Subdivision Map features for Stanislaus County

This map is designated as Final.Land-Use Data Quality ControlEvery published digital survey is designated as either ‘Final’, or ‘Provisional’, depending upon its status in a peer review process. Final surveys are peer reviewed with extensive quality control methods to confirm that field attributes reflect the most detailed and specific land-use classification available, following the standard DWR Land Use Legend specific to the survey year. Data sets are considered ‘final’ following the reconciliation of peer review comments and confirmation by the originating Regional Office. During final review, individual polygons are evaluated using a combination of aerial photo interpretation, satellite image multi-spectral data and time series analysis, comparison with other sources of land use data, and general knowledge of land use patterns at the local level.Provisional data sets have been reviewed for conformance with DWR’s published data record format, and for general agreement with other sources of land use trends. Comments based on peer review findings may not be reconciled, and no significant edits or changes are made to the original survey data.The 2010 Stanislaus County land use survey data was developed by the State of California, Department of Water Resources (DWR) through its Division of Integrated Regional Water Management (DIRWM) and Division of Statewide Integrated Water Management (DSIWM). Land use data was gathered and reviewed by DWR staff using extensive field visits, 2009 National Agriculture Imagery Program (NAIP) one-meter aerial photography and Landsat 5 imagery. NAIP imagery from 2010 was used for data review. Land use polygons in agricultural areas were mapped in greater detail than areas of urban or native vegetation. Quality control procedures were performed jointly by staff at DWR’s DSIWM headquarters, under the leadership of Jean Woods, and North Central Region, under the supervision of Kim Rosmaier. This data was developed to aid DWR’s ongoing efforts to monitor land use for the main purpose of determining current and projected water uses. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standards version 2.1, dated March 9, 2016. DWR makes no warranties or guarantees - either expressed or implied - as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov. This data represents a land use survey of central and eastern Stanislaus County. The northern, eastern and southern boundaries are defined by the Stanislaus County boundary. The western extent of the survey area extends to the western edges of the Solyo (U.S.G.S. No. 37121E3) and Howard Ranch (U.S.G.S. No. 37121B1) 7.5’ quadrangles and is also bounded by the western and southern borders of the Copper Mountain (U.S.G.S. No. 37121D3) and Orestimba Peak (U.S.G.S. No. 37121C2) quadrangles. Land use boundaries were developed by updating line work from DWR's 2004 land use survey of Stanislaus County. Boundaries were modified on a quadrangle by quadrangle basis. Roads were delineated using the U.S. Census Bureau's TIGER®(Topologically Integrated Geographic Encoding and Referencing) database as guidelines. Other land use boundaries were adjusted and new fields were added based upon 2009 NAIP imagery. Field boundaries were drawn to depict observable areas of the same crop or other land uses and are not intended to represent legal parcel (ownership) boundaries. In this survey, some areas of creeks and rivers were included within polygons of riparian areas and not delineated separately. The primary field data collection for this survey was conducted between July 2010 and February 2011 by DWR staff from the South Central Region Office who visited each field and noted what was grown at that time. Supplemental field visits took place from April 28 through June 14, 2010 and from July 12 through August 3, 2010 when randomly selected fields were visited by SIWM staff to collect data for mapping crops using Landsat imagery analysis. For field data collection, 2009 NAIP imagery and vector files of land use boundaries were loaded onto laptop computers that, in most cases, were used as the field data collection tools. Some surveyors also used Landsat 5 imagery for the field survey. GPS units connected to the laptops were used to confirm the surveyors’ locations with respect to the fields. Virtually all agricultural fields were visited to positively identify the land use. Land use codes were entered in the field on laptop computers using ESRI ArcMAP software, version 9.3. Some staff took printed aerial photos into the field and wrote directly onto these photo field sheets. Attribute data from photo field sheets were coded and entered back in the office. Any necessary field boundary changes were digitized at the same time. In addition to the identification of crops through the collection of data in the field, a supervised classification of Landsat 5 data was used to identify fields with winter crops. The Landsat images of a selection of fields mapped by surveyors as grain, spinach, lettuce or fallow were reviewed using a time series of Landsat 5 images to confirm that the pattern of vegetation over time was consistent with the expected pattern for these crops. The selected fields were then used to develop spectral signatures for the represented crop categories using ERDAS Imagine and eCognition Developer software. Two Landsat 5 images, March 16, 2010 and April 17, 2010, were selected for identifying winter crops using a maximum likelihood supervised classification. The classified images were used to calculate zonal attributes for fields mapped during the summer survey as field crops, truck crops or fallow. Fields mapped during the survey as winter truck crops or grains were also included. For the fields that were classified as winter crops, a time series of Landsat imagery was reviewed for consistency with the classification results. Fields for which the identified winter crops were confirmed by the review of time series data were added to the shapefile database using the special condition “U”, indicating that they were identified by a method other than having been mapped during the field survey. To identify fields with summer crops that were missed during the field survey, fields identified as fallow were reviewed using 2010 NAIP and Landsat 5 imagery. Where the imagery indicated that crops had been produced, the attributes of these fields were changed to identify them as cropped. They are also labeled with special condition "U". Before final processing, standard quality control procedures were performed jointly by staff at DWR’s North Central Region, and at DSIWM headquarters under the leadership of Jean Woods. Senior Land and Water Use Supervisor. After quality control procedures were completed, the data was finalized. The positional accuracy of the digital line work, which is based upon the orthorectified NAIP imagery, is approximately 6 meters. The land use attribute accuracy for agricultural fields is high, because almost every delineated field was visited by a surveyor. The accuracy is 95 percent because some errors may have occurred. Possible sources of attribute errors are: a) Human error in the identification of crop types, b) Data entry errors.

