| SBCSDE.SDE.assessor_parcels | |
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Data format: SDE Feature Class File or table name: SBCSDE.SDE.assessor_parcels Coordinate system: Lambert Conformal Conic Theme keywords: Assessor Parcels, assessor parcel cadastral |
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Abstract:
This feature class is the ongoing repository for the assessor's cadastral dataset of Santa Barbara County. |
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Metadata elements shown with blue text are defined in the Federal Geographic Data Committee's (FGDC) Content Standard for Digital Geospatial Metadata (CSDGM). Elements shown with green text are defined in the ESRI Profile of the CSDGM. Elements shown with a green asterisk (*) will be automatically updated by ArcCatalog. ArcCatalog adds hints indicating which FGDC elements are mandatory; these are shown with gray text.
This feature class is the ongoing repository for the assessor's cadastral dataset of Santa Barbara County.
This dataset was originally completed in December of 1999. This allowed users for the first time to work with a seamless county-wide parcel layer, populated by assessor's information. As such it has been of enormous value not only for various county operations but also to a large number of public and private entities. Land ownership boundaries are a fundamental dataset of administrative functions.
At this time, January of 2008, this feature class is being updated on a monthly basis with changes to the cadastral fabric. This feature class is then used as the basis of a join to create "Parcel_layers_xxxx_xxxx" on the E$ drive in the subdirectory Parcels (AS), where the x's represent the year, month and day of the last update.
publication date
None.
The County Clerk-Recorder-Assessor's Mapping Division.
From a textual standpoint the accuracy of the Assessor's Parcel Number is extremely high. This is due to its derivation from the Assessor's Property System whereby the assigned numbers have a one-to-one relationship with a property description. In very rare instances a number may not be on the proper polygon it references. Each iteration of the feature class' apn field is tested programmatically in FoxPro to ensure that this one-to-one relationship persists from the APS data to this feature class.
This is a text field that references the "level" of the unit, if necessary, of a condominium, or simply references the parcel as being part of the ground fabric. Its accuracy is very high, as it is worked on extensively throughout the updating process and is simple to review for accuracy and completeness.
The ground layer of this feature class was cleaned by the creation and verification of a topology in June of 2007. All errors of overlaps and gaps between polygons were corrected at that time. It is projected that this topology will be verified on an annual basis. At any one time throughout the year, in the vicinity of newly created or modified parcels, there may be slight errors in the topological integrity, although every effort is made to maintain the highest level of accuracy during all phases of layer modifications.
Due to the nature of its construction the assessor's cadastral dataset has varying degrees of positional precision. It is useful to distinguish between positional accuracy and positional precision. In our feature class, the former refers to the relative accuracy of a given group of spatially related parcel polygons. In other words, for any given polygon, are the neighboring polygons in a proper or accurate relationship spatially with our subject polygon? Subjectively we find that our positional accuracy is good to excellent. On the other hand, positional precision refers to an actual ground location and how well any determinable cadastral point in our dataset is related to this established ground location. As stated previously, this will vary depending on its general location. In those areas which were initially spatially referenced by the Flood Control Topo Map Sets, which were the areas of Santa Barbara city, the Goleta valley, the Santa Ynez valley, and the Santa Maria valley, we consistently find a positional horizontal error of between 3 and 6 feet. The lower figure would be within the city blocks themselves, and the higher figure in the areas outside the numbered orthogonal blocks. Outside of this control set, the nature of the precision may be quite varied. In the unpopulated areas without the control of the Knopf GPS road set, there may be variance of more than 100 feet. For the majority of the populated areas, any horizontal positional precision would be between these general values, and more closer to the lower side given a reasonable distance and tie-in to the Knopf GPS road set. Ultimately it must be remembered that for many of the more antique legal descriptions that might reference, say, a rancho line, that a precise location of any given cadastral point is by its nature an abstraction unless referenced by a modern record of survey, and even then there may be serious discrepancies in the various surveys that are available. The southern Tepusquet Rd area is a prime example, where it would take a survey and the signed acquiescence of all of the affected property owners to truly call that area spatially precise in cadastral terms.
This is not an attribute of this feature class, there are no "Z" values.
Dataset copied.
Dataset copied.
Metadata imported.
Metadata imported.
Dataset copied.
Dataset moved.
Metadata imported.
The key designator of a parcel polygon
a key descriptor for the tax parcel
the base level fabric that is seamless over the county
Parcelized Right-of-Way to county
Parcelized Right-of-Way to city
Feature geometry.
ESRI
Internal feature number.
ESRI
Feature geometry.
ESRI
The key non-spatial attributes are the Assessor's Parcel Number (APN) which is the designator for the assessment bill, and the layer, which allows a more complex spatial relationship for display purposes, showing the condominium unit floor, or the generalized footprint of a mobile home, for instance. The Assessor roll information is joined to into this shape file creating additional non-spacial attributes. there are tables provided with the shape file that explain the codes provided in this data.