AndreaBozzo/ceres-open-data-index huggingface dataset:
Vegetation - Los Penasquitos Lagoon [ds3034]

The San Diego Coast District, Department of Natural Resources, and California State Parks created a fine-scale vegetation map of portions of the Los Penasquitos Lagoon. San Diego Coast District, Department of Natural Resources, and California State Parks conducted field reconnaissance assistance for this project, as well as accuracy assessment (AA) field data collection. CDFW’s Vegetation Classification and Mapping Program (VegCAMP) provided in-kind service to allocate and score the AA. The mapping study area consists of approximately 1204.82 acres of San Diego county. Prior to performing field work, preliminary polygons were delineated on a 2013 true color aerial image with 6 inch pixel resolution. The majority of polygons were later surveyed in the field and redrawn as needed to accurately reflect the boundaries of each vegetation type. Field data was collected from mid 2013 to early 2015. The primary purpose of the project was to further CDFW’s goal of developing fine-scale digital vegetation maps as part of the California Biodiversity Initiative Roadmap of 2018. Mapped vegetation was classified according to the Vegetation Manual for Western San Diego County (AECOM 2011) codes. Holland (sensu Oberbauer 2008) classes were derived via the crosswalk recommended in the Vegetation Manual for Western San Diego County (AECOM 2011). CNPS under separate contract and in collaboration with CDFW VegCAMP developed the floristic vegetation classification used for the project. The floristic classification follows protocols compliant with the Federal Geographic Data Committee (FGDC) and National Vegetation Classification Standards (NVCS). The vegetation map was produced applying heads-up digitizing techniques using LIDAR vegetation elevation data, false color infrared, and other aerial imagery. Map polygons are assessed for Vegetation Type, Percent Cover, Exotics, Development Disturbance, and other attributes. The minimum mapping unit (MMU) is 0.1 hectares. Mappers retained salt panne, mudflat, and water polygons that were below the MMU due to the importance of these habitats. In addition, polygons that were enclosed by these habitat types (such as islands of Salicornia pacifica surrounded by water) were allowed as exceptions to the MMU rule, as were polygons on the perimeter of the mapped area. Polygons initially mapped as salt panne, mudflat, or water that were later changed to a different category based on examination in the field were also allowed as exceptions to the MMU rule. Field reconnaissance and accuracy assessment enhanced map quality. The accuracy assessment was performed in the autumn of 2016. A total of 61 plots from 20 categories were evaluated. The final map accuracy was 56% using a traditional error matrix. There was a total of 42 mapping classes. The overall Fuzzy Accuracy Assessment rating for the final vegetation map, at the association levels, is 89% percent.
Elk Home Range - McAdams - 2017-2021 [ds2992]

The project lead for the collection of this data was Carrington Hilson. Elk (2 adult females) were captured and equipped with GPS collars (Lotek Iridium) transmitting data from 2017-2021. The McAdams herd does not migrate between traditional summer and winter seasonal ranges. Therefore, annual home ranges were modeled using year-round data to demarcate high use areas in lieu of modeling the specific winter ranges commonly seen in other ungulate analyses in California. GPS locations were fixed between 1-6 hour intervals in the dataset. To improve the quality of the data set as per Bjørneraas et al. (2010), the GPS data were filtered prior to analysis to remove locations which were: i) further from either the previous point or subsequent point than an individual pronghorn is able to travel in the elapsed time, ii) forming spikes in the movement trajectory based on outgoing and incoming speeds and turning angles sharper than a predefined threshold , or iii) fixed in 2D space and visually assessed as a bad fix by the analyst. The methodology used for this migration analysis allowed for the mapping of the herd’s home range. Brownian bridge movement models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data from 2 elk, including 6 annual home range sequences, location, date, time, and average location error as inputs in Migration Mapper. BBMMs were produced at a spatial resolution of 50 m using a sequential fix interval of less than 27 hours. Large water bodies were clipped from the final output. Home range is visualized as the 50th percentile contour (high use) and the 99th percentile contour of the year-round utilization distribution. Home range designations for this herd may expand with a larger sample.
Sonoran Desert Toad Range - CWHR A030 [ds1158]

Vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for California's wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage ([https://www.wildlife.ca.gov/Data/CWHR]). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.
Elk Home Range - Red Schoolhouse - 2017-2021 [ds2994]

