Vegetation classification map and covariates associated with NEON AOP survey, East River, CO 2018

Dataset · Mon Jan 01 00:00:00 EST 2024

DOI:https://doi.org/10.15485/1602034· OSTI ID:1602034

Falco, Nicola  ^[1]; M. Wainwright, Haruko ^[1]; Chadwick, K. Dana ^[2]; Dafflon, Baptiste ^[1]; J. Enquist, Brian ^[3]; Unhlemann, Sebastian ^[1]; Breckheimer, Ian ^[4]; Lamb, Jack ^[1]; Chen, Jiancong ^[1]; Tuvshintugs, Orgil ^[5]; Balde, Abdoulaye ^[1]; H. Williams, Ken ^[1]; Brodie, Eoin ^[1]

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1. Lawrence Berkeley National Laboratory
2. Stanford University
3. University of Arizona
4. RMBL
5. Arizona State University

The package is composed of:- Classification vegetation map.zip: it contains the classification map (PNG, geotiff), which is derived from hyperspectral and LiDAR airborne data acquired by the NEON AOP in June 2018 using a machine learning approach, and the class code (csv) showing the corresponding vegetation class to pixel values.- Classification_reference_data.zip (csv): it contains reference data used in the machine learning procedure to predict vegetation and non-vegetation classes;- LiDAR_derived_products.zip (geotiff): elevation, slope, curvature, Topographic Wetness Index (TWI), Topographic Position Index (TPI), solar insolation, canopy height model (CMD). The topographical metrics were smoothed with a 5x5 pixel window;- Vegetation_indices.zip (geotiff): Normalized Difference Vegetation Index, Normalized Difference Nitrogen Index, Normalized Difference Water Index;- Cloud_shadow_urban_masks.zip (geotiffs): Masks of clouds and shadows that were applied to the mapping;- Covariates_10mGrid_vegetationClasses_topographicMetrics_soilProperties.zip (csv): 10-m gridded data that integrate all the previous datasets as well as geophysical data.Geotiffs can be visualized with any GIF software or library able to handle geotiff images. CSV can be open with any software able to handle comma-separated values files.

• Research Organization: Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) (United States); Watershed Function SFA
• Sponsoring Organization: U.S. DOE > Office of Science > Biological and Environmental Research (BER)
• DOE Contract Number: DEAC0205CH11231
• OSTI ID: 1602034
• Report Number(s): paf_326
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
Hyperspectral imaging
Airborne remote sensing
watershed
Vegetation classification
NEON AOP
Modelling results
Vegetation classification map
Soil electrical conductivity
Canopy height
Vegetation indices
EARTH SCIENCE > LAND SURFACE > LAND USE/LAND COVER
EARTH SCIENCE > LAND SURFACE > SOILS
EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION > DIGITAL ELEVATION/TERRAIN MODEL (DEM)
EARTH SCIENCE > BIOSPHERE > VEGETATION > VEGETATION INDEX > NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI)