AndreaBozzo/ceres-open-data-index huggingface dataset:
i03 Proposition1 Funding Areas

<span style='font-family:&quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, sans-serif; font-size:16px;'>This data depicts California Proposition 1 Funding Area boundaries as defined by Water Code §79744, which states, &quot;(a) Of the funds authorized by Section 79740, five hundred ten million dollars ($510,000,000) shall be allocated to the hydrologic regions as identified in the California Water Plan in accordance with this section. For the South Coast hydrologic region, the department shall establish three funding areas that reflect the watersheds of San Diego County and southern Orange County (designated as the San Diego subregion), the Santa Ana River watershed (designated as the Santa Ana subregion), and the Los Angeles and Ventura County watersheds (designated as the Los Angeles subregion), and shall allocate funds to those areas in accordance with this subdivision. The North and South Lahontan hydrologic regions shall be treated as one area for the purpose of allocating funds. For purposes of this subdivision, the Sacramento River hydrologic region does not include the Delta. For purposes of this subdivision, the Mountain Counties Overlay is not eligible for funds from the Sacramento River hydrologic region or the San Joaquin River hydrologic region. Multiple integrated regional water management plans may be recognized in each of the areas allocated funding.&quot; Key differences between the old and new P1 FAs data set (original/proposed data set, respectively): 1. Line-work along the coastline formerly excluded much detail (bays, inlets, piers, lagoons, etc.); the new proposed dataset more closely follows the i03_Hydrologic_Regions data set. Hence, this data set includes more line detail along the coastline. 2. Line-work forming the P1 FAs between the Southwest portion of the San Joaquin River funding area and Northwest portion of the Tulare/Kern funding area was inconsistent between the two data sets. This data set corrects this notable discrepancy.</span>

Tags: boundaries, boundary, california, california-department-of-water-resources, dwr, dwr-gis-atlas, funding-areas, funds, prop-1, proposition-1, water-code-79744
Organization: State of California
Camera Trap Survey - Terrestrial Species Stressor Monitoring [ds2826]

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Camera traps were deployed at 320 sites across the Mojave Desert ecoregion and 265 sites across the Great Valley ecoregion between March and July of 2016 and 2017. At each survey location, a Reconyx PC900 camera trap was cable-locked onto a T-post that was securely placed in the ground and baited with a 1-kg salt lick, 500 ml of oatmeal-peanut butter mixture, and 150 g of fishy cat food. Cameras were programmed to take three photos at each trigger event with a delay of one second between trigger events. Each camera was deployed for an average of 34 days at sites in the Mojave Desert ecoregion and 29 days at sites in the Great Valley ecoregion. </SPAN></P><P><SPAN>Photos collected were reviewed to identify observed animals to the species-level, and multi-species hierarchical occupancy models were used to estimate 1) species-specific probabilities of occupancy, 2) the richness of terrestrial mammal species weighing &gt;0.5kg, and 3) community and species-specific responses to the different ecological covariates. Each 24-hr period was treated as a repeat survey at a particular camera, where a '1' indicated species x was photographed at camera y on trap day z and a '0' indicated that it was not. A species' probability of occupancy (i.e., the probability a species used the area surrounding a camera trap during our survey) was assumed to be influenced by ecological covariates, such as the presence of an artificial water catchment, precipitation, and temperature in the Mojave Desert ecoregion, or water availability, temperature, and natural vegetation cover in the Great Valley ecoregion. A species' probability of detection (i.e., the probability a species was photographed if present) was assumed to be influenced by ecological covariates, such as human disturbance and precipitation. </SPAN></P></DIV></DIV></DIV>

Tags: amphibian, auth_cdfw, bat, biodiversity, bird, california, california-department-of-fish-and-wildlife, california-natural-resources-agency, camera, camera-trap-survey, caopendata, cdfw, central-valley, drought, ds2826_20190626_wm, environment, great-valley, mojave-desert, reptile, terrestrial-species-stressor-monitoring, tsm, vegetation
Organization: State of California
Jurisdictional Peaker Power Plants

