20251104
08294600
1.0
FALSE
Lidar_Geomorph_2022
6116346.035000
6463976.573333
1798070.550833
2077528.653333
1
Projected
GCS_NAD_1983_2011
Linear Unit: Foot_US (0.304801)
NAD_1983_StatePlane_California_II_FIPS_0402_Feet_2011
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32
FALSE
None
1
AMD
TRUE
continuous
floating point
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
Basic
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
NONE
<_docversion_ Sync="TRUE">10
Name,MinPS,MaxPS,LowPS,HighPS,Tag,GroupName,ProductName,CenterX,CenterY,ZOrder,Shape_Length,Shape_Area,Thumbnail
0
47244
3.28083333333333
104.986666666667
MosaicFunction.OutputRaster
0
0
0
0
20251205
07261700
20251205
07261700
ISO19139
150000000
5000
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rVcF/s4t0Byy8/T1pGfdDHJtYFjkKwwfxFEs0UCqrEl2HzEfyoAsNGbXTy0QIY4A/wA/hSxuUUjcV5zjmqt9qNutqjs/yE5+UHg/5xT0vrOdRJ9pj5/2xQBUn1TyTsW2neQ9EVetSward2io15ZyKrYUuwDgD+lS2sF1NetqLwg2rHyvKLcjBPPtV2e1llkARG8hTwT3H1oAYfENlfSDyLONnIw8sZOQMdfTNQMlnpkJeWRN6neAew6gn39qjW3kW4lkjhYIOGUL0x6Va1GzS8uP3pjVBsMg/i4A4xQBny/adTifyY2iDgjewwfrU+m6ha2lt9gu4IpJ7cBW2kjIxwc0lxr8sV2ltaQiUkcxKAAAO5NRNbrE02oTsCWwrhR90en86ANC8kSfyp7eMqgUKUznae1VL6GGWVLGRFkL87WAIH+c1csYvsrSzxuskSx7hjGT2AP4kVktPu1oXEysIjGVDgZw2eaAHTaXBasksG63fozIeB6cdP0oa2yRJNIZY2OCc/0rSnlintTJGxZkG1hjn61SjZ4kIyXjGCwI5H0oAVrPyXKrtPcZXjFaFjYIttJNcRKishCIT99vp6U9GuEg82OCCe4IBiSXuvris25up5J/OfeH/iVun4elAEsk9yGxcksF4BxjaPTFNted8obBLEg+w6U5b6GdCsrMGHAJH6GobVTEGjyCgOV+hoAv3O+6jSdZFEwG2Tf39D+X8qytTE8McDsE2mRVJBzwTWpaxmZ5EGAzIQu7pkc1nahBdi3OYkfaQ2AeuDQBcjgkcfxYJ6jGfwoaMxnYxJ/3utRxah5tqkkeVVuNq9c+lPSA+YHlPzEZx/dFACpDM53Qvn6rwPxqc2nnwbXkiSXP3Q/HsRUc0xI2hiI16Cq6CS4+58i+pHP1oAlk00s+Wtw23qQOPzFRRoyIEdGRgccLVu0dbWQMJJHYZ+83y9PTvUBuZmZ5ppG3MSevSgBCFKqxC57duaRZgZgzbVfGOuAffpU8eoqWEMkazIDzhOfwao7q40xSqNFOSfcEn2xj+tACNEwG52Vi/