This shapefile contains tax rate area (TRA) boundaries in Stanislaus County for the specified assessment roll year. Boundary alignment is based on the 2021 county parcel map. A tax rate area (TRA) is a geographic area within the jurisdiction of a unique combination of cities, schools, and revenue districts that utilize the regular city or county assessment roll, per Government Code 54900. Each TRA is assigned a six-digit numeric identifier, referred to as a TRA number. TRA = tax rate area number

Tax rate area boundaries and related data based on changes filed with the Board of Equalization per Government Code 54900 for the specified assessment roll year. The data included in this map is maintained by the California State Board of Equalization and may differ slightly from the data published by other agencies. BOE_TRA layer = tax rate area boundaries and the assigned TRA number for the specified assessment roll year; BOE_Changes layer = boundary changes filed with the Board of Equalization for the specified assessment roll year; Data Table (C##_YYYY) = tax rate area numbers and related districts for the specified assessment roll year

The Stanislaus County river centerlines were derived from digitizing the following data sources: National Hydrography Dataset (NHD), USGS 1:24,000 Topographic Map, 2015 Aerial Imagery. Application: (OES Editor)(PG&E PSPS Event)(Planning and Community Development)Web Map: (OES Editor Map)(PG&E PSPS Event Map)(Planning and Community Development Map)

Analysis of ‘Stanislaus County Land Use Survey 2010’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/3a040ace-b464-46b5-b093-e7562cbcf3e8 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

