This map is designated as Final.

Land-Use Data Quality Control

Every 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 Legendspecific 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 photointerpretation, 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 datasets 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 2006 Alameda 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 imagery 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 Central District. Quality control procedures were performed jointly by staff at DWR’s DPLA headquarters and Central District, under the supervision of Ed Morris, Senior Land and Water Use Supervisor. 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 Alameda County conducted by the California Department of Water Resources, Central District Office staff. Field survey boundaries data was developed using: 1. The county was surveyed with a combination of 2005 one meter and 2006 two meter NAIP imagery. 2. The 2005 images were used in the spring of 2006 to develop the land use field boundary lines that would be used for the summer survey. The 2006 imagery was used for identification in the field and to edit any boundary line changes from the 2005 imagery. 3. These images and land use boundaries were copied onto laptop computers that were used as the field collection tools. The staff took these laptops in the field and virtually all areas were visited to positively identify the land use. The site visits occurred from June through September 2006. Land use codes were digitized directly into the laptop computers using AUTOCAD (and a standardized digitizing process) any land use boundaries changes were noted and corrected back in the office. 4. After quality control/assurance procedures were completed on each file (DWG), the data was finalized for the summer survey. Important points about using this data set: 1. The land use boundaries were drawn on-screen using orthorectified imagery. 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 created as a "snapshot" in the summer, and further improved by the addition of spring crops found through the use of satellite imagery. There still could be fields where there were crops grown before or after the field survey. The surveyor may not have been able to detect them from the field or the photographs, and the satellite imagery processing may not have identified the spring crop. Thus, although the data is very accurate for the summer, and probably the spring, it may not be an accurate determination of what was grown in the fields for the whole year. 3. If the data is to be brought into a GIS for analysis of copped (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. Not all land use codes will be represented in the survey. Sources of irrigation water were not identified. 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 12.4 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.