O5TkGo0cLLyMc5Ydse1XoLBQCkVykYkXd5UxwVPbtxUD2c6u7lPljBD85H4etAEUBVLLEqBnjYlCPQkUWULrIzIwzhsqecntSqm0CNR8mPm9qlsoH+3mWFfMBySq8nIFAFGaNofKEeBPvDe59as3Iee+RjxGvX8s0XNpc21yskkL4Py8jpS3cyx7oRksRg470AVbuSSeWN4DwrjHGc1JPLaw3hubrzGj2hHhj6e/wBKfEzC53kKiRL8oHdjSRKMbmGdxJNADX1uS+tlGm6ZE1gCQBK2N3uT1NTW11b2FtJLPGEWMfKuOAT2FVAJbS8HkFWhcZeIj9RU9/B5trbTtiO2J3tk9cGgCjJbX11qi3ElzJsdflQDoff8KuXM9vplsZLyeGSQgDBPAz/Wlt7lhbiacBJJCWRT1Ve1UoLJHuJ5LpROZHBUSfwcfw0Aa9hdwXCFJ4I/src70ADD3/8A11Xew0eV2YNCwzjLQc1U1GaTTbuCyS33Wp5kmHUHqAfarImjA+VHYeqqMUAUbG3ujrUts0peGQq0fYgk4Naesakiyvaq4WGGTZCgPUDofrUNlcrH4us0j+6V5LDGSGFV9fjs7jUhp0MZVzMZFY9VVWoAtK17MAWmeNe6r3pdVgK3bQR7jO2F+U8njk0qh4uYnI9ietWbmRlSO+kUJK6bS6/7PHFAEVhYAXbwxquYQpcjqB16VAl5ayanfWUmVjdEJ4z1zz+lM0mC5ttSu78swjmQDDHuAR+PWoP7TisdcMbQb5J4gVOzI+Un/GgDXs7BLS5YSSQrDMpVctzyOOPyrPAV7lozgIg2+2c00TBrlp594kdsj0Aq0JLSeRgTskfjGOCaAGwwyJIwt8kj7yEZyKsPJBp0jmVC0rjcqsMqn19aLmQW9v8AY0f96vEjoOSQePyqrDeDy3W7jDqCMAjkDvigBlxOZf8AT45ixU8kHoRWk039oQeZtDSxLlip5ZfU1m6jZtHBK1lgxsN2F4J9qsWUyQwCS1yo2Et7+ooAjmWJgSy8VnyWd4pD2kiLznypMkfn1FbZhtJYvP8A3iMmAYxyM+oJqGTVIbeRkt4DLjgrjLZ+vagCrZ6lFvdZ/wDR50BBRz39j3p0Wu2luHXzhIrcEKN3Pt71CYv7TUNc26oN3yoecf8A16txwYlMUUYCIMEgYANAGXFPNYyyXs1mfsbMdgXl1/2mWr8V/DKWIfa7jJ3jBx+NOvpXmnW2tFYW8IJaUj7zccVYaxhv9PEk0S7OQ3tx2oArf64j/nmP/HquOTb2DcfvJTsHsKztImKhoJwRJDkJu/5aD+Ej1qa6kZowu75mcEfWgBN7IoXZucDsaSOymuiHnkZIhycDipI4gnCgkn8zVi5K29uEJJk6sPT0FAFaW4Ubo7VMDO1fU+5NWo2fTrQPId80hBwewqlp8R4ByWZ8frU+pORfOrdEYfTHagBh3tO8jnOcYqaO5MCtu2snUq3SoSyqu4nAqEy+c4jjRnGeTjigC3vQQx3Qt1WYlkUqxAPplfXJpZHMFqUCiMuNzspP+RReuBp9uB8p3Nhv73NR3rb0jG7LEDNAE1nf3EEQ2yFlYDcr8g/nVgw2t9Ipt9sE7nDRuflJ9j/Ss9m2gHBPpiiOKWZ9x+VU+bAPp60AEqyRA2oB8xmO446c0oXYNuMBfU1qHUra8iigkhIulIxMgB49xVV9Nnhg80bZYc/fQ7h+NAFOBfPHnBRnHTuBUtyqLBHHMxdIlyI+wOc02xgaPU9roUUgkEgjtmoZj506KW4LZY9fwoAajPdPLczLk9EHvTbgQz6fICxIXEYYHq3c/ganuS8VuIoxwoyTn1pYtPH2CPcAkeThj0yetAFS4LHSLdHO53ON3cDtz+Bq3vjt0RJbyKNyoJX0qKe4iYeRbDdLGuFGOAfeq50/R77E93Gsc5GHUnvQBM9v51xFKcxtCwdGB5z/AIVDFA/9oSXU8vmSuxUcYwOtaUjgRuW/gAwf51XEBlIdsgtwB6fjQBODGe7e/FT3MCT2NuRJmGNzvGPmyeQP0rLUgzmNnbcDwR3+taFthLe5DFm3KMZPfIoAhmmuLltzYiUdEHIqlZRrcX90Z2yy4RDjG0VerPtWD6leeWxGAqkgd+T/AFoAvlEC+RKvz/wv2I9KW2iMl3FDIu4MwAYDNKWYxeWzFhjAJ6ipJ702Sr5Unl4X94Sv3sjp9KAHTSRXE0kjv5RZs7SMgD6iqlzZWTArcGVlPG5DjH0NV47qfUNzW0PlRDrI/f6Cp3tkt7fE8zu7dVJoAsRpGkYh8x2jXlGflvoTVNoxZSHyG8yCU8jOcZqCCzmaVw11KFGCsY7CjUNPc2cjwyMLlPmTJ6kdjQBozzCy007xvnm5RAefYUlpBNFpL+YBJPvDM5GME9fwqnax6ZeQR3dzdFH2AqxO7Z6jrV6C7tbU/uZDdMwx8zcEUAFjCxYHHybmLHHAqK5vRErLDDIYic8kAsannuJLcBLWMLDjf1zknrn1rOiuZ9RYhrMW4QnL7uX/AA7UAVtHubywe4/tGEC2uZN6ktnGex9O1dHbQxXFrcw2d5GFkxhJG2n14PSq1xbTTMkaQO28rxtPSm31nMtmlvA2xS4MnlsG+btnHtQBYutNeCwWJdkh2/vGjO7ae3NYliHhvJbWd97KN8THuh/+vV22s9T01xc/2j5YbJaKVOWHpTbS3fXLo3ttEYI7dT+9bkPz0/3aAL9qgVhK/QdM/wA6oTS+ZcM2CxBO0eppkmqiK5e3n3eaBz5SFwR6jA4qSx8qSI3SkNG5+QA9aALmnxmPEkmAEBJ9z7VVupFMbtK+Bjk98VPJcbVDOeGUjA7VStoLq7aS4dRDAh6ydMCgB1tBNeBH3IqgZG7oB61PJKXP2aA4QfeccZNMupGeQQ24ZlC5kdR1P07VYsYHKmdkEcEX948sfSgCHUNqQpbKcqh2rn17mmysscAJPzHjjsBUN03mXKp3OT+tW4tOhmHnSu0caHoO/wBKAKqkysmA7nOdqjOPrVl5ZfL+yxKwkk+/x0FPa9lldbTS0EadM9z9TUUnmwyCztGM93IQZZMYxQA4rBplsztKXnIIVR0BPrTEuJ9L06Nt0oklYAkHOOw4qZUS2ZyxEkyqSGPQN7U15ZJJ/NZuQABQBNb3t7FcsjkOvpL83bnr0pyWKS+bLbN5gSTcsZXDbSePrioPMO9nb5mYYJNRrujAyfm9RQA/yZGuVEwZVOd4xjjFQ3T/AGmTyYmIhTjHYf8A16uDUmeM205E0bEAZPzJ7g1HLafY2EfG1uQw5BGeuaAKqLHZ6Y5VMSNJ8p7nmobnTxPIJN+3KjipLpPNkXljtPC+gqae2Ejqc9FAoAlnZPIYnO18ZHpzTiFCqQ2VzzxyKiv0dtCkKfeWTcB64HSnWd9aXVorRDeki5685oAq3SeVdxyLkqeMgdauxjbbzMDkMVGD27/0pkiRzLtt5Qx/iV/lP0qRU/0O4jYchlPB6UAV3YeWT1GKrLthuBk7cj8MYqw7FxjtjqT2pu1ZVeQrmMDbk+vtQBZBhwMZbPeq97BJd6l5IDNkA5x1HtUKo8ZKKxz1Udmq/aX8stjPB0AAZWA5XkA4P49KAJDHBbQiHduYckJ0HtmoJJLZW3vAxJ/i3dKgKRgjdNJu9gTTW8tP+Wz47714NAGlbtAzOVgBkCcZY8jvWff3otrWR+OhCLjqx6D86py3z2E8TRW8syk4CqOcH+lWGtUvpUurgAHqsR6Jx/OgCTT7VILOG3ZQdiAE+/eqrWsFnqEn7tcOctgdyetWIri5ilaDCjbyjHqw9akvr6O1t0uZoRJdP8oCjhvQ49c/yoAXV7lLe1gs4QvmhNiDuSTk/lmprSHyYhLJGSFHBPd+KpafYStePeXY8yYryo6Rr6D3qee9keQSHKMuAFYcY6YoAU3k6FlmmkeNv9o4z6VLYF7W0uZVkYTXOApB+6BzVLUp1js3dYwGYBVT1Y9P1qJ4NSttLiMt5D5mCFUJ1P50ALrN611CINrT3bMqk7jkL6mtm8maC3gsreMCEIrPsI5b3+lY2jxFLdZJDundsyNjqan1V2RbiaNmVsnaB3PQUAVtFvpFv7y6WAPibZzjkLWne6FLvF7pimFJhvweV98j696qaTaGO2hgH3ifmY+vcmpNS1F7T/SInk+XCIi/xDoBigCC1E9xdNDdRrG8IBODkEHoRVy7nZ7fygf3a9Aay1tb66upLu5uTD5igCGL+H6nvVm20u9mmEcE7zkHIVwP1NAFm3iZSFjJ3Hqc9asXkp+0RxE5SJO3Q8ZJ/M1FEWyYnwrr9/ByD9D6UkH79pZfY9fTpQBBZwFme7n4LfdU9l7U+eZ5FEKfePYdqa0oWNi33d3AHepLVP3ys/3mYZ9qAFWGfTrB5pQsbtwozg47n+n40mmows7i4ywk8rIPU5Jx/jTLp3l1GeDpsbr6Z9KtOv2aNIV4IGWIoAo277y/qTu/OpgCZMn7o6D1NV97NO/lgbjxz2xU8Wmzz/PKwRB/ETigBjyI0gT72OSBSAXU8istpIY843DuatCOztFOGaQ9yeBTftV1cgwxO0UR+X5epFADo7ZLW3nubiVQkC5KDrn3pmm3zSw+VOjYcggSEjy+eoFH2JYNodnaP3PU1JOlmpViHLL3z0oAimBSd1YkHnJx0qpJd3m8+QhWL+Dg8j1q8Ejvhu2MJBwAf48e3rTMM7ElV4OB9KABhK+n+Tj5ixyfQY61UsdNt5owsYKEf3DjmtC8ZRpe8MymRGYk9cVTsRNHYxThVdSu75e4NABDA8k0scgHnx8AHrVuzMolME6BFYFWGMVV1CGB1ivcbZehkjOCR7mplnaBEkEm5V/jbmgCMs07njbHnp6mlz/qLcDKjlqnkaJ51KMCkoyrL096VYAkm+SaNMgHBbt+FAEMY8y6e3+82flx9RirBVLSN404lc/vQOgx2oghhiv1uftAIKkbcHn61FIgSRlHr1Jzn3oAVJdhzsU/UU15FZ8bVBPYdqYzkEKBknp7ULHHGPlGD3J70AV3+e/jTuPSrksTIiSwsA2ck47+9Z9szSX80x+4cKnvjqa04maVhEUADt1zkg0ARSQm6kikTIlZcdMYI6/hVa+HmX9rZDa5gXzJmHIz2H6/pT9U1R7CBltOctsVe7EnHJ7Cn6VasjRrOxklkbfK3dj/AJ4oAt3bXMOyBYzgBXJ7kkZ/kartfsf9bGd/TJTOaS7vZ3mkk5VnJOM0lnZzXimaZjsDYOTgUAZs0hutYtodhEUIMpJ7t0A/ma1btwunq5VSy7lUn8Ko3AVdTRYEwYxlgPQ//qqzcET2IK/8s3yPxGKAG6UrKOVJZf3hX171X1CRrq6htTCUYt5rk+3T9f5VplVgg2D774LewHasrSw9zNcXMnzGSQog/wBkccUAasYEcRfoxG1fp3rHLi415IyA0dum7B6bjWjqU9ta27NJuKwrgMHOWP8AXmqtjZMLZGIInkbecdie