--- Original source retains full ownership of the source dataset ---

The 1996 Stanislaus County land use survey data set was developed by DWR through its Division of Planning and Local Assistance (DPLA). The data was gathered using aerial photography and extensive field visits, the land use boundaries and attributes were digitized, and the resultant data went through standard quality control procedures before finalizing. The land uses that were gathered were detailed agricultural land uses, and lesser detailed urban and native vegetation land uses. The data was gathered and digitized by staff of DWR’s San Joaquin District. Quality control procedures were performed jointly by staff at DWR’s DPLA headquarters and San Joaquin District. Important Points about Using this Data Set: 1. The land use boundaries were hand drawn directly on USGS quad maps and then digitized. They were drawn to depict observable areas of the same land use. They were not drawn to represent legal parcel (ownership) boundaries, or meant to be used as parcel boundaries. 2. This survey was a "snapshot" in time. The indicated land use attributes of each delineated area (polygon) were based upon what the surveyor saw in the field at that time, and, to an extent possible, whatever additional information the aerial photography might provide. For example, the surveyor might have seen a cropped field in the photograph, and the field visit showed a field of corn, so the field was given a corn attribute. In another field, the photograph might have shown a crop that was golden in color (indicating grain prior to harvest), and the field visit showed newly planted corn. This field would be given an attribute showing a double crop, grain followed by corn. The DWR land use attribute structure allows for up to three crops per delineated area (polygon). In the cases where there were crops grown before the survey took place, the surveyor may or may not have been able to detect them from the field or the photographs. For crops planted after the survey date, the surveyor could not account for these crops. Thus, although the data is very accurate for that point in time, it may not be an accurate determination of what was grown in the fields for the whole year. If the area being surveyed does have double or multicropping systems, it is likely that there are more crops grown than could be surveyed with a "snapshot". 3. If the data is to be brought into a GIS for analysis of cropped (or planted) acreage, two things must be understood: a. The acreage of each field delineated is the gross area of the field. The amount of actual planted and irrigated acreage will always be less than the gross acreage, because of ditches, farm roads, other roads, farmsteads, etc. Thus, a delineated corn field may have a GIS calculated acreage of 40 acres but will have a smaller cropped (or net) acreage, maybe 38 acres. b. Double and multicropping must be taken into account. A delineated field of 40 acres might have been cropped first with grain, then with corn, and coded as such. To estimate actual cropped acres, the two crops are added together (38 acres of grain and 38 acres of corn) which results in a total of 76 acres of net crop (or planted) acres. 4. Water source and irrigation method information were not collected for this survey. 5. Not all land use codes will be represented in the survey.The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standard version 3.4, dated September 2022. DWR makes no warranties or guarantees - either expressed or implied - as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. See the CADWR Land User Viewer (gis.water.ca.gov/app/CADWRLandUseViewer) for the most current contact information. Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov.

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Subdivision Map features for Stanislaus County

This polygon shapefile contains areas of important farmland in Stanislaus County, California for 2010. Important Farmland Maps show the relationship between the quality of soils for agricultural production and the land's use for agricultural, urban, or other purposes. A biennial map update cycle and notation system employed by FMMP captures conversion to urban land while accommodating rotational cycles in agricultural use. The minimum land use mapping unit is 10 acres unless specified. Smaller units of land are incorporated into the surrounding map classifications. In order to most accurately represent the NRCS digital soil survey, soil units of one acre or larger are depicted in Important Farmland Maps. For environmental review purposes, the categories of Prime Farmland, Farmland of Statewide Importance, Unique Farmland, Farmland of Local Importance, and Grazing Land constitute 'agricultural land' (Public Resources Code Section 21060.1). The remaining categories are used for reporting changes in land use as required for FMMP's biennial farmland conversion report. This layer is part of the 2010 California Farmland Mapping and Montoring Project.

Supervisorial Districts for Stanislaus County, CA

Boundaries of the Wendt Ranch Reclmation District, drawn to legal description. Sphere of Influence is coterminous with existing boundaries.(Last updated: 2012)

Trails - Frank Raines (Edits to this layer made during the day will show up the next day)Applications: (Public Inquiry Map Application)Web Map: (Public Inquiry Map)

The National Pipeline Mapping System (NPMS) includes a geographic information system (GIS) dataset containing the location and selected attributes of gas transmission and hazardous liquid pipelines, liquefied natural gas (LNG) plants and breakout tanks (BOT) under jurisdiction of the Pipeline and Hazardous Materials Safety Administration (PHMSA). Effective October 1, 2015, pipeline and LNG plant data is collected annually from pipeline operators as required by 49 CFR §§ 191.29 and 195.61. This metadata is for the national pipeline dataset. There is NPMS pipeline data for all 50 states as well as the District of Columbia and Puerto Rico. The NPMS pipeline dataset contains gas transmission and hazardous liquid pipelines subject to regulations from PHMSA. The NPMS pipeline dataset does not contain gas gathering, gas distribution, or hazardous liquid lines not subject to 49 CFR § 195.61 and can never be used in place of contacting a one call center prior to digging. Distribution of NPMS data in GIS format is handled for PHMSA by the National Repository and is limited to pipeline operators and local, state, tribal, and federal government officials and is subject to data access limitations and agreements. Fulfillments of data requests will include data only for the area of jurisdiction of the person requesting the data (data requests are fulfilled per county/counties, state, or the entire U.S.). Instructions for requesting NPMS data in a GIS format are outlined on the NPMS website at www.npms.phmsa.dot.gov.