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sedac/urbanspatial_urban_extents_viirs_modis_us_2015 (MapServer)

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Service Description: The 2015 VIIRS/MODIS Urban Extents Using Neural Network Method map layer is part of the 2015 Urban Extents from VIIRS and MODIS for the Continental U.S. Using Machine Learning Methods data set. It models urban settlements as of 2015 with input data from two types of satellite imagery: Visible Infrared Imaging Radiometer Suite (VIIRS) Nighttime Light (NTL) data from the Day/Night Band (DNB), and Moderate Resolution Imaging Spectroradiometer (MODIS) corrected daytime Normalized Difference Vegetation Index (NDVI). After several machine learning methods including Random Forest (RF), Gradient Boosting Machine, Neural Network (NN), and Enterprise Service Bus (ESB) were evaluated, the NN method shown here had the highest accuracy in predicting urban extent at 500 meter resolution. See more information at: https://doi.org/10.7927/a49b-sm16.

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Copyright Text: NASA SEDAC

Spatial Reference: 102100  (3857)


Single Fused Map Cache: true

Tile Info: 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: 1000

MaxImageHeight: 4096

MaxImageWidth: 4096

Supported Query Formats: JSON, AMF, geoJSON

Min Scale: 9244648.868618

Max Scale: 36111.909643

Supports Datum Transformation: true



Child Resources:   Info   Dynamic Layer

Supported Operations:   Export Map   Identify   Find   Return Updates