{
 "currentVersion": 10.5,
 "serviceDescription": "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.",
 "mapName": "Layers",
 "description": "",
 "copyrightText": "NASA SEDAC",
 "supportsDynamicLayers": true,
 "layers": [
  {
   "id": 0,
   "name": "urbanspatial-urban-extents-viirs-modis-us-2015.tif",
   "parentLayerId": -1,
   "defaultVisibility": true,
   "subLayerIds": null,
   "minScale": 0,
   "maxScale": 0
  }
 ],
 "tables": [],
 "spatialReference": {
  "wkid": 102100,
  "latestWkid": 3857
 },
 "singleFusedMapCache": true,
 "tileInfo": {
  "rows": 256,
  "cols": 256,
  "dpi": 96,
  "format": "MIXED",
  "compressionQuality": 75,
  "origin": {
   "x": -2.0037508342787E7,
   "y": 2.0037508342787E7
  },
  "spatialReference": {
   "wkid": 102100,
   "latestWkid": 3857
  },
  "lods": [
   {
    "level": 0,
    "resolution": 156543.03392800014,
    "scale": 5.91657527591555E8
   },
   {
    "level": 1,
    "resolution": 78271.51696399994,
    "scale": 2.95828763795777E8
   },
   {
    "level": 2,
    "resolution": 39135.75848200009,
    "scale": 1.47914381897889E8
   },
   {
    "level": 3,
    "resolution": 19567.87924099992,
    "scale": 7.3957190948944E7
   },
   {
    "level": 4,
    "resolution": 9783.93962049996,
    "scale": 3.6978595474472E7
   },
   {
    "level": 5,
    "resolution": 4891.96981024998,
    "scale": 1.8489297737236E7
   },
   {
    "level": 6,
    "resolution": 2445.98490512499,
    "scale": 9244648.868618
   },
   {
    "level": 7,
    "resolution": 1222.992452562495,
    "scale": 4622324.434309
   },
   {
    "level": 8,
    "resolution": 611.4962262813797,
    "scale": 2311162.217155
   },
   {
    "level": 9,
    "resolution": 305.74811314055756,
    "scale": 1155581.108577
   },
   {
    "level": 10,
    "resolution": 152.87405657041106,
    "scale": 577790.554289
   },
   {
    "level": 11,
    "resolution": 76.43702828507324,
    "scale": 288895.277144
   },
   {
    "level": 12,
    "resolution": 38.21851414253662,
    "scale": 144447.638572
   },
   {
    "level": 13,
    "resolution": 19.10925707126831,
    "scale": 72223.819286
   },
   {
    "level": 14,
    "resolution": 9.554628535634155,
    "scale": 36111.909643
   },
   {
    "level": 15,
    "resolution": 4.77731426794937,
    "scale": 18055.954822
   },
   {
    "level": 16,
    "resolution": 2.388657133974685,
    "scale": 9027.977411
   },
   {
    "level": 17,
    "resolution": 1.1943285668550503,
    "scale": 4513.988705
   },
   {
    "level": 18,
    "resolution": 0.5971642835598172,
    "scale": 2256.994353
   },
   {
    "level": 19,
    "resolution": 0.29858214164761665,
    "scale": 1128.497176
   }
  ]
 },
 "initialExtent": {
  "xmin": -1.3496838692707656E7,
  "ymin": 3632461.813632687,
  "xmax": -7843661.307781359,
  "ymax": 7602317.714306007,
  "spatialReference": {
   "cs": "pcs",
   "wkid": 102100
  }
 },
 "fullExtent": {
  "xmin": -1.3885500000246223E7,
  "ymin": 2870242.7834959277,
  "xmax": -7455000.000242797,
  "ymax": 6338886.058989692,
  "spatialReference": {
   "cs": "pcs",
   "wkid": 102100
  }
 },
 "minScale": 9244648.868618,
 "maxScale": 36111.909643,
 "units": "esriMeters",
 "supportedImageFormatTypes": "PNG32,PNG24,PNG,JPG,DIB,TIFF,EMF,PS,PDF,GIF,SVG,SVGZ,BMP",
 "documentInfo": {
  "Title": "2015 VIIRS/MODIS Urban Extents Using Neural Network Method",
  "Author": "",
  "Comments": "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.",
  "Subject": "To provide representations of urban areas in the Continental U.S. in the year 2015.",
  "Category": "",
  "AntialiasingMode": "None",
  "TextAntialiasingMode": "Force",
  "Keywords": "urban,nighttime lights,urbanspatial-urban-extents-viirs-modis-us-2015"
 },
 "capabilities": "Map,Query,Data",
 "supportedQueryFormats": "JSON, AMF, geoJSON",
 "exportTilesAllowed": false,
 "supportsDatumTransformation": true,
 "maxRecordCount": 1000,
 "maxImageHeight": 4096,
 "maxImageWidth": 4096,
 "supportedExtensions": "WMSServer"
}