The project lead for the collection of this data was Carrington Hilson. Elk (3 adult females) were captured and equipped with GPS collars (Lotek Iridium) transmitting data from 2017-2021. The Red Schoolhouse herd does not migrate between traditional summer and winter seasonal ranges. Therefore, annual home ranges were modeled using year-round data to demarcate high use areas in lieu of modeling the specific winter ranges commonly seen in other ungulate analyses in California. GPS locations were fixed between 1-6 hour intervals in the dataset. To improve the quality of the data set as per Bjørneraas et al. (2010), the GPS data were filtered prior to analysis to remove locations which were: i) further from either the previous point or subsequent point than an individual pronghorn is able to travel in the elapsed time, ii) forming spikes in the movement trajectory based on outgoing and incoming speeds and turning angles sharper than a predefined threshold , or iii) fixed in 2D space and visually assessed as a bad fix by the analyst. The methodology used for this migration analysis allowed for the mapping of the herd’s home range. Brownian bridge movement models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data from 3 elk, including 7 annual home range sequences, location, date, time, and average location error as inputs in Migration Mapper. BBMMs were produced at a spatial resolution of 50 m using a sequential fix interval of less than 27 hours. Large water bodies were clipped from the final output. Home range is visualized as the 50th percentile contour (high use) and the 99th percentile contour of the year-round utilization distribution. Home range designations for this herd may expand with a larger sample.
Elk Home Range - Reservation Ranch - 2017-2021 [ds2995]

The project lead for the collection of this data was Carrington Hilson. Elk (3 adult females) were captured and equipped with GPS collars (Lotek Iridium) transmitting data from 2017-2021. The Reservation Ranch herd does not migrate between traditional summer and winter seasonal ranges. Therefore, annual home ranges were modeled using year-round data to demarcate high use areas in lieu of modeling the specific winter ranges commonly seen in other ungulate analyses in California. GPS locations were fixed between 1-6 hour intervals in the dataset. To improve the quality of the data set as per Bjørneraas et al. (2010), the GPS data were filtered prior to analysis to remove locations which were: i) further from either the previous point or subsequent point than an individual pronghorn is able to travel in the elapsed time, ii) forming spikes in the movement trajectory based on outgoing and incoming speeds and turning angles sharper than a predefined threshold , or iii) fixed in 2D space and visually assessed as a bad fix by the analyst. The methodology used for this migration analysis allowed for the mapping of the herd’s home range. Brownian bridge movement models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data from 3 elk, including 5 annual home range sequences, location, date, time, and average location error as inputs in Migration Mapper. BBMMs were produced at a spatial resolution of 50 m using a sequential fix interval of less than 27 hours. Large water bodies were clipped from the final output. Home range is visualized as the 50th percentile contour (high use) and the 99th percentile contour of the year-round utilization distribution. Home range designations for this herd may expand with a larger sample.
Vegetation - Santa Lucia Preserve [ds2924]

Aerial Information Systems, Inc (AIS) was contracted to create both a baseline vegetation map derived from 1990s-era imagery and an updated 2010 vegetation map for the Santa Lucia Preserve (Preserve) and neighboring properties to the west, for a total area of 25,630 acres. The neighboring properties are contiguous with the western boundary of the Preserve and are owned by several different organizations. These adjacent properties are: Whisler-Wilson Ranch, Palo Corona Regional Park, both owned by Monterey Peninsula Regional Park District (MPRPD); Mitteldorf Preserve, owned by Big Sur Land Trust (BSLT); a small portion of the Joshua Creek Canyon Ecological Reserve, which is the property of the California Department of Fish and Wildlife (DFW); and several pieces of private property owned by individuals. The vegetation mapping classification created for the project area is based on a floristic vegetation classification according to the National Vegetation Classification (NVCS) and on California statewide vegetation mapping and classification standards.
Elk Home Range - Rowdy - 2017-2021 [ds2996]

The project lead for the collection of this data was Carrington Hilson. Elk (4 adult females) were captured and equipped with GPS collars (Lotek Iridium) transmitting data from 2017-2021. The Rowdy herd does not migrate between traditional summer and winter seasonal ranges. Therefore, annual home ranges were modeled using year-round data to demarcate high use areas in lieu of modeling the specific winter ranges commonly seen in other ungulate analyses in California. GPS locations were fixed between 1-6 hour intervals in the dataset. To improve the quality of the data set as per Bjørneraas et al. (2010), the GPS data were filtered prior to analysis to remove locations which were: i) further from either the previous point or subsequent point than an individual pronghorn is able to travel in the elapsed time, ii) forming spikes in the movement trajectory based on outgoing and incoming speeds and turning angles sharper than a predefined threshold , or iii) fixed in 2D space and visually assessed as a bad fix by the analyst. The methodology used for this migration analysis allowed for the mapping of the herd’s home range. Brownian bridge movement models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data from 4 elk, including 7 annual home range sequences, location, date, time, and average location error as inputs in Migration Mapper. BBMMs were produced at a spatial resolution of 50 m using a sequential fix interval of less than 27 hours. Large water bodies were clipped from the final output. Home range is visualized as the 50thpercentile contour (high use) and the 99thpercentile contour of the year-round utilization distribution. Home range designations for this herd may expand with a larger sample.
Elk Home Range - Sinkyone - 2019-2021 [ds2997]

The project lead for the collection of this data was Carrington Hilson. Elk (2 adult females) were captured and equipped with GPS collars (Lotek Iridium) transmitting data from 2019-2021. The Sinyone herd does not migrate between traditional summer and winter seasonal ranges. Therefore, annual home ranges were modeled using year-round data to demarcate high use areas in lieu of modeling the specific winter ranges commonly seen in other ungulate analyses in California. GPS locations were fixed between 1-6 hour intervals in the dataset. To improve the quality of the data set as per Bjørneraas et al. (2010), the GPS data were filtered prior to analysis to remove locations which were: i) further from either the previous point or subsequent point than an individual pronghorn is able to travel in the elapsed time, ii) forming spikes in the movement trajectory based on outgoing and incoming speeds and turning angles sharper than a predefined threshold , or iii) fixed in 2D space and visually assessed as a bad fix by the analyst. The methodology used for this migration analysis allowed for the mapping of the herd’s home range. Brownian bridge movement models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data from 2 elk, including 3 annual home range sequences, location, date, time, and average location error as inputs in Migration Mapper. BBMMs were produced at a spatial resolution of 50 m using a sequential fix interval of less than 27 hours. Large water bodies were clipped from the final output. Home range is visualized as the 50thpercentile contour (high use) and the 99thpercentile contour of the year-round utilization distribution. Home range designations for this herd may expand with a larger sample.
Elk Home Range - Timmons - 2017-2021 [ds2998]

The project lead for the collection of this data was Carrington Hilson. Elk (2 adult females) were captured and equipped with GPS collars (Lotek Iridium) transmitting data from 2017-2021. The Timmons herd does not migrate between traditional summer and winter seasonal ranges. Therefore, annual home ranges were modeled using year-round data to demarcate high use areas in lieu of modeling the specific winter ranges commonly seen in other ungulate analyses in California. GPS locations were fixed between 1-6 hour intervals in the dataset. To improve the quality of the data set as per Bjørneraas et al. (2010), the GPS data were filtered prior to analysis to remove locations which were: i) further from either the previous point or subsequent point than an individual pronghorn is able to travel in the elapsed time, ii) forming spikes in the movement trajectory based on outgoing and incoming speeds and turning angles sharper than a predefined threshold , or iii) fixed in 2D space and visually assessed as a bad fix by the analyst. The methodology used for this migration analysis allowed for the mapping of the herd’s home range. Brownian bridge movement models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data from 2 elk, including 6 annual home range sequences, location, date, time, and average location error as inputs in Migration Mapper. BBMMs were produced at a spatial resolution of 50 m using a sequential fix interval of les than 27 hours. Large water bodies were clipped from the final output. Home range is visualized as the 50thpercentile contour (high use) and the 99thpercentile contour of the year-round utilization distribution. Home range designations for this herd may expand with a larger sample.
Elk Home Range - Tolowa - 2017-2021 [ds2999]

The project lead for the collection of this data was Carrington Hilson. Elk (8 adult females) were captured and equipped with GPS collars (Lotek Iridium) transmitting data from 2017 to 2021. The Tolowa herd does not migrate between traditional summer and winter seasonal ranges. Therefore, annual home ranges were modeled using year-round data to demarcate high use areas in lieu of modeling the specific winter ranges commonly seen in other ungulate analyses in California. GPS locations were fixed between 1-6 hour intervals in the dataset. To improve the quality of the data set as per Bjørneraas et al. (2010), the GPS data were filtered prior to analysis to remove locations which were: i) further from either the previous point or subsequent point than an individual pronghorn is able to travel in the elapsed time, ii) forming spikes in the movement trajectory based on outgoing and incoming speeds and turning angles sharper than a predefined threshold , or iii) fixed in 2D space and visually assessed as a bad fix by the analyst. The methodology used for this migration analysis allowed for the mapping of the herd’s home range. Brownian bridge movement models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data from 8 elk, including 18 annual home range sequences, location, date, time, and average location error as inputs in Migration Mapper. BBMMs were produced at a spatial resolution of 50 m using a sequential fix interval of less than 27 hours. Due to a high variance parameter (greater than 8000), one home range sequence was run with a fixed motion variance of 1000. Large water bodies were clipped from the final output. Home range is visualized as the 50thpercentile contour (high use) and the 99thpercentile contour of the year-round utilization distribution. Home range designations for this herd may expand with a larger sample.
Sooty (Blue) and Ruffed Grouse Hunt Zone [ds1341]

Mapped hunt boundary is an approximation of regulations using best available data as of September 2015. Hunters are responsible for knowing the exact current boundary locations as described within the California Code of Regulations, Title 14, Section 300(a)(1)(E)3: 3. Area Open Zone: The open hunting zone for sooty and ruffed grouse includes the following counties: Alpine, Amador, Butte, Calaveras, Del Norte, El Dorado, Fresno, Glenn, Humboldt, Inyo, Lake, Lassen, Madera, Mariposa, Mendocino, Modoc, Mono, Nevada, Placer, Plumas, Shasta, Sierra, Siskiyou, Tehama, Trinity, Tulare, Tuolumne, and Yuba. All other counties are closed to the taking of sooty or ruffed grouse.
NCCP Gains & Losses - San Diego [ds892]

An NCCP identifies and provides for the regional protection of plants, animals, and their habitats, while allowing compatible and appropriate economic activity. Working with landowners, environmental organizations, and other interested parties, a local agency oversees the numerous activities that compose the development of an NCCP. CDFW and the U.S. Fish and Wildlife Service provide the necessary support, direction, and guidance to NCCP participants. HabiTrak consolidates the NCCP Habitat Gains and Losses into a single system.
California Bumble Bee Atlas Sampling Grids - 2022 [ds3004]

The California Bumble Bee Atlas sampling grid cell map for 2022. Trained volunteers participate in the atlas by adopting a grid cell to conduct at least two surveys in 2022. The project launches on three different dates based on the start of bumble bee flight season: March 15th in southern California, April 15th in central and coastal California, and May 15th everywhere else. For more information please visit [https://www.cabumblebeeatlas.org/].
State Highway Network Lines

StateHighways are state highways based upon the Caltrans Linear Referencing System. Each record in this layer represents a highway segment where the county, route, postmile prefix, and postmile suffix are the same. Each segment has a begin and end postmile. This geometry is based upon the extraction from TSN on 8 June 2025. Route geometry updates based upon this extraction include routes 3, 36, 38, 49, 89, 139, 174, and 221. All updates received an update date of 6/8/2025 except for route 221 which received a date of 7/1/2025.
State Highway Network Postmiles Tenth

Postmiles are valid postmile points at 0.1 (1/10th) mile intervals, based on the Caltrans Linear Referencing System. Exceptions that are included are the beginning and ends of routes (and other situations) that don't necessarily begin or end on the even 0.1 mile interval. This geometry is based upon the extraction from TSN on 8 June 2025. . Route geometry updates based upon this extraction include routes 3, 36, 38, 49, 89, 139, 174, and 221. All updates received an update date of 6/8/2025 except for route 221 which received a date of 7/1/2025.
Wildlife Movement Barrier Priorities - CDFW - 2020 [ds3023]

CDFW divides the state into six administrative Regions. CDFW staff in each Region identified linear segments of infrastructure that currently present barriers to wildlife populations in their jurisdiction. In doing so, the Regions used all available empirical information in their possession, including existing connectivity and road crossing studies, collared-animal movement data, roadkill observations, and professional expertise. The dataset represents the ten highest priority barriers identified in each region. This dataset represents CDFW's initial effort to identify priority wildlife movement barriers across the state. Currently, increasing attention is being directed toward wildlife habitat connectivity as a mechanism of maintaining biodiversity in the face of population growth and climate change. Listing priority wildlife barrier locations will help focus limited financial resources where the highest need has been identified to improve wildlife movement. This is complementary to CDFW’s fish passage barrier priorities that have been identified for anadromous fish. Like the fish passage priorities, the wildlife barrier priorities list will be periodically updated to reflect new information and barrier removal successes. Most of the barriers identified are highway segments, but the list also includes a local road, a high speed rail segment, and a concrete water conveyance canal. Additional information can be found in this report: [https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=178511]. [Wildlife Movement Barriers - CDFW [ds2867]] represents a comprehensive dataset of all barriers identified to date, including those which have been remediated since 2020.
Quail Hunt Zones [ds1342]

Mapped hunt boundary is an approximation of regulations using best available data as of September 2015. Hunters are responsible for knowing the exact current boundary locations as described within the California Code of Regulations, Title 14, Section Quail 300(a)(1)(B)3: 3. Area Zone Descriptions: a. Zone Q1: The early mountain quail season hunting zone includes the counties of Alpine, Butte, Del Norte, Glenn, Humboldt, Inyo, Lassen, Modoc, Mono, Plumas, Shasta, Sierra, Siskiyou, Tehama, Trinity, and those portions of Amador, Calaveras, El Dorado, Fresno, Madera, Mariposa, Nevada, Placer, Tuolumne, Tulare, and Yuba counties lying east of the western boundary of the national forests. b. Zone Q2: The early coastal quail season (all species) hunting zone includes the counties of Marin, Napa, Solano, Sonoma, Lake, and Mendocino. c. Zone Q3: The balance of the state season (all species) hunting zone includes the remaining land area not included in Zone Q2 (the counties of Marin, Napa, Solano, Sonoma, Lake, and Mendocino).