<div style='font-family: inherit;'><div style='font-family: inherit;'><font size='4' style='font-family: inherit;'>2001 California Emergency Siting Peaker Power Plant Permitting</font></div></div><div style='font-family: inherit;'><br /></div><div style='font-family: inherit;'>In 2001, Governor Davis identified a goal of bringing 1,000 megawatts of new power plants to meet the electricity needs during peak demand periods. Typically these are simple-cycle power plants that can be constructed in a relatively small area, do not require water supplies for cooling, and can readily be connected to the existing transmission and natural gas system. The Governor directed the Energy Commission to use its emergency power plant permitting authority under Public Resources Code 25705 to permit new peaking and renewable power plants that could be online by September 30, 2001.<br /></div><div style='font-family: inherit;'><br /></div><div style='font-family: inherit;'>For more information about Peaker Projects contact:</div><div style='font-family: inherit;'>Joe Douglas</div><div style='font-family: inherit;'>Compliance Project Manager</div><div style='font-family: inherit;'>STEP Division</div><div style='font-family: inherit;'>916-653-4677</div><div style='font-family: inherit;'>Joe.Douglas@energy.ca.gov</div><div style='font-family: inherit;'><br /></div>

Tags: california-energy-commission, california-natural-resources-agency, caopendata, map, natural-gas, pdf, power-plant, step
Organization: State of California
Utility Solar Generation by Type and County: 2024

<p>Solar electrical generation data is reported for commercial power plants that<br />have a nameplate capacity of 1 MW or more. San Bernardino and Riverside<br />county had solar thermal in addition to solar photovoltaic electric generation.<br />Data originates from the California Energy Commission, and is classified using<br />the Jenk’s Natural Break’s method. Projection: NAD 1983 California (Teale)<br />Albers. Data is for 2024 and is current as of June 20, 2025. For more<br />information, contact John Hingtgen at john.hingtgen@energy.ca.gov.</p>

Tags: california-energy-commission, california-natural-resources-agency, caopendata, ead, pdf
Organization: State of California
Vegetation - Suisun Marsh - 2000 [ds161]

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This vegetation mapping project of Suisun Marsh blends ground-based classification, aerial photo interpretation, and GIS editing and processing. The method is based on the development of a quantitative vegetation classification, which is used to describe the vegetation map units of the marsh. The classification is defined to meet the specifications of the National and State standards for vegetation classification, but is related through a cross-walking table to other standard classifications in use locally or statewide ( http://www.nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=24570 ).</SPAN></P></DIV></DIV></DIV>

Tags: auth_cdfw, california-department-of-fish-and-wildlife, california-natural-resources-agency, caopendata, cdfw, distribution, ds0161_20140822_wm, habitat-attributes, inventory, management, monitoring, planning, special-status-species, trent, vegetation
Organization: State of California
Natural Communities Commonly Associated with Groundwater

The Natural Communities dataset is a compilation of 48 publicly available State and federal agency datasets that map vegetation, wetlands, springs, and seeps in California. A working group comprised of DWR, the California Department of Fish and Wildlife (CDFW), and The Nature Conservancy (TNC) reviewed the compiled dataset and conducted a screening process to exclude vegetation and wetland types less likely to be associated with groundwater and retain types commonly associated with groundwater, based on criteria described in Klausmeyer et al., 2018. 

Two habitat classes are included in the Natural Communities dataset: (1) wetland features commonly associated with the surface expression of groundwater under natural, unmodified conditions; and (2) vegetation types commonly associated with the sub-surface presence of groundwater (phreatophytes).

The data included in the Natural Communities dataset do not represent DWRs determination of a GDE. However, the Natural Communities dataset can be used by GSAs as a starting point when approaching the task of identifying GDEs within a groundwater basin.

