Service Description: The purpose of this project was to conduct a top down canopy assessment approach. Utilizing the most current 2020 National Agricultural Imagery Program (NAIP) 60cm imagery and advance remote sensing technology, land cover features were identified by using an object-based image analysis (OBIA) methodology to process and analyze high resolution imagery. This technique allows a more accurate and cost-effective automated feature extraction of land cover classes. The final GIS land cover layer allows the city of Davis, California to conduct additional spatial analyses necessary to identify and map the existing land cover layer for future.
Service ItemId: ef67d65c1b7a4369980a63ea56292b75
Has Versioned Data: false
Max Record Count: 2000
Supported query Formats: JSON
Supports applyEdits with GlobalIds: False
Supports Shared Templates: True
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Layers:
Description: With the size of the study area measured at approximately 10 square miles, a cost-effective and accurate strategy for assessing the urban forest is the use of remotely sensed and semi-automated classification methods to inventory the current canopy cover and to analyze data for future planting goals
102642 (2226)
Initial Extent:
XMin: 6618901.3560234
YMin: 1955902.72650272
XMax: 6656069.91646304
YMax: 1972345.96061427
Spatial Reference: 102642 (2226)
Full Extent:
XMin: 6620590.83604339
YMin: 1956729.80929901
XMax: 6654380.436443
YMax: 1971518.87781793
Spatial Reference: 102642 (2226)
Units: esriFeet
Child Resources:
Info
SharedTemplates
Supported Operations:
Query
ConvertFormat
Get Estimates