A Development Site (DV), referenced using a Development Site Number, is a property boundary that the Seattle Department of Construction and Inspections (SDCI) uses to apply code standards. A Development Site may overlap with one or more King County tax parcels.Source Data: DPD.DevsitesDefinition Query: Where DEVSITE STATUS IN ('ACTIVE', 'PRESUMED', 'UPDATE') And DEVSITE ID does not begin with 'UN' And DEVSITE ID does not begin with 'WB' And SEATTLE is not equal to 0Symbology Category Expression: var disp_txt = $feature["PRCLID"]; if (Find("RW", disp_txt, 0)>-1) { return "Right-of-Way"; } else { return "Non-Right-of-Way"; }Refresh: Daily

This data layer references data from a high-resolution tree canopy change-detection layer for Seattle, Washington. Tree canopy change was mapped by using remotely sensed data from two time periods (2016 and 2021). Tree canopy was assigned to three classes: 1) no change, 2) gain, and 3) loss. No change represents tree canopy that remained the same from one time period to the next. Gain represents tree canopy that increased or was newly added, from one time period to the next. Loss represents the tree canopy that was removed from one time period to the next. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. Direct comparison was possible because land-cover maps from both time periods were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, _location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction.University of Vermont Spatial Analysis LaboratoryThis dataset consists of City of Seattle Council District areas as they existed in the first comparison year (2016) which cover the following tree canopy categories:Existing tree canopy percentPossible tree canopy - vegetation percentRelative percent changeAbsolute percent changeFor more information, please see the 2021 Tree Canopy Assessment.

This data layer references data from a high-resolution tree canopy change-detection layer for Seattle, Washington. Tree canopy change was mapped by using remotely sensed data from two time periods (2016 and 2021). Tree canopy was assigned to three classes: 1) no change, 2) gain, and 3) loss. No change represents tree canopy that remained the same from one time period to the next. Gain represents tree canopy that increased or was newly added, from one time period to the next. Loss represents the tree canopy that was removed from one time period to the next. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. Direct comparison was possible because land-cover maps from both time periods were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction.University of Vermont Spatial Analysis LaboratoryThis dataset consists of City of Seattle Council District areas as they existed in the first comparison year (2016) which cover the following tree canopy categories:Existing tree canopy percentPossible tree canopy - vegetation percentRelative percent changeAbsolute percent changeFor more information, please see the 2021 Tree Canopy Assessment.

description: https://gisrevprxy.seattle.gov/arcgis/rest/services/ext/WM_CityGISLayers/MapServer/15; abstract: https://gisrevprxy.seattle.gov/arcgis/rest/services/ext/WM_CityGISLayers/MapServer/15

Please Note: Community Reporting Areas (CRA) have been updated to follow the 2020 census tract lines which resulted in minor changes to some boundary conditions. They have also been extended into water areas to allow the assignment of CRAs to overwater housing and businesses. To exclude the water polygons from a map choose the filter, water=0.Community reporting areas (CRAs) are designed to address a gap that existed in city geography. The task of reporting citywide information at a "community-like level" across all departments was either not undertaken or it was handled in inconsistent ways across departments. The CRA geography provides a "common language" for geographic description of the city for reporting purposes. Therefore, this geography may be used by departments for geographic reporting and tracking purposes, as appropriate. The U.S. Census Bureau census tract geography was chosen as the basis of the CRA geography due to their stability through time and link to widely-used demographic data.The following criteria for a CRA geography were defined for this effort:no overlapping areascomplete coverage of the citysuitable scale to represent neighborhood areas/conditionsreasonably stable over timeconsistent with census geographyrelatively easy to use in a data contextfamiliar system of common place namesrespects neighborhood district geography to the extent possibleThe following existing geographies were reviewed during this effort:neighborhood planning areas (DON)neighborhood districts (DON/CNC/Neighborhood District Councils)city sectors/neighborhood plan implementation areas (DON)urban centers/urban villages (DPD)population sub-areas (DPD)Neighborhood Map Atlas (City Clerk)Census tract geographytopographyvarious other geographic information sources related to neighborhood areas and common place namesThis is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.

Displays citywide address points using TRANSPO.MAFDAP_PV. Differs from TRANSPO.DAP in that it contains address data. Attributes include house number and modifier, directional, street name, and street type. Does not display when zoomed out beyond 1:10,000. Labels are based on the attribute MAF_HSENUMMOD and do not display when zoomed out beyond 1:3,000. ATTRIBUTE INFORMATION: MAILUSECODE: Identifies suitability of MAF address and associated MAFUNIT record(s) for use as a mailing address. This field serves as an indicator whether the address is being utilized in the City's Utility Billing System. If so, it is more likely (but still not guaranteed) to be a valid mailing address. DCLUSTAT - Description of address establishment and validation status related to DCLU business process. Valid values: INITIAL VALUE: SPU-added records are assigned this value upon creation. DRAFT: only DPD-added records are assigned this value upon creation.FIELD VERIFIED: only DPD can assign this value. Indicates that DPD at some point conducted a site visit. This value is not reliably assigned and is not necessarily an indicator of a correct address. CANCELED: only DPD can assign this value. The address was never utilized. RETIRED: DPD or SPU can assign this value. The address may have been utilized for some period of time but was then replaced by a different address for the _location or retired from use completely. DCLUSTATDT - Date of creation or modification of record. SOURCENAME - Descriptive character string identifying agency, department or divisional record source or usage. Valid values: DPD_MAF: Added or modified by DPD CGDB_MAFEDITS: Added or modified by SPUINIT_MAF: The initial record value, likely harvested from King County Assessor data when the MAF/DAP was first implemented.Data refreshed daily.