**Reference**
Klausmeyer, K., Howard J., Keeler-Wolf T., Davis-Fadtke K., Hull R., and Lyons A. (2018). Mapping Indicators of Groundwater dependent ecosystems in California

Tags: california-department-of-water-resources, ecosystems, groundwater, habitat, sgma, vegetation, vegetation-mapping, wetland, wetlands
Organization: State of California
Southern Alligator Lizard Habitat Model for NSNF Connectivity - CDFW [ds1051]

The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al. 2006). Species occurrence points were primarily obtained from CNDDB (California Natural Diversity Database) and other CDFW sources, GBIF (Global Biodiversity Information Facility), PRBO (Point Blue Conservation Science) and Arctos museum databases. Vegetation, distance to water, elevation, and bioclimatic variables (Franklin et al. 2013) were used as predictor variables. The models were run at 270 m spatial resolution with five replications using cross-validation as a method of sample evaluation. Cross-validation involved the partitioning of the sample data into n subsets, fitting the models to n-1subsets, and testing the model on the one subset not used in fitting the model. Initial model runs showed that our models converged around 2,000 iterations and for this reason we ran all models with 2,500 maximum iterations. Maxent was implemented in R using the ‘dismo''package (Hijmans et al. 2011). Model evaluation was carried out using the ‘PresenceAbsence''package in R (Freeman and Moisen 2008). We used AUC as a metric to evaluate model performance. The package also computes threshold values using several accuracy metrics to translate predicted probability maps into binary suitable and unsuitable habitats. We selected the MeanProb, a threshold set based on the mean predicted probability of species occurrences. The output from Maxent are grid datasets in a multiband ‘tif''format with one band for each replication. We averaged the five replicated maps and created a mean grid for each species. The grid was then symbolized to represent low (threshold-50), medium (50-75) and high (75-100) habitat suitability, with pixel values that are below the threshold excluded. Models were reviewed by CDFW species experts; please review the use limitations.For more information see the project report at [https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=85358].

Tags: auth_cdfw, california-department-of-fish-and-wildlife, california-natural-resources-agency, caopendata, cdfw, cn-southern-alligator-lizard, connectivity-modeling, ds1051_20141006_wm, habitat-modeling, reptile, sn-elgaria-multicarinata
Organization: State of California
2023 FTB EITC Summary of CA Residents Year Comparison

Produced by the Economic & Statistical Research Bureau, year-end tabulations of tax filings statistics for the Earned Income Tax Credit, (EITC), Young Child Tax Credit (YCTC) and Foster Youth Tax Credit (FYTC) provide credit use by county, preparer type, credit amount allowed number of dependents and a many other useful cross-sections.

Tags: california-franchise-tax-board, comparison, eitc, ftb, fytc, report, yctc
Organization: State of California
Utility Solar Capacity and Generation by Type and County: 2022

<div>Energy data is collected for power plants that have a nameplate capacity of 1 MW or more. Counties that are gray had no utility-scale solar capacity. Data originates from the California Energy Commission, and is classified using the Jenk’s Natural Break’s method. Projection: NAD 1983 California (Teale) Albers. Data is for 2022 and is current as of August 7, 2023. For more information, contact Gordon Huang at gordon.huang@energy.ca.gov or John Hingtgen at john.hingtgen@energy.ca.gov.</div>

Tags: california-energy-commission, california-natural-resources-agency, ead
Organization: State of California
Sierra Meadows Project [ds4]

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Recognizing Montane Meadows and Quaking Aspen communities are a rare and valuable resource to plant and animal species in the Sierra Nevada, this project represents the beginning of a monitoring strategy for the conservation management of these ecosystems. The projects goals and objectives are to develop an accurate inventory of these systems, including high-resolution mapping and classification of community types, and surveys of selected terrestrial and aquatic animal species which depend on them. Other inventory related products include 360° photography, online survey reports and dynamic maps. In addition, refinements to electronic data collection tools and applications are provided to enhance future assessment programs.</SPAN></P></DIV></DIV></DIV>

