UAS-multisensor input imagery and random forest classification products for mapping vegetation species at a tallgrass prairie in Urbana, IL

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Hall, Emma;Lara, Mark J

Description

Three mosaic raster files are provided depicting Uncrewed Aerial Systems (UAS) data collection from RGB, multispectral, and hyperspectral sensors, which were collected at Weaver Park in Urbana, IL. Along with spectral bands, all image products are fused with canopy height models (CHM), where RGB and multispectral products are fused with an SfM-derived (structure from motion) CHM and the hyperspectral product is fused with a LiDAR-derived (Light Detection and Ranging) CHM. A multispectral phenological time series product is also provided, where Normalized Difference Vegetation Index (NDVI) was calculated across six time periods in one growing season and where an additional 15 NDVI-derived metrics were calculated, resulting in a 21-band image product. Differential GPS (dGPS; 2cm resolution) data identifying vegetation species are also provided, which were used at the training and testing datasets for conducting random forest classifications on each image product. Random forest classification models were applied to each of the three UAS-sensor types both with and without CHM fusion, and to the multispectral phenology time series image, resulting in the 7 vegetation maps provided.

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Metrics

Dataset Index

1.2

FAIR Score

96%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

PANGAEA

Assigned Domain

Subfield

Media Technology

Field

Engineering

Domain

Physical Sciences

Confidence Score

46%

Source

Scholar Data Model

Keywords

hyperspectralLidarMultispectralphenologyRandom forest classificationTallgrass PrairieTime seriesUASVegetation MappingFile contentBinary ObjectBinary Object (File Size)Uncrewed Aerial System

Normalization Factors

FT

26.92

CTw

1.00

MTw

1.00