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Spectral sensing for dry matter biomass estimation of energy crops
Tofael Ahamed
, Lei Tian
, Casimiro Gadanah
, Francisco A.C. Pinto
, Hx Liu
, K. C. Ting
Research output
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Chapter in Book/Report/Conference proceeding
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Conference contribution
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Dive into the research topics of 'Spectral sensing for dry matter biomass estimation of energy crops'. Together they form a unique fingerprint.
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Keyphrases
Dry Matter
100%
Energy Crops
100%
Biomass Estimation
100%
Spectral Sensing
100%
Image Information
66%
Biomass Yield
33%
Miscanthus
33%
Spectral Data
33%
Central Wavelength
33%
Infrared Image
33%
Red Edge
33%
Multispectral Image
33%
Energy Content
33%
Growing Season
33%
Georeferencing
33%
Switchgrass
33%
Leaf Area Index
33%
Vegetation Change
33%
Biomass Energy
33%
Data Processing System
33%
Ground Truth Data
33%
RTK-GPS
33%
Intercepted Photosynthetically Active Radiation
33%
Green Normalized Difference Vegetation Index (GNDVI)
33%
Vegetation Index
33%
Prairie Grass
33%
Colour Infrared
33%
Remote Sensing Model
33%
Multispectral Camera
33%
Ground Reference
33%
Agronomic Data
33%
Ground Control Points
33%
GPS Units
33%
Orthorectification
33%
Vegetative Indices
33%
Spectrometry Analysis
33%
Canopy Analysis
33%
Index Leaf
33%
Engineering
Dry Matter
100%
Tower
100%
Spectral Sensing
100%
Image Information
66%
Reference Data
33%
Central Wavelength
33%
Biomass Yield
33%
Multispectral Image
33%
Control Point
33%
Energy Content
33%
Rectification
33%
Processing System
33%
Captured Image
33%
Growing Season
33%
Global Positioning System
33%
Leaf Area Index
33%
Earth and Planetary Sciences
Energy Crop
100%
Dry Matter
100%
Rectification
33%
Multispectral Image
33%
Global Positioning System
33%
Vegetation
33%
Growing Season
33%
Leaf Area
33%
Photosynthetically Active Radiation
33%
Vegetation Index
33%
Data Processing System
33%
Vegetative Index
33%
Remote Sensing
33%