Tags: amphibian, auth_cdfw, bird, california-department-of-fish-and-wildlife, california-natural-resources-agency, caopendata, cdfw, distribution, ds0004_20040402_wm, habitat, habitat-attributes, inventory, mammal, management, monitoring, multi-species, plant, sample, special-status-species
Organization: State of California
Terrestrial Irreplaceability Summary - ACE [ds2715]

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN><SPAN>For more information, see the Terrestrial Endemic Species Index Factsheet at </SPAN><A href="https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=150816" STYLE="text-decoration:underline;"><SPAN>https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=150816</SPAN></A><SPAN>. </SPAN></SPAN></P><P><SPAN>The user can view a list of species potentially present in each hexagon in the ACE online map viewer </SPAN><A href="https://apps.wildlife.ca.gov/ace/" STYLE="text-decoration:underline;"><SPAN>https://apps.wildlife.ca.gov/ace/</SPAN></A><SPAN>. Note that the names of some rare or endemic species, such as those at risk of over-collection, have been suppressed from the list of species names per hexagon, but are still included in the species counts. </SPAN></P><P><SPAN><SPAN>The California Department of Fish and Wildlife’s (CDFW) Areas of Conservation Emphasis (ACE) is a compilation and analysis of the best-available statewide spatial information in California on biodiversity, rarity and endemism, harvested species, significant habitats, connectivity and wildlife movement, climate vulnerability, climate refugia, and other relevant data (e.g., other conservation priorities such as those identified in the State Wildlife Action Plan (SWAP), stressors, land ownership). ACE addresses both terrestrial and aquatic data. The ACE model combines and analyzes terrestrial information in a 2.5 square mile hexagon grid and aquatic information at the HUC12 watershed level across the state to produce a series of maps for use in non-regulatory evaluation of conservation priorities in California. The model addresses as many of CDFWs statewide conservation and recreational mandates as feasible using high quality data sources. High value areas statewide and in each USDA Ecoregion were identified. The ACE maps and data can be viewed in the ACE online map viewer, or downloaded for use in ArcGIS. For more detailed information see </SPAN></SPAN><A href="https://www.wildlife.ca.gov/Data/Analysis/ACE" STYLE="text-decoration:underline;"><SPAN><SPAN>https://www.wildlife.ca.gov/Data/Analysis/ACE</SPAN></SPAN></A><SPAN> and </SPAN><A href="https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=24326" STYLE="text-decoration:underline;"><SPAN><SPAN>https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=24326</SPAN></SPAN></A><SPAN><SPAN>.</SPAN></SPAN></P></DIV></DIV></DIV>

Tags: ace, amphibian, auth_cdfw, biodiversity, bird, california-department-of-fish-and-wildlife, california-natural-resources-agency, caopendata, cdfw, ds2715_20200221_wm, endemic, game, mammal, native, plant, rare, rare-natural-community, rarity, reptile, richness, riparian, sensitive-haibtat, terrestrial, wetland
Organization: State of California
i04 CIMIS Reference Evapotranspiration Zones v1999

<div style='text-align:Left;'><p><span style='font-family:&quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, sans-serif; font-size:16px;'>The ETo Zones Map allows users to view the grass-reference evapotranspiration (ETo) Zones for the State of California. The map was developed by DWR and UC Davis in 1999 and divides the State into 18 zones based on long-term monthly average ETo. The ETo values were calculated using data from various data sources, including CIMIS weather stations that had at least five years of archived data. This dataset is the version from 1999.</span><br /></p></div>

Tags: 1999, atmosphere, biota, california, california-department-of-water-resources, climatology, dwr, dwr-gis-atlas, eto, evapotranspiration, meteorology, weather, zones
Organization: State of California
Clean Transportation Program

<div>Clean Transportation Program Data 2022. The Clean Transportation Program (also known as Alternative and Renewable Fuel and Vehicle Technology Program) invests up to $100 million annually in a broad portfolio of transportation and fuel transportation projects throughout the state. The Energy Commission leverages public and private investments to support adoption of cleaner transportation powered by alternative and renewable fuels. </div><div><br /></div><div>The program plays an important role in achieving California’s ambitious goals on climate change, petroleum reduction, and adoption of zero-emission vehicles, as well as efforts to reach air quality standards. The program also supports the state’s sustainable, long-term economic development.</div><div><br /></div><div>Data within this application was last updated August 2024.</div><div><br /></div><div>For more information on the Clean Transportation Program, visit:</div><div><a href='https://www.energy.ca.gov/programs-and-topics/programs/clean-transportation-program' target='_blank' rel='nofollow ugc noopener noreferrer'>https://www.energy.ca.gov/programs-and-topics/programs/clean-transportation-program</a><br /></div><div><br /></div>

Tags: california-energy-commission, california-natural-resources-agency, caopendata, clean-transportation-program, ctp, ftd
Organization: State of California
Elk Home Range - American - 2005-2008, 2015-2017 [ds3111]

<DIV STYLE="text-align:Left;"><DIV><DIV><P STYLE="margin:0 0 11 0;"><SPAN><SPAN>The project lead for the collection of this data was Bob Stafford. Elk (9 adult females, 5 adult males) from the American herd were captured and equipped with Lotek GPS collars (</SPAN></SPAN><SPAN><SPAN>LifeCycle 800 GlobalStar/ GPS3300L, Lotek Wireless, Newmarket, Ontario, Canada</SPAN></SPAN><SPAN><SPAN>) and ATS GPS collars (G2000, Advanced Telemetry Systems, Isanti, Minnesota, USA), transmitting data from 2005-2008 and 2015-2017. The study area was within the La Panza Elk Management Unit, northeast of State Highway 166 and largely residing within Carrizo Plain National Monument and Carrizo Plains Ecological Reserve. The American herd contains short distance, elevation-based movements likely due to seasonal habitat conditions, but this herd does not migrate between traditional summer and winter seasonal ranges. Instead, the herd displays a residential pattern, slowly moving up or down elevational gradients. 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 at 11-13 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 elk 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. </SPAN></SPAN></P><P STYLE="margin:0 0 11 0;"><SPAN><SPAN>The methodology used for this analysis allowed for the mapping of the herd’s annual range based on a small sample. Brownian Bridge Movement Models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data from 11 elk in total, including 20 year-long sequences, location, date, time, and average location error as inputs in Migration Mapper to assess annual range. Annual range BBMMs were produced at a spatial resolution of 50 m using a sequential fix interval of less than 27 hours and a fixed motion variance of 1000. Population-level annual range designations for this herd may expand with a larger sample, filling in some of the gaps between high-use annual range polygons in the map. Annual range is visualized as the 50</SPAN></SPAN><SPAN><SPAN>th</SPAN></SPAN><SPAN><SPAN> percentile contour (high use) and the 99</SPAN></SPAN><SPAN><SPAN>th</SPAN></SPAN><SPAN> percentile contour of the year-round utilization distribution.</SPAN></P></DIV></DIV></DIV>

Tags: annual-range, brownian-bridge-movement-model, california, california-department-of-fish-and-wildlife, cdfw, cervus-canadensis, connectivity, elk, gps, home-range, kern, migration-mapper, san-luis-obispo, telemetry
Organization: State of California
Utility Renewable Generation by End Use and County: 2019

<p style='box-sizing:border-box; margin-top:0px; margin-bottom:12px; max-width:100%; font-family:&quot;Avenir Next&quot;, &quot;Avenir Next&quot;; font-size:16px;'>Renewable Generation as a Fraction of Electricity End Use by County</p><span style='font-family:&quot;Avenir Next&quot;, &quot;Avenir Next&quot;; font-size:16px;'>Map of Renewable Generation as a Fraction of Electricity End Use by County.</span>

Tags: california-energy-commission, california-natural-resources-agency, caopendata, ead
Organization: State of California