1AGmghQebIQw52x5wSff2qez1H+0LS6g2R24/hMSYIx1B9aqyW8DqscrAyR9SBwT7ViLDL/aU6WF6Y7bIM2Bk7vQHt70ASPLcfbzbWARyBiRpDgKT2qYzX1ihFxaqY1+VnibOPwNaMFuunWwlhiyWOUK8892PvUlpfyX0E1tqBZ5UbdDITzg9qAMyK4jvEiki/1Wc7jxn2rSt1CkzP8AcTn8aztNRoEntwgCpMyqCO3X+tXyFdCZnAiT/lmnf60AQW5J8y5ZcPK/BNPvJNjO7HJA/Wn3LmWRMYVY/ugDFUZSZZ9vbOB/X9KAJtNtd6bnPJ+djUxm81Rj7g6CpiRb2B4wW6/SqWWWONFxubigAYeZMF/hXk/WrMjC2iO4/MRz7D0p1tbpG7B3BZRub61UZ/OnAJ6fMQfWgB8TufmYhBg/WlBXIdsEDnnpTjnjIAU801kDJ5k20g9FUdhQA5bl5pUKfMEbcSOgqeW906SQtLpYkkP3mR9oJ+lUnmmktvKhh2R98DBNNS1uCv7uMhfrQBY1YxtaursFWOLaQvTgciqumSQJp9uyz7AUGFPYelN1F1jtGZ+R6etTiCAxgov7mRcAjjBoAsSRKbRtvzdxtI6VCQII1kQgDeAVxwQaSGORSVBJXp6EVNuV5R5gLeVzsUAbunNAE0yRwAIsxCuFOV4CjH/1zmq0unRqF3NuIHyspzkUbPtQPmxMM9C7YpqWksIaLzzjsH52/jQA02sbbdxYAdwxB+lSYXaANw47nvTIfMido7iRWRjlHXt9ahu9QtbGULOdwJAAUZJNAE+Agz19TUarJcMq7gA3YDt7mhi/2QSqB87cLnt6VYhK6dZPO/zMRhc9zQBVH7mUL1APJq7ArIsswdRhcDd2J9KpwKzRl5eWfk1YDRrphckFVfr7Y70AZuoefP5UKhHlEiv0wAAa1bKZZLqNWBVzwQOOTxVKKGQJ9pk48w4BHUVbtt5u0MxBROd44IAoAaiQW87vcyB5c4CKeAPrTLq88xMqdkQ+6B0HsKcxhkkZlKvk88VVnYPKkY6cgn0oAWxtzGGmYnzZSCST27CtKHFlHNcMSC42KjDI3ZGTVZkbaFTrwQM9anusF0UjJRQp+tAGbf3Di1lZNwJGA3ck8DFT6LD5ENrCeTHjP59arzusmqWts/C4aU/UcD+dadjCYHklOCI0bnPUEYH86AMm7tIp7iC3C9W3+/HStWyMhM8e0iRY+cflmsw7pLwzIM7Bx7itCWZ44owsRyyhmIPPsKAKGpwvHAI1eWOSU7FIY5qxZ2SWqxW9uNgB5zznPUn1qnHJLd6uWkGIoBtRSc5Y9TWtI6W8IlyVMnCL1PvigBJY2ebmYCNOEQcACs65t2muhHBM0Mg5ZkwaLq6mERWFNrkcFu3virWlWa20fLFyBukdurGgDOUX+mOHMhu7ctufKgOv+Iq3DePcSAC1lEROSSMdO+KddyNLOsYOBjgD6/8A1quQozqyp1OB+FAFV72FnJVuOxxTLOeCX5kkSR1znBzgmjUWjgsXKRg4x26kmm3WkQxzJPaoIZVH31GA2exFAFq4kLWjgnLE/wA6g86JdjGRmx6L1qCKSWa5NvPtwoB44DVpIF3bIgjN0J2g0AVWmuJy5toQFY8lqSO3uIgT5fmMeWOMGrkk0dvyzM79gvApiz3E5DMojA7Dr+JoAjHnvz5Dkexpfssl0u7zDGg67j/Sp5ruV5xBbux2gc9B05NNkkJVY95YA8se9AAnkwtkF5GH8ROB+VXUvXZQftDR/wCyp4FZTSKZCqqzFT2pN8acTyBX649BQBHPtkuIYwNw3ZapVxavt/5ZngKegpssajZGMqd3brUrOXg2SR5YH7w7igC3GsYBnKyCJAOgzk+gqP7REokMSEOeDvPO32pJFMtnAI5WVwzZTbgduuetQfZpQpLO2R3wMUAOlZ4/nQ7h1Kk9RT08m4xlmVW9OtVyJSeqfXHWmncpDbCCOco1AEWpJFHaBBIytI6x4LYPLAcVZNlBDGI0jXHUMO9Zk2+bVoLmePzYVVgPZuOfyzzWwsnm2smyPa+zKgHIyKAGqOVX1OPpTZf9KhAOMxjbg9qWCaKaDeN4YdQR0NN2MJbsZxna9ADJMtARGCr5HHpTtSaRVsbbhPNcCRQPvEc/4VNbxbLx53JWPbgj1z0xVFRHLq89wJjIsKheTnBPX8elAGoiC4guI2yu2MsgHQmobUxz6DBdZBeViCD2AA/r/KpL1ktRCi5O8BuOpz61nWln5VzHYRsdskrSkjoARnH+fWgCwrqSwUZA6kDiobRPN3NjOOAP51em2QRFI1CoucnHU1nWLGOVxkgtyKALlvAyXCyr/qo/v55p8ksGS8kjBicngf4065dzEighUYbm2jljzUFtppnXzXICk9SaAM9ZoG18sXYL5G1WK993NbMIidJIxKGEi7cdMmqd8tr9rsbWNxvdy248DABJ/pU76a7DdBJGGHPBxmgBkEP+mGLG3AGR6CnXE2S8p7dB/IVZj8xbSZ7hMTjCBsc4/wAisy5cuywr3I3GgBtrH+6J/jLn5q1NSSO3dDjG2MAn8M/1qvDEg27l/dx/MfwqpIDd3PmyFjvYt8x6/WgB1tGJlklk7qSo96sRyx21l5knLSgfLnGAO9WIII44GkkVsE4RRxmsy+ka5vIrXgZ+Z8dlHAFADrbdK73DjAbhB6CtDH2eIhzh5AMAHoPelVEtokdly7DKL2A9TTd9pcMxnhKS4zkdG+lAGZqUiOILVMtPNIMD0UHJNa15fRRRLCo8x0UA5PGax7cQN4ld4RlIYVQ59S2f6VPfEFpFRQBvyx7daAKcdq97ePeyuykfLGo6AetT3El1p0XnRjz4SP3kY4ZR6j1+laFvbDADHZEv3mPp/U1DrOorFZOtvb8uQkak5Yk8df1oAbZCO5VJw4ZXG7cOgHtU7sCcKML6VENORLUNaSGEoMYzlT6ZFULa9kvN6So0MkZ2sgP3j7H0oA0kIhhYlhvfl29B6VDuaTnOyPse5oGnO4DyFiPQHgU77LtI3QnaeQ2cg0AIkix8RKx9CBTfKZ/mkCM3ct1q5FBtQyynEQPQnH4CmjyZss1qi84G5jkj1oAfKtrM0m0yRsuGAPJPtVGeSeCE3Fq4LxNuG8cfSrUSNBBLczoVdhhNx+8aZHLLd2kkUhXy3+4xHQ+tAC/JJbwT7gWlXeSDxgnio5AEOWkZz2GetWJIUtre0t3O6VIc7wONmTjn1qO3WNGaeUF2P3Y/agBFRIbbzpuZWGQCelRIjOgZ2LZGcdqb9oa8nn3IqRxgYA5yatXEgtojIwAITIHpxQBHZLG8bK33gDxnoabDILScbs+WTx+PUVFBCxjDZKyt8xxT2Z3j2ScPn5XHQmgCVLcrLIUUknnj0p4iWGU+e37yRgNvoB2P5dKdO8/lRpE+wMoZj3Pp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Sonoma County Vegetation Mapping and LiDAR Program
help@pacificvegmap.org
20251205
ArcGIS Metadata
1.0
Lidar_Geomorph_2022
2022-03-31
Sonoma County Agricultural Preservation and Open Space District
Sonoma County Vegetation Mapping and LiDAR Program
County of Sonoma ISD GIS Central
2615 Paulin Drive, Santa Rosa, CA, 95404, US
raster digital data
<div style='text-align:Left;'><div><div><p><span>LiDAR Derivatives for 14 California Countieshttps://tukmangeospatial.egnyte.com/dl/ADWSBBL7acLiDAR Derivatives Datasheet Sonoma</span></p><p><span>Original Coordinate System: NAD 1983 (2011) UTM Zone 10N</span></p><p><span>Projected Coordinate System: State Plane NAD 1983 (2011), CA Zone II, US Survey Feet</span></p><p><span><span>Horizontal Datum: NAD 1983 2011</span></span></p><p><span><span>Vertical Coordinate System: NAVD88 (Geoid 18)</span></span></p><p><span><span>Pixel size = 1-meter</span></span></p><p><a href='https://storymaps.arcgis.com/stories/183976156b3940bc93167e7461fdc673' target='_blank' style='text-decoration:underline;'><span><span style='text-decoration:underline;'>LiDAR Derivatives for 14 California Counties</span></span></a></p><p><a href='https://tukmangeospatial.egnyte.com/dl/ADWSBBL7ac' target='_blank' style='text-decoration:underline;'><span><span style='text-decoration:underline;'>https://tukmangeospatial.egnyte.com/dl/ADWSBBL7ac</span></span></a></p><p><a href='https://tukmangeospatial.egnyte.com/dl/ADWSBBL7ac' target='_blank' style='text-decoration:underline;'><span><span style='text-decoration:underline;'>LiDAR Derivatives Datasheet Sonoma</span></span></a></p></div></div></div>
The geomorphon raster is calculated from the DTM and classifies the landscape into distinct geomorphic classes based on relief-independent, local spatial pattern and the magnitude of overall relief. Landform types are then generalized into 10 distinct categories (see Table 5). They were calculated on a smoothed DTM aimed at reducing noise with a 30-meter search radius.
Geomorphon Code
Landform Type 1 = Flat
2 = Summit
3 = Ridge
4 = Shoulder
5 = Spur
6 = Slope
7 = Hollow
8 = Footslope
9 = Valley
10 = Depression
Funders: California Natural Resources Agency, State Coastal Conservancy, NASA, USGS, Sonoma Water, University of California, San Diego, Sonoma Ag + Open Space, Humboldt Bay Municipal Water District
Grantees & Coordinating Organizations: North Coast Resource Partnership, Solano County
Technical Team: NV5 Geospatial and Tukman Geospatial
Sonoma County
LiDAR
Light Detection And Ranging
ISO 19115 Topic Categories
imageryBaseMapsEarthCover
LiDAR
Light Detection And Ranging
imageryBaseMapsEarthCover
Sonoma County
<div style='text-align:Left;'><div><div><p><span>Publicly available.</span></p><p><span>This data has been reprojected from UTM Zone 10N. Horizontal units are in meters. Vertical units are in meters.Data Limitations and Missing Data: While it is great to have harmonized lidar data and county-by-county derivatives, there are numerous limitations to these data and some areas of missing data. Please be aware that these limitations can result in incorrect or misleading information. Limitations and areas of missing data include the following: 1. There is a 340,000 acre ‘hole’ (No Data) in the lidar data products between Del Norte and Humboldt Counties. 2. There are holes (No Data areas) over some tribal lands in Sonoma, Lake, and Mendocino Counties. 3. There are data quality issues, especially in the older Quality Level 2 datasets, leading to anomalies in the point clouds and the derivatives. These can manifest as ‘pits’ in the canopy height models, anomalous high returns in the canopy and forestry metrics that aren’t vegetation, and missing data in places. We are limited to the data quality of the source point clouds and couldn’t re-fly areas as part of this effort. 4. Note that because we have harmonized the point clouds and created products from a harmonized point cloud, there will be differences across collection boundaries in the characteristics of the data. These will stem from both numerous factors including variations in collection time of year, changes in ground condition between adjacent collection, point density of adjacent collections, and lidar collection specification differences of adjacent collections (e.g., point density, sensor characteristics, and processing specifications). Please be aware of these variations and the shortcomings that they impose when using these data for modeling and analysis. 5. There are particular issues with the 2017 FEMA R9 collection in Modoc County. As a result, some of the derivative rasters do not exist for Modoc County.</span></p></div></div></div>
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.
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LiDAR flight lines have been examined to ensure that there was at least 60% sidelap, there are no gaps between flightlines, and overlapping flightlines have consistent elevation values. Shaded relief images have been visually inspected for data errors such as pits, border artifacts, gaps, and shifting. The data were examined at a 1:3000 scale.
LiDAR has been collected and processed for all areas within the project study Area. In the First-Return surface model, only the highest hits are shown (e.g. tree-tops, roofs, etc.).
Relative Accuracy measures the divergence between points from different flightlines. Relative Accuracy median is 0.05 meters (0.16 feet) out of 106,255,665,985 laser points over 4,133 flightlines. For more information regarding the internal consistency between ground-classified points from different overlapping flightlines please see LiDAR data report.
The Fundamental Vertical Accuracy (FVA) of the data set is 0.03 meters (0.09 feet). Accuracy was assessed using 9,685 ground control (real time kinematic) points. These ground control points are distributed through out the project study area. Supplemental Vertical Accuracy (SVA) is reported as the deviation between landcover classified laser points and landclass checkpoints at the 95th percentile. The SVA for individual land classes are 0.27 meters for shrub, 0.09 meters for short grass, 0.19 meters for tall grass, 0.19 meters for mixed forest, 0.05 meters for developed areas, 0.12 for herbaceous upland natural areas, 0.05 for non-natural woody areas and 0.07 for barren areas. The supplemental vertical accuracies were calculated using 417 individual landclass checkpoints. Consolidated Vertical Accuracy (CVA) is reported as the deviation between both ground and landcover classified laser points from all survey checkpoints, reported at the 95th percentile. CVA for this dataset is 0.06 meters, and was calculated from 10,102 ground and landclass checkpoints. See LiDAR data report.
The FVA was tested using 851 independent ground control points (GCPs) located in open terrain. The GCPs were distributed throughout the project area. Elevations from the unclassified LiDAR surface were measured for the x,y location of each check point. Elevations interpolated from the LiDAR surface were then compared to the elevation values of the surveyed control. The Root-Mean-Square (RMSE) was computed to be 0.03 m (0.09 ft.). AccuracyZ has been tested to meet 0.05 m (0.17 ft.) FVA at 95 Percent confidence level using RMSE(z) x 1.9600 as defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using National Digital Elevation Program (NDEP)/ASRPS Guidelines.
0.05 meters RMSEz at 95 percent Confidence Interval.
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This raster data set represents highest hit surface elevations derived from classified LiDAR point data.
Sonoma County Vegetation Mapping and LiDAR Program