Using a Genetic Algorithm as an Optimal Band Selector in the Mid and Thermal Infrared (2.5–14 µm) to Discriminate Vegetation Species
Genetic variation between various plant species determines differences in their physio-chemical makeup and ultimately in their hyperspectral emissivity signatures. The hyperspectral emissivity signatures, on the one hand, account for the subtle physio-chemical changes in the vegetation, but on the o...
Main Authors: | Saleem Ullah, Thomas A. Groen, Martin Schlerf, Andrew K. Skidmore, Willem Nieuwenhuis, Chaichoke Vaiphasa |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2012-06-01
|
Series: | Sensors |
Subjects: | |
Online Access: | http://www.mdpi.com/1424-8220/12/7/8755 |
Similar Items
-
Assessment of the Usefulness of Spectral Bands for the Next Generation of Sentinel-2 Satellites by Reconstruction of Missing Bands
by: Jordi Inglada, et al.
Published: (2022-05-01) -
Estimation of Soil Moisture Content from the Spectral Reflectance of Bare Soils in the 0.4–2.5 µm Domain
by: Sophie Fabre, et al.
Published: (2015-02-01) -
Discrimination of Tropical Mangroves at the Species Level with EO-1 Hyperion Data
by: Chaichoke Vaiphasa, et al.
Published