lidar/ImperviousSurfaces (MapServer)

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Service Description: <DIV STYLE="text-align:Left;font-size:12pt"><DIV><DIV>The Santa Clara County Impervious Surfaces map (v. 6/7/22) is a 5-class fine-scale polygon vector representation of all artificial impervious surfaces in Santa Clara County. There are 1,866,057 features in the dataset. Non-impervious areas are not mapped and are not covered by polygons. The impervious map represents the state of the landscape in summer, 2020. This data product was produced by the impervious mapping team at the University of Vermont Spatial Analysis Lab. Table 1 lists download locations for the dataset.Santa Clara County impervious surfaces data product availabilityDescriptionLinkFile GDBhttps://vegmap.press/Santa Clara_impervious_fgdbArcGIS Pro Layer Packagehttps://vegmap.press/Santa Clara_impervious_layer_packageVector Tile Layerhttps://vegmap.press/Santa Clara_impervious_vector_tile_layerDetailed Dataset Description:The impervious map was created using “expert systems” rulesets developed in Trimble Ecognition. These rulesets combine automated image segmentation with-object based image classification techniques. In contrast with machine learning approaches, expert systems rulesets are developed heuristically based on the knowledge of experienced image analysts. Key data sets used in the expert systems rulesets for impervious mapping included: high resolution (6 inch or greater) 4-band orthophotography (2020), the lidar point cloud (2020), and lidar derived rasters such as the canopy height model.After it was produced using Trimble Ecognition, the preliminary impervious map product was manually edited by a team of UVM’s photo interpreters. Manual editing corrected errors where the automated methods produced incorrect results.The impervious map has 5 classes, which are described below:Building – Structures including homes, commercial buildings, outbuildings, and other human-made structures such as water tanks and silage silos. Structures fully occluded by vegetation will not be mapped.Paved Road – Roads that are paved and wide enough for a vehicle.Dirt/Gravel Road – Dirt or gravel roads wide enough for a vehicle. Non-ephemeral fire roads, ranch roads and long driveways. Polygons representing narrow unpaved (single track) trails are not included in this data product.Other Dirt/Gravel Surface – Dirt or gravel surfaces that are highly compacted and used by humans and equipment, such as parking lots, road pull-offs, some dirt or gravel paths, and highly compacted areas around commercial activities. This class DOES NOT include natural turf playing fields, very lightly used dirt roads, livestock areas, naturally occurring bare soil or rock, or bare areas around ponds.Other Paved Surface – Includes parking lots, sidewalks, paved walking paths, swimming pools, tennis courts.Miscellaneous quality control and processing notes:Zoom level used during manual quality control was no finer than 1 to 500.Vector data was created with no overlapping polygons.</DIV></DIV></DIV>

Map Name: ImperviousSurfaces

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ImperviousSurfaces (0)

Description: <DIV STYLE="text-align:Left;font-size:12pt"><DIV><DIV>The Santa Clara County Impervious Surfaces map (v. 6/7/22) is a 5-class fine-scale polygon vector representation of all artificial impervious surfaces in Santa Clara County. There are 1,866,057 features in the dataset. Non-impervious areas are not mapped and are not covered by polygons. The impervious map represents the state of the landscape in summer, 2020. This data product was produced by the impervious mapping team at the University of Vermont Spatial Analysis Lab. Table 1 lists download locations for the dataset.Santa Clara County impervious surfaces data product availabilityDescriptionLinkFile GDBhttps://vegmap.press/Santa Clara_impervious_fgdbArcGIS Pro Layer Packagehttps://vegmap.press/Santa Clara_impervious_layer_packageVector Tile Layerhttps://vegmap.press/Santa Clara_impervious_vector_tile_layerDetailed Dataset Description:The impervious map was created using “expert systems” rulesets developed in Trimble Ecognition. These rulesets combine automated image segmentation with-object based image classification techniques. In contrast with machine learning approaches, expert systems rulesets are developed heuristically based on the knowledge of experienced image analysts. Key data sets used in the expert systems rulesets for impervious mapping included: high resolution (6 inch or greater) 4-band orthophotography (2020), the lidar point cloud (2020), and lidar derived rasters such as the canopy height model.After it was produced using Trimble Ecognition, the preliminary impervious map product was manually edited by a team of UVM’s photo interpreters. Manual editing corrected errors where the automated methods produced incorrect results.The impervious map has 5 classes, which are described below:Building – Structures including homes, commercial buildings, outbuildings, and other human-made structures such as water tanks and silage silos. Structures fully occluded by vegetation will not be mapped.Paved Road – Roads that are paved and wide enough for a vehicle.Dirt/Gravel Road – Dirt or gravel roads wide enough for a vehicle. Non-ephemeral fire roads, ranch roads and long driveways. Polygons representing narrow unpaved (single track) trails are not included in this data product.Other Dirt/Gravel Surface – Dirt or gravel surfaces that are highly compacted and used by humans and equipment, such as parking lots, road pull-offs, some dirt or gravel paths, and highly compacted areas around commercial activities. This class DOES NOT include natural turf playing fields, very lightly used dirt roads, livestock areas, naturally occurring bare soil or rock, or bare areas around ponds.Other Paved Surface – Includes parking lots, sidewalks, paved walking paths, swimming pools, tennis courts.Miscellaneous quality control and processing notes:Zoom level used during manual quality control was no finer than 1 to 500.Vector data was created with no overlapping polygons.</DIV></DIV></DIV>

Service Item Id: 67eefd71f1e8412db2618acc306c881f

Copyright Text: San Mateo County Resource Conservation District, CALFIRE, Santa Clara Mountains Stewardship Network, Midpeninsula Regional Open Space District, County of Santa Clara, Tukman Geospatial LLC

Spatial Reference: 102100 (3857) LatestVCSWkid(0)

Single Fused Map Cache: true

Tile Info:

Height: 256
Width: 256
DPI: 96
Levels of Detail: 24
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Format: PNG
Compression Quality: 0.0
Origin: X: -2.0037508342787E7
Y: 2.0037508342787E7
Spatial Reference: 102100 (3857) LatestVCSWkid(0)

Storage Info:

Storage Format: esriMapCacheStorageModeCompactV2
Packet Size: 128

Initial Extent:

Full Extent:

Units: esriMeters

Supported Image Format Types: PNG32,PNG24,PNG,JPG,DIB,TIFF,EMF,PS,PDF,GIF,SVG,SVGZ,BMP

Document Info:

Supports Dynamic Layers: true

MaxRecordCount: 2000

MaxImageHeight: 4096

MaxImageWidth: 4096

Supported Query Formats: JSON, geoJSON, PBF

Supports Query Data Elements: true

Min Scale: 5.91657527591555E8

Max Scale: 282.124294

Supports Datum Transformation: true

Child Resources: Info Dynamic Layer

Supported Operations: Export Map Identify QueryLegends QueryDomains Find Return Updates