{
 "currentVersion": 10.91,
 "serviceDescription": "https://landscape.jpl.nasa.gov/\n\nProject Description\nThis website presents the research projects of Dr. Marc Simard, Senior Scientist at the Jet Propulsion Laboratory. The overall objective is to combine radar and lidar remote sensing to characterize the forested landscapes in 3D. The science products generated by Simard and collaborators have four main components: \n\nGlobal scale mapping of canopy height and biomass at 1km spatial resolution.\nImproving Shuttle Radar Topography Mission (SRTM) elevation dataset using ICESat's Geoscience Laser Altimeter System (GLAS).\nHigh spatial resolution mapping of canopy height and biomass using polarimeteric synthetic aperture radar interferometry (polinSAR) and LiDAR.\nMapping of mangrove forests canopy height, biomass, productivity and assessment of vulnerability to anthropogenic activity and sea level change.\n\nThese projects are funded through the NASA MEaSUREs (1,2), Terrestrial Ecology (3) and Land Cover Land Use Change (LCLUC) (4) programs. \n\nThe recent availability of global scale datasets such as SRTM, MODIS, Landsat, and ICESat/GLAS enable scientists to map the entire Earth's land surface with unprecedented details. \n\nICESat/GLAS measurements are spatially sparse measurements that provide, nonetheless, valuable information about ground elevation as well as canopy structure. Thus GLAS can be used to complete datasets, to produce global maps of canopy height. The combination of ICESat/GLAS and SRTM has been fruitful. Since mangrove forests grow around sea level, SRTM provide a first estimate of forest height (interferometric phase center) which can be calibrated with field and GLAS data. We produced maps of mangrove canopy height and biomass in several regions of the World. More details here. \n\nTo obtain high spatial resolution 3D maps, we use airborne radar and lidar sensors, in particular, UAVSAR and LVIS. In this case, our research aims at developing polarimetric synthetic aperture radar interferometry (polinSAR) for repeat-pass systems. That is, using a single radar antenna flown at least twice over a same site. This configuration is poised by the so-called temporal decorrelation that can significantly reduce interferometric coherence. Temporal decorrelation is due to short and long term changes in the target properties resulting from wind, precipitation, vegetation growth, etc. Simard, Hensley and Dubayah designed a UAVSAR flight campaign to measure the impact of temporal decorrelation on the repeat-pass interferometric signal. UAVSAR flew several sites with a variety of vegetation types: \n\nThe Laurentides Wildlife Reserve, Québec, Canada (Boreal)\nThe Hubbard Brook/Bartett forests, New Hampshire (Temperate)\nThe Howland experimental forest, Maine (Temperate)\nThe King's Canyon National Park, California (Temperate)\nLa Selva experimental forest, Costa Rica (Tropical)\nOsa Peninsula, Costa Rica (Tropical)",
 "name": "static/tree_canopy_height_global_3d",
 "description": "https://landscape.jpl.nasa.gov/\n\nProject Description\nThis website presents the research projects of Dr. Marc Simard, Senior Scientist at the Jet Propulsion Laboratory. The overall objective is to combine radar and lidar remote sensing to characterize the forested landscapes in 3D. The science products generated by Simard and collaborators have four main components: \n\nGlobal scale mapping of canopy height and biomass at 1km spatial resolution.\nImproving Shuttle Radar Topography Mission (SRTM) elevation dataset using ICESat's Geoscience Laser Altimeter System (GLAS).\nHigh spatial resolution mapping of canopy height and biomass using polarimeteric synthetic aperture radar interferometry (polinSAR) and LiDAR.\nMapping of mangrove forests canopy height, biomass, productivity and assessment of vulnerability to anthropogenic activity and sea level change.