AndreaBozzo/ceres-open-data-index huggingface dataset:
Elk Home Range - Harts Valley - 2021-2023 [ds3082]

The project lead for the collection of this data was Carrington Hilson. Elk (1 adult female) was captured and equipped with GPS collars (Lotek Iridium) transmitting data from 2021-2023. The Harts Valley 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 1-7 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 1 elk, including 2 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. 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 - Laytonville - 2022-2023 [ds3083]

The project lead for the collection of this data was Carrington Hilson. Elk (1 adult female) were captured and equipped with GPS collars (Lotek Iridium) transmitting data from 2022-2023. The Laytonville 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 1-7 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 1 elk, including 1 annual home range sequence, 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. 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 - Little Lake - 2022-2023 [ds3084]

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 2022-2023. The Little Lake 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 1-7 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 2 annual home range sequence, 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. 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 - Shamrock - 2022-2023 [ds3085]

The project lead for the collection of this data was Carrington Hilson. Elk (1 adult female) were captured and equipped with GPS collars (Lotek Iridium) transmitting data from 2022-2023. The Shamrock 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 1-7 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 1 elk, including 1 annual home range sequence, 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. 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 - Sherwood - 2022-2023 [ds3086]

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 2022-2023. The Sherwood 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 1-7 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 2 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 then 27 hours. 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 - Sultan - 2022-2023 [ds3087]

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 2022-2023. The Sultan 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 1-7 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 2 annual home range sequence, 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. 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 - Wilson - 2022-2023 [ds3088]

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 2022-2023. The Wilson 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 1-7 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 2 annual home range sequence, 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 then 27 hours. 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.
Crotch's Bumble Bee Range - CDFW [ds3095]

Range polygons may include areas not currently occupied by a species and, conversely, may omit areas potentially used by a species. The boundary delineations are primarily based on ecoregion subsections (USDA F.S., Ecomap Subsections 2007), watersheds (USGS HUC12) and 10 Kilometer occurrence buffers. The ecoregions subsections and hucs were combined and will heretofore be referred to as "ecohuc"s. Criteria used to delineate range boundaries: 1. Select all occupied ecohucs. 2. Buffer species occurrences by 10 Kilometers (per maximum buffer distance suggested by scientific literature). 3. If occurrence buffer extends outside a selected subsection, expand subsection boundary to incorporate buffer or ecohuc after assessing vegetational characteristics with subject matter experts. 4. If non-selected subsection is surrounded by selected subsections, incorporate non-selected subsections into species range. 5. Clip species range by California State boundary. 6. Merge ecoregion subsections to create a seamless species range polygon. EcomapSubsections 2007 - Metadata The Ecomap Subsections feature class contains ecological subsection polygons attributed with subsection names and descriptions. The EcomapSubsections 2007 data set describes the ecological subsections within the conterminous United States. It contains regional geographic delineations for analysis of ecological relationships across ecological units. ECOMAP is the term used for a USDA Forest Service initiative to map ecological units and encourage their use in ecosystem-based approaches to forest land conservation and management. This is a collaborative effort with many partners. It is coordinated at the national and regional levels by USDA Forest Service staff and implemented in cooperation with State forestry agencies and others. ECOMAP mapping criteria are outlined in the National Hierarchical Framework of Ecological Units ([https://www.fs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb5286434.pdf]). The framework systematically divides the country into progressively smaller areas of land and water that have similar physical and biological characteristics and ecological processes. Note: The "EcomapSubSections_2007" was downloaded from the [USDA Forest Service Clearing House] website on January 17, 2023.
Western Bumble Bee Historic Range - CDFW [ds3096]

Range polygons may include areas not currently occupied by a species and, conversely, may omit areas potentially used by a species. The boundary delineations are primarily based on ecoregion subsections (USDA F.S., Ecomap Subsections 2007), watersheds (USGS HUC12) and 10 Kilometer occurrence buffers. The ecoregions subsections and hucs were combined and will heretofore be referred to as "ecohuc"s. Criteria used to delineate range boundaries: 1. Select all occupied ecohucs. 2. Buffer species occurrences by 10 Kilometers (per maximum buffer distance suggested by scientific literature). 3. If occurrence buffer extends outside a selected subsection, expand subsection boundary to incorporate buffer or ecohuc after assessing vegetational characteristics with subject matter experts. 4. If non-selected subsection is surrounded by selected subsections, incorporate non-selected subsections into species range. 5. Clip species range by California State boundary. 6. Merge ecoregion subsections to create a seamless species range polygon. EcomapSubsections 2007 - Metadata The Ecomap Subsections feature class contains ecological subsection polygons attributed with subsection names and descriptions. The EcomapSubsections 2007 data set describes the ecological subsections within the conterminous United States. It contains regional geographic delineations for analysis of ecological relationships across ecological units. ECOMAP is the term used for a USDA Forest Service initiative to map ecological units and encourage their use in ecosystem-based approaches to forest land conservation and management. This is a collaborative effort with many partners. It is coordinated at the national and regional levels by USDA Forest Service staff and implemented in cooperation with State forestry agencies and others. ECOMAP mapping criteria are outlined in the National Hierarchical Framework of Ecological Units ([https://www.fs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb5286434.pdf]). The framework systematically divides the country into progressively smaller areas of land and water that have similar physical and biological characteristics and ecological processes. Note: The "EcomapSubSections_2007" was downloaded from the [USDA Forest Service Clearing House] website on January 17, 2023.
Electric Load Serving Entities (IOU & POU)

Data compiled from California Energy Commission staff from georeferenced electric territory maps and the United States Department of Homeland Security, Homeland Infrastructure Foundation-Level Data (HIFILD), https://hifld-geoplatform.opendata.arcgis.com/datasets/geoplatform::electric-retail-service-territories-2/about Boundaries are approximate, for absolute territory information, contact the appropriate load serving entity. For more information on California Load Serving Entities visit this website: [https://www.energy.ca.gov/data-reports/energy-almanac/california-electricity-data/electric-load-serving-entities-lses]
Electric Load Serving Entities (Other)

Data compiled from California Energy Commission staff from georeferenced electric territory maps and the United States Department of Homeland Security, Homeland Infrastructure Foundation-Level Data (HIFILD), https://hifld-geoplatform.opendata.arcgis.com/datasets/geoplatform::electric-retail-service-territories-2/about Community Choice Aggregation information provided by Cal-CCA. Boundaries are approximate, for absolute territory information, contact the appropriate load serving entity. Not all electric load serving entities are represented, if you have information on missing territory locations, please contact [GIS@energy.ca.gov]. For more information on California Load Serving Entities visit this website: [https://www.energy.ca.gov/data-reports/energy-almanac/california-electricity-data/electric-load-serving-entities-lses]
Medium and Heavy Duty Infrastructure

Medium- and heavy-duty (MDHD) zero-emission vehicle (ZEV) hydrogen refueling and charging station data was collected from the following agencies: California Air Resources Board (CARB), California Energy Commission (CEC), CALSTART Inc., California State Transportation Agency (CalSTA), California Department of Transportation (Caltrans), California Transportation Commission (CTC) and San Diego Gas & Electric (SDGE). “Chargers” (charging): Typically high-powered (150 kW or more) direct current fast chargers (DCFCs) for simultaneous charging at each location. “Dispensers” (hydrogen): Typically 700-bar dispensers for simultaneous refueling at each location. “Nozzles” (both charging/hydrogen): Connector that latches to the ZEV for charging or refueling. Following data fields are included: * Charging or Hydrogen: Whether the station is classified as charging or hydrogen * Charger or Dispenser Count: Number of chargers for DCFC and number of dispensers for hydrogen * Nozzle Count: Number of nozzles * Address: Location of the station * Latitude * Longitude * Funding Agencies: Agency/agencies that have provided funding for building the stations
Vegetation - Modoc Plateau - Shinn, Likely, and Snowstorm Mountains - 2020 [ds2877]

Under contract to the California Department of Fish and Wildlife (CDFW), The Geographical Information Center (GIC) was tasked with creating a fine-scale vegetation and land use map of portions of the Modoc Plateau in northeastern California. The mapping effort was done in a two phases. The first phase started in 2016 and covered the ecoregion subsections named Cottonwood-Skedaddle Mountains, Likely Mountain, and the eastern portion of Eagle Lake-Observation Peak (Miles and Goudey 1997) which covered nearly 1.1 million acres. The second phase began in 2018 and covered the ecoregion subsections named Devil’s Garden and Adin Mountains, which covered an additional 866,228 acres. This map was produced during phase one of the project and covers approximately 1,091,702 acres in eastern Lassen and southern Modoc counties. The vegetation map followed guidelines set forth by the National Vegetation Classification System (NVCS) and A Manual of California Vegetation (MCV). It is an Alliance level map overall, with photo-interpreters attempting to map to the more specific Association level when they were confident to go to that level of detail. The GIC used 2016 NAIP imagery for mapping. Accuracy assessments were performed in 2018 and 2020. The minimum mapping unit (MMU) varies by vegetation type. For standard vegetation polygons the MMU is 1 acre. For wetland and riparian areas, the MMU is 0.25 acres. Polygons on the border of the mapping boundary did not have a MMU. For Agriculture and Urban areas, the MMU is 1 acre For Water, the MMU is 1 acre (with the exception of small earthen dams which went down to .25 acres). More information can be found in the project report, which is bundled with the vegetation map published for BIOS here: https://filelib.wildlife.ca.gov/Public/BDB/GIS/BIOS/Public_Datasets/2800_2899/ds2877.zip