static/tree_canopy_height_global

View In: ArcGIS JavaScript ArcGIS Online Map Viewer ArcGIS Earth ArcMap

View Footprint In: ArcGIS Online Map Viewer

Service Description: https://landscape.jpl.nasa.gov/ Project Description This 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: Global scale mapping of canopy height and biomass at 1km spatial resolution. Improving Shuttle Radar Topography Mission (SRTM) elevation dataset using ICESat's Geoscience Laser Altimeter System (GLAS). High spatial resolution mapping of canopy height and biomass using polarimeteric synthetic aperture radar interferometry (polinSAR) and LiDAR. Mapping of mangrove forests canopy height, biomass, productivity and assessment of vulnerability to anthropogenic activity and sea level change. These projects are funded through the NASA MEaSUREs (1,2), Terrestrial Ecology (3) and Land Cover Land Use Change (LCLUC) (4) programs. The 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. ICESat/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. To 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: The Laurentides Wildlife Reserve, Québec, Canada (Boreal) The Hubbard Brook/Bartett forests, New Hampshire (Temperate) The Howland experimental forest, Maine (Temperate) The King's Canyon National Park, California (Temperate) La Selva experimental forest, Costa Rica (Tropical) Osa Peninsula, Costa Rica (Tropical)

Name: static/tree_canopy_height_global_3d

Description: https://landscape.jpl.nasa.gov/ Project Description This 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: Global scale mapping of canopy height and biomass at 1km spatial resolution. Improving Shuttle Radar Topography Mission (SRTM) elevation dataset using ICESat's Geoscience Laser Altimeter System (GLAS). High spatial resolution mapping of canopy height and biomass using polarimeteric synthetic aperture radar interferometry (polinSAR) and LiDAR. Mapping of mangrove forests canopy height, biomass, productivity and assessment of vulnerability to anthropogenic activity and sea level change. These projects are funded through the NASA MEaSUREs (1,2), Terrestrial Ecology (3) and Land Cover Land Use Change (LCLUC) (4) programs. The 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. ICESat/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. To 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: The Laurentides Wildlife Reserve, Québec, Canada (Boreal) The Hubbard Brook/Bartett forests, New Hampshire (Temperate) The Howland experimental forest, Maine (Temperate) The King's Canyon National Park, California (Temperate) La Selva experimental forest, Costa Rica (Tropical) Osa Peninsula, Costa Rica (Tropical)

Single Fused Map Cache: false

Extent:

Initial Extent:

Full Extent:

Pixel Size X: 0.00833333

Pixel Size Y: 0.00833333

Band Count: 1

Pixel Type: U8

RasterFunction Infos: {"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": "" } ]}

Mensuration Capabilities: Basic

Has Histograms: false

Has Colormap: false

Has Multi Dimensions : false

Rendering Rule:

Min Scale: 0

Max Scale: 0

Copyright Text: JPL

Service Data Type: esriImageServiceDataTypeGeneric

Min Values: N/A

Max Values: N/A

Mean Values: N/A

Standard Deviation Values: N/A

Object ID Field:

Fields: None

Default Mosaic Method: Center

Allowed Mosaic Methods:

SortField:

SortValue: null

Mosaic Operator: First

Default Compression Quality: 75

Default Resampling Method: Nearest

Max Record Count: null

Max Image Height: 4100

Max Image Width: 15000

Max Download Image Count: null

Max Mosaic Image Count: null

Allow Raster Function: true

Allow Copy: true

Allow Analysis: true

Allow Compute TiePoints: false

Supports Statistics: false

Supports Advanced Queries: false

Use StandardizedQueries: true

Raster Type Infos:

Has Raster Attribute Table: false

Edit Fields Info: null

Ownership Based AccessControl For Rasters: null

Child Resources: Info Statistics Key Properties Legend Raster Function Infos

Supported Operations: Export Image Identify Measure Compute Histograms Compute Statistics Histograms Get Samples Compute Class Statistics Query Boundary Compute Pixel Location Compute Angles Validate Project

static/tree_canopy_height_global_3d (ImageServer)