\n\nThese projects are funded through the NASA MEaSUREs (1,2), Terrestrial Ecology (3) and Land Cover Land Use Change (LCLUC) (4) programs. \n\nThe recent availability of global scale datasets such as SRTM, MODIS, Landsat, and ICESat/GLAS enable scientists to map the entire Earth's land surface with unprecedented details. \n\nICESat/GLAS measurements are spatially sparse measurements that provide, nonetheless, valuable information about ground elevation as well as canopy structure. Thus GLAS can be used to complete datasets, to produce global maps of canopy height. The combination of ICESat/GLAS and SRTM has been fruitful. Since mangrove forests grow around sea level, SRTM provide a first estimate of forest height (interferometric phase center) which can be calibrated with field and GLAS data. We produced maps of mangrove canopy height and biomass in several regions of the World. More details here. \n\nTo obtain high spatial resolution 3D maps, we use airborne radar and lidar sensors, in particular, UAVSAR and LVIS. In this case, our research aims at developing polarimetric synthetic aperture radar interferometry (polinSAR) for repeat-pass systems. That is, using a single radar antenna flown at least twice over a same site. This configuration is poised by the so-called temporal decorrelation that can significantly reduce interferometric coherence. Temporal decorrelation is due to short and long term changes in the target properties resulting from wind, precipitation, vegetation growth, etc. Simard, Hensley and Dubayah designed a UAVSAR flight campaign to measure the impact of temporal decorrelation on the repeat-pass interferometric signal. UAVSAR flew several sites with a variety of vegetation types: \n\nThe Laurentides Wildlife Reserve, Québec, Canada (Boreal)\nThe Hubbard Brook/Bartett forests, New Hampshire (Temperate)\nThe Howland experimental forest, Maine (Temperate)\nThe King's Canyon National Park, California (Temperate)\nLa Selva experimental forest, Costa Rica (Tropical)\nOsa Peninsula, Costa Rica (Tropical)",
 "extent": {
  "xmin": -180.00138889,
  "ymin": -89.99853911000001,
  "xmax": 179.99846711000004,
  "ymax": 90.00138889,
  "spatialReference": {
   "wkid": 4326,
   "latestWkid": 4326
  }
 },
 "initialExtent": {
  "xmin": -180.00138889,
  "ymin": -89.99853911000001,
  "xmax": 179.99846711000004,
  "ymax": 90.00138889,
  "spatialReference": {
   "wkid": 4326,
   "latestWkid": 4326
  }
 },
 "fullExtent": {
  "xmin": -180.00138889,
  "ymin": -89.99853911000001,
  "xmax": 179.99846711000004,
  "ymax": 90.00138889,
  "spatialReference": {
   "wkid": 4326,
   "latestWkid": 4326
  }
 },
 "hasMultidimensions": false,
 "pixelSizeX": 0.00833333,
 "pixelSizeY": 0.00833333,
 "datasetFormat": "TIFF",
 "uncompressedSize": 933120000,
 "blockWidth": 43200,
 "blockHeight": 1,
 "compressionType": "None",
 "bandNames": [
  "Band_1"
 ],
 "allowCopy": true,
 "allowAnalysis": true,
 "bandCount": 1,
 "pixelType": "U8",
 "minPixelSize": 0,
 "maxPixelSize": 0,
 "copyrightText": "JPL",
 "serviceDataType": "esriImageServiceDataTypeGeneric",
 "serviceSourceType": "esriImageServiceSourceTypeDataset",
 "minValues": [],
 "maxValues": [],
 "meanValues": [],
 "stdvValues": [],
 "objectIdField": "",
 "fields": [],
 "capabilities": "Mensuration,Image,Metadata",
 "defaultMosaicMethod": "Center",
 "allowedMosaicMethods": "",
 "sortField": "",
 "sortValue": null,
 "sortAscending": true,
 "mosaicOperator": "First",
 "defaultCompressionQuality": 75,
 "defaultResamplingMethod": "Nearest",
 "maxImageHeight": 4100,
 "maxImageWidth": 15000,
 "allowRasterFunction": true,
 "rasterFunctionInfos": [
  {
   "name": "None",
   "description": "Make a Raster or Raster Dataset into a Function Raster Dataset.",
   "help": ""
  },
  {
   "name": "tree_canopy_height",
   "description": "A raster function template.",
   "help": ""
  }
 ],
 "rasterTypeInfos": [
  {
   "name": "Raster Dataset",
   "description": "Supports all ArcGIS Raster Datasets",
   "help": ""
  }
 ],
 "mensurationCapabilities": "Basic",
 "hasHistograms": false,
 "hasColormap": false,
 "hasRasterAttributeTable": false,
 "minScale": 0,
 "maxScale": 0,
 "exportTilesAllowed": false,
 "supportsStatistics": false,
 "supportsAdvancedQueries": false,
 "editFieldsInfo": null,
 "ownershipBasedAccessControlForRasters": null,
 "allowComputeTiePoints": false,
 "useStandardizedQueries": true,
 "advancedQueryCapabilities": {
  "useStandardizedQueries": true,
  "supportsStatistics": false,
  "supportsOrderBy": false,
  "supportsDistinct": false,
  "supportsPagination": false
 },
 "spatialReference": {
  "wkid": 4326,
  "latestWkid": 4326
 }
}