMCKBpPKjW48sXBXLLGcjPfGecc/rUvSqsPkvqFw4tWSZAqNMyYEgxk AHuBk/jT7q1S7REkLAJIko2nGSpBGfbIoAnqm4mngaHzEhvhHkSrHvWPJIBGevTpUt5e2un2zXF5 PHBCpALyHAGelSxyJLGskbBkcBlYdCD0NLyHZpXFUEKATkgck96WiimIKKKKACiiigAooooAKKKK ACiiigAooooAKKKKACiiigCrqQuzp04sTi62Hyjxw348UthHcRWEEd3IJLhUAkcdzVmily63AhS7 gkupbVXzNEAzrg8A9OelKtvEtw04QCVxhm9RUtQXVql2iK7yrscODHIUOR6kdR7UD0J6r3ctzFGh tbYXDGRVZTJs2qerZwc49KsVysnjWOHT5LltPmeRLqWEwxEsRHGRvlJxwADnH0FDaWg0nZz6I0/E Wgx+ItOFjNdTQRbwzeVj5sdAcj15qzpdo+nWiWcl690UHyGRVVlQAADCgccdfercM0dxBHNE26OR Q6nGMgjIqK5sorklstHNt2CWM4cDIOM+mQKlxSbklqV7WTgqd9Nx0VuY7iebz5X83b8jtlUwMfKM cZ71MQCCCMg9qzDY38QJttQAYj7s0bSKfzbI/CqcOj63HZCL/hIH8w5LObdXOfQE9v8AIx0qYzk4 3cdfl/mZvQure6fp0iabBuMo5WGJWcjJzyei5/2iK0hnAz1rO0rTLLToitvEvnDKyzbSGds7jknk 8n1NaNXG9tQCiiiqAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACqiX8cryRRA+apZVDggMR7 4PH+cVbrm49PnRPOis5hNtzuEgQ5x/vAivNzDGVsM4OlTc7vWyvp+hcIp7s2YP7QBg877OQd5m2s cjn5AvAzxwc4p1+5is5pUh82UIVRQhbJPGMDnGcZ9hU6LsjVdxbAAyeppk6zt5fkSImJAX3LnK9w PQ+9eiQZugaJ/YtjFCbu4ncQxoweVmRSq4JQE8Ann/63FaTpBdxPFIsc0edrKQGGR2IqWsua/ezm lit9HvZWL7iyBArk9TktS+ECsvhtYWle0uHtH8wNC0TucDuHUthgTnjA4qSG219yiXGoWqIiY8yG HLyN6kNwPw71Yj1OY2onm0y7iXBJUAOw6Y+UHPc9u1Y/hL+2Teao99NNPZSTlreSddjj2C44GMeg yOOprN8qkklv2LUU4tt2t07m7p8twbaJbslrhlLEiEoMZ4B5IB5HGauUUVqlYgKKKKYBRRRQAUUU UAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQ B//Z