Data Access: The imagery is available as a dynamic image service (thanks to the UC Berkeley GIF for hosting) as well as for download as a lossy compressed Mr. SID mosaic (for use as visual reference only). Table 1 below shows download information. This imagery is best displayed as a color composite (also known as color infrared) for assessing fire effects.
Download information for the 2022 postfire imagery is shown in Table 1.
Table 1. Download information
Dataset
Description
Download Location
Mr. SID Lossy Compressed Mosaic
Image mosaic in Mr. SID format for use in desktop GIS software (for use as visual reference only)
https://vegmap.press/czu_postfire_imagery_sid
Dynamic, 4-band, Image Service
Image service hosted on ArcGIS Server at UC Berkeley GIF
https://zenith.cnr.berkeley.edu/arcgis/rest/services/CZU_IMAGERY/ImageServer
Dataset Summary:
This 4-band (Red, Green, Blue, and Near Infrared) imagery was collected in early summer, 2022 for the area that burned in the 2020 CZU Lighning Complex Fire. The data is 6-inch spatial resolution imagery and is in the California State Plane Zone 3 coordinate system.
These data were collected under a CAL FIRE grant to study the effects of the 2020 CZU Lightning Complex Fires. The data, along with accompanying post-fire QL1 lidar data, were collected to assess and map forest canopy damage and to assess the landscape variables most highly correlated to forest canopy damage.
The technical report that describes the post fire imagery, its collection, and its horizontal accuracy, is available here: https://vegmap.press/czu_postfire_imagery_report
Thanks for the UC Berkeley Geospatial Innovation Facility (GIF) for hosting this image service!For more information about mechanical treatment feasibility, visit this story map:https://storymaps.arcgis.com/stories/d176adc01bcf465ab846a7d93e1d625cMechanical Treatment Feasibility provides maps of where mechanical fuel treatments of woody fuels are difficult for legal or operational reason, and where they are not. This assessment will screen out locations where any proposed mechanical fuel treatments will be infeasible due to legal or operational constraints. This assessment does not include the feasibility of prescribed burning, which has different operational and legal constraints and can occur in areas where mechanical treatments may not be feasible. The North Coast Mechanical Treatment Feasibility assessment was based on a similar analysis by North et. al (2015) for mechanized treatment feasibility across National Forests in the Sierra Nevada. The Mechanical Treatment Feasibility assessment provides a map of treatment feasibility based on the following set of criteria: wilderness designation, slope, treatable vegetation, hydrology, and distance to roads/trails. This assessment utilizes a set of geospatial datasets to spatially represent these constraints on mechanical treatment of woody vegetation. The table below highlights each geospatial dataset, its source, its constraint on mechanical treatment of woody vegetation and the processing steps performed on the geospatial dataset to create the Mechanical Treatment Feasibility raster.
Data Set
Source
Mechanical Treatment Constraint
Processing
Wilderness Designation
National Wilderness Preservation System
Motors are prohibited in designated wilderness; this prevents vehicle access and the use of chainsaws, chippers, and other equipment, limiting the feasibility of mechanical treatments.
If designated wilderness, assign: "Low Feasibility – Designated Wilderness"
Slope
Pyrologix 30m Slope Raster
Areas with steep terrain are difficult to access with vehicles and make it difficult for humans to perform mechanical treatment activities.
If
40% slope, assign: "Low Feasibility – Steep (>40% Slope)"
Treatable Vegetation
CAL FIRE Fire and Resource Assessment Program (FRAP) Vegetation Map
Mechanized treatment of woody vegetation cannot be conducted in areas that do not have treatable woody vegetation such as woody shrub and forest areas.
If vegetation designation is 'Barren/other', 'Agriculture', 'Herbaceous', 'Water', 'Urban' area is considered un-mechanically treatable, assign: "Low Feasibility – No Treatable Woody Vegetation"
Hydrology
National Hydrography Dataset (NHD)
Riparian areas often have special permitting laws and/or protected species that hinder or prevent woody vegetation treatment.
Create a buffer of 100ft for perennial streams flowlines and 50 feet for intermittent stream flowlines. Assign these areas: "Low Feasibility - Likely Riparian"
Distance to Roads and Trails
Open Street Map Roads and Trails
Mechanical treatment requires road or trail access. Areas not road or trail-accessible have low feasibility for mechanical treatment.
Buffer roads and trails by 1,000 feet. Assign areas not within this 1,000-foot buffer as: "Low Feasibility - >1000 ft. from Road/Trail"
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Data Access: The imagery is available as a dynamic image service (thanks to the UC Berkeley GIF for hosting) as well as for download as a lossy compressed Mr. SID mosaic (for use as visual reference only). Table 1 below shows download information. This imagery is best displayed as a color composite (also known as color infrared) for assessing fire effects.
Download information for the 2022 postfire imagery is shown in Table 1.
Table 1. Download information
Dataset
Description
Download Location
Mr. SID Lossy Compressed Mosaic
Image mosaic in Mr. SID format for use in desktop GIS software (for use as visual reference only)
https://vegmap.press/czu_postfire_imagery_sid
Dynamic, 4-band, Image Service
Image service hosted on ArcGIS Server at UC Berkeley GIF
https://zenith.cnr.berkeley.edu/arcgis/rest/services/CZU_IMAGERY/ImageServer
Dataset Summary:
This 4-band (Red, Green, Blue, and Near Infrared) imagery was collected in early summer, 2022 for the area that burned in the 2020 CZU Lighning Complex Fire. The data is 6-inch spatial resolution imagery and is in the California State Plane Zone 3 coordinate system.
These data were collected under a CAL FIRE grant to study the effects of the 2020 CZU Lightning Complex Fires. The data, along with accompanying post-fire QL1 lidar data, were collected to assess and map forest canopy damage and to assess the landscape variables most highly correlated to forest canopy damage.
The technical report that describes the post fire imagery, its collection, and its horizontal accuracy, is available here: https://vegmap.press/czu_postfire_imagery_report