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Table · dataset · 2025

Vegetation - Northern California Coast [ds3196]

Listed in California Open Data

Phase 1 Under contract to the California Department of Fish and Wildlife (CDFW), Tukman Geospatial was tasked to provide floristic classification data collection, fine-scale vegetation mapping and accuracy assessment (AA) data collection, within western Del Norte, Humboldt, and Mendicino counties of California.

Description

The California Native Plant Society (CNPS) was subcontracted to perform the floristic classification data collection within approximately 6.31 million acres focused mostly in the Northern California Coast (NCC) with some work in the Northern California Coast Ranges (NCCR) ecoregions , alongside CDFW staff who focused more on the NCCR area .

Aerial Information Systems, Inc. (AIS) was subcontracted to conduct the photo interpretation and mapping of vegetation for approximately 1,820,150 acres within the NCC ecoregion. 15 cm 4-band aerial imagery from Hexagon from 2022 was used for the creation of this map. The minimum mapping unit (MMU) is 1 acre; exceptions are made for wetlands and riparian types, which were mapped to a ¼ acre MMU size.

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Field reconnaissance and accuracy assessment enhanced map quality. There was a total of 110 mapping classes. The overall Fuzzy Accuracy Assessment rating for the final vegetation map (Alliance and Group levels) is 90.60 percent (Users score) and 91.04 percent (Producers score).

The vegetation map adheres to the National Vegetation Classification Standard (NVCS) and the Survey of California Vegetation (SCV). Report is in progress as of July 2026, but will be available at: nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=232835 Phase 2 Under contract to the California Department of Fish and Wildlife (CDFW), Aerial Information Systems, Inc. (AIS) was tasked to provide fine-scale vegetation mapping and accuracy assessment (AA) data collection, within the Northern California Coast ecoregion in southern Humboldt County and Mendicino County.

The California Native Plant Society (CNPS) was subcontracted to perform the floristic classification data collection within approximately 6.31 million acres focused mostly in the Northern California Coast (NCC) with some work in the Northern California Coast Ranges (NCCR) ecoregions , alongside CDFW staff who focused more on the NCCR area . Aerial Information Systems, Inc. (AIS) was subcontracted to conduct the photo interpretation and mapping of vegetation for approximately 1,820,150 acres within the NCC ecoregion. 15 cm 4-band aerial imagery from Hexagon from 2022 was used for the creation of this map.

The minimum mapping unit (MMU) is 1 acre; exceptions are made for wetlands and riparian types, which were mapped to a ¼ acre MMU size. Field reconnaissance and accuracy assessment enhanced map quality. There was a total of 110 mapping classes.

The overall Fuzzy Accuracy Assessment rating for the final vegetation map (Alliance and Group levels) is PENDING. The vegetation map adheres to the National Vegetation Classification Standard (NVCS) and the Survey of California Vegetation (SCV). Report is in progress as of July 2026, but will be available at: nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=246735 Dataset can be downloaded from: filelib.wildlife.ca.gov/Public/BDB/GIS/BIOS/Public_Datasets/3100_3199/ds3196.zip

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Stated by source
Natural Resources
Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
California Open Data5e4b4f3e-259e-4a92-ae1a-0f09c4a0444613 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · data ca govconnector:data_ca_gov@1.0.0
concepts[topic].ckan_group:data_ca_gov:natural-resourcessource · data ca govconnector:data_ca_gov@1.0.0
created_datesource · data ca govconnector:data_ca_gov@1.0.0
descriptionsource · data ca govconnector:data_ca_gov@1.0.0/notes
license_textsource · data ca govconnector:data_ca_gov@1.0.0
publication_datesource · data ca govconnector:data_ca_gov@1.0.0
titlesource · data ca govconnector:data_ca_gov@1.0.0/title
updated_datesource · data ca govconnector:data_ca_gov@1.0.0