ArcGIS REST Services Directory
Home > services > Planning > i15_LandUse_Merced2012 (FeatureServer) > i15_LandUse_Merced2012 API Reference
JSON

Layer: i15_LandUse_Merced2012 (ID: 0)

View In:   ArcGIS Online Map Viewer

Name: i15_LandUse_Merced2012

Display Field: WATERSOURC

Type: Feature Layer

Geometry Type: esriGeometryPolygon

Description: This data represents a land use survey of 2012 Merced County conducted by the California Department of Water Resources, South Central Region Office staff. Land use boundaries were digitized, and land use data was gathered by staff of DWR’s South Central Region Office using extensive field visits and aerial photography. Detailed agricultural land uses, and lesser detailed urban and native vegetation land uses were mapped. Landsat 5 imagery was analyzed prior to the field survey by DRA staff to map fields likely to have winter crops. The land use data went through standard quality control procedures before final processing. Quality control procedures were performed jointly by staff at DWR’s DRA headquarters and South Central Region Office. Land use field boundaries were digitized with ArcGIS 9.3 using 2010 NAIP as the base, and Google Earth were used as reference as well. Agricultural fields were delineated by following actual field boundaries instead of using the centerlines of roads to represent the field borders. Field boundaries were not drawn to represent legal parcel (ownership) boundaries and are not meant to be used as parcel boundaries. Field work for land use surveys occurs primarily during the summer and early fall, so it can be difficult to identify fields where winter crops have been produced during the survey year. To improve the mapping of winter crops, we analyzed Landsat 5 imagery to identify fields with high winter vegetative cover. The identification of these fields was based on an analysis of Landsat 5 imagery. Visual inspection of the Landsat scene displayed in false color infrared was used to select fields with high and low vegetative cover. These fields were used to develop spectral signatures using ERDAS Imagine and eCognition Developer software. The Landsat image was classified using a maximum likelihood supervised classification to label each pixel as vegetated or not vegetated, then the zonal attributes of polygons representing agricultural fields were summarized to identify fields vegetated during the winter. Polygons representing these fields were used on laptop taken to the field to highlight the fields which should be checked closely for winter crop residue. Site visits occurred from July through October 2012. Images and land use boundaries were loaded onto laptop computers that, in most cases, were used as the field data collection tools. GPS units connected to the laptop computers were used to confirm surveyor's location with respect to the fields. Staff took these laptop computers into the field and virtually all the areas were visited to positively identify the land use. Land use codes were digitized 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. The data from the photo field sheets were digitized back in the office. The primary focus of this land use survey is mapping agricultural fields. Urban residences and other urban areas were delineated using aerial photo interpretation. Some urban areas may have been missed. Rural residential land use was delineated by drawing polygons to surround houses and other buildings along with some of the surrounding land. These footprint areas do not represent the entire footprint of urban land. Water source information was not collected for this land use survey. Therefore, the water source has been designated as Unknown. Before final processing, standard quality control procedures were performed jointly by staff at DWR’s South Central Region, and at DRA's headquarters office 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.

Copyright Text: California Department of Water Resources, Division of Regional Assistance (DRA), South Central Region Office, Water Conservation and Land and Water Use Section, and Water Use Efficiency Branch (Sacramento Headquarters).

Default Visibility: true

MaxRecordCount: 1000

Supported Query Formats: JSON, geoJSON, PBF

Min Scale: 0

Max Scale: 0

Supports Advanced Queries: true

Supports Statistics: true

Can Scale Symbols: false

Use Standardized Queries: true

Supports ValidateSQL: true

Supports Calculate: true

Supports Datum Transformation: true

Extent:
Drawing Info: Advanced Query Capabilities:
HasZ: true

HasM: true

Has Attachments: false

HTML Popup Type: esriServerHTMLPopupTypeAsHTMLText

Type ID Field: CLASS1

Fields: Types:
Capabilities: Query

Sync Can Return Changes: false

Is Data Versioned: false

Supports Rollback On Failure: true

Supports ApplyEdits With Global Ids: false

Supports Query With Historic Moment: false

Supports Coordinates Quantization: true

Child Resources:   Field Groups   Contingent Values

Supported Operations:   Query   Query Analytic   Validate SQL   Generate Renderer   Return Updates   Iteminfo   Thumbnail   Metadata   Update Metadata