**IsImpervious field was added to track areas of pervious hard surface. Initial data was brought in from the city's swPerviousSurface feature class, and has been added to since. Gravel that conducts vehicle traffic (parking, driveways, and roadways) is considered impervious.

"Impervious surface means a non-vegetated surface area that either prevents or retards the entry of water into the soil mantle as under natural conditions prior to development. a non-vegetated surface area which causes water to run off the surface in greater quantities or at an increased rate of flow from the flow present under natural conditions prior to development."

Common impervious surfaces include, but are not limited to, roof tops, walkways, patios, driveways, parking lots or stormwater areas, concrete or asphalt paving, gravel roads, packed earthen materials, and oiled, macadam or other surfaces which similarly impede the natural infiltration of stormwater.

Washington Phase II Municipal Stormwater Permit – August 1, 2013

Modified January 16, 2015

Page 69 of 74"

May 2015 stereo photography was used to photogrammetrically evaluate existing planimetric data for selected impervious surface layers compared to current conditions.

Data was modified to reflect signficant change (additions or removal) within the limits of stated map accuracy standards and the limits of what could be interpreted from aerial photography.

Planimetric mapping was compiled to industrry standards using established methodologies, flight altitudes, control and processes to meet or exceed ASPRS Class 1 accuracies for 1"=100' mapping, consistent with existing data sets and past mapping projects. Field checks were not performed.

ATTRIBUTES

Features were assigned attributes for the following:

Surface Type: Parking, Sidewalk, Sidewalk_Bridge, Driveway, Roadway, Roadway_Bridge, Pad and Pool.

Material: Asphalt, Concrete, Grass Pavement, Gravel, Other (applies to footbridges only), Pavement, Pavers, Permeable Pavers, Pervious Concrete, Porous Asphalt, Water,

Impervious surface features updated and developed into final polygons included:

Pad: Permanent concrete or ashpalt impervious pads greater than 100 square feet in area)

Pool: Permanent in-ground swimming pools

Parking and Driveway: Attributed as parking or driveway depending on dominant use. Some gravel areas were identified as parking along paved streets. These areas may or may not be actual parking and should be field verified. Driveways into parking areas were generally included as parking. The disinction between parking, driveway and sidewalks crossing driveways was not always consistent in the existing data. This was not updated or revised unless the feature actually changed.

Sidewalk: Public and private paved or concrete sidewalks were included. Gravel or dirt paths were not included. In many cases the sidewalk attribute was assigned to sidewalks where crossing paved driveways. However, this varies and is not consistent due to the varying methodologies used in existing data. Sidewalk_bridge was assigned to footbridges where part of the sidewalk network.

Roadway: Roads maintained the coding of the existing data sets for obvious roadways as interpreted from the imagery. Verification of public vs. private roads or roads vs. driveways was not performed.

Material type: Pavement and Gravel attributes were determined within limits of interpretation from aerial imagery. In many instances it was difficult to interpret material type and field verification may be required. Pavement was assigned to concrete or asphalt parking, sidewalk, driveways, roadways or pads. Gravel was assigned to unpaved parking, roadway or driveway areas. Gravel pads (areas with no obvious parking or driveway use) or gravel paths were not collected. Water was assigned to all pools. Other was assigned to Sidewalk_bridge features (footbridges).

Field verification of surface type or material was not performed.

GENERAL PROCESS

Prepared by

DAVID C. SMITH & ASSOCIATES, INC.1734 SE Tacoma Street, Portland, Oregon, 97202

http://www.davidsmithmapping.com

info@davidsmithmapping.com

Job #: 2334

Supervising Professionals: Scott Smith, Certified Photogrammetrist, Oregon Professional Photogrammetrist # 38670 RPP; Doug Smith, Certified Photogrammetrist, Oregon Professional Engineer # 16707

Source photography

Camera: UltraCam XP, S/N UC-SXp-CI-10411033 (Bergman Photographic Services, Inc.)

Calibration Date: 12/11/2012 (Factory Calibration)

NOTE: Standard USGS calibration does not apply to digital cameras. USGS certifies the camera manufacture and factory calibration process but does not calibrate individual cameras.

Calibrated Focal Length: 100.5 mm

Date of Photography: 5/29/2015 Approx. Time of Flight: 11:00 a.m. to 1:00 p.m., Pacific Daylight Time

Flight specifications

0.3' pixel Ground Sample Distance(maximium)

Nominal Flight Altitude: 4,600' Above Ground Level

Nominal Photo Scale: 1058 ft/inch (1:12700)

Control

Datum: NAD '83/'2011, U.S. Survey Feet

Projection: LAMBERT CONICAL, Washington, SOUTH ZONE

Ground Control: Air-borne GPS control was acquired and tied to new City of Olympia control. Existing City ground control was also used to provide datum consistency. New premarks and survey points were established.

Aerotriangulation Solution: Aerotriangulation was performed to industry standards as supported by photo scale and available existing City control. Aerotriangulation solution was designed to support 1"=50' scale, 2' contour mapping within the UGB extents of existing control and 1"=50' scale, Accuracies for discrete aerotriangulation points and supported stereomodel measurements are: +/- 0.5' horizontal and vertical.

Data set Accuracy

HORIZONTAL ACCURACY: Compiled to meet ASPRS Class 1 accuracies for 1"=100' scale mapping, consistent with existing data sets from past mapping work. This is equal to an ASPRS 2014 30 cm RMSE horizontal accuracy class equating to a circular horizontal accuracy of +/- 2.4' at a 95% confidence level. VERTICAL ACCURACY: NOT APPLICABLE

Data Collection and Update Process

Softcopy photogrammetric workstations were used to view and evaluate existing City GIS impervious surface data against current (2015) stereo imagery using 3D softcopy photogrammetry methods for planimetric data updates. Photogrammetric vector linework was collected and coded by feature type. Impervious area polygons were built using polygon ID points to identify selected impervious surface polygons. Final polygon builds were generated using automated methods and manually reviewed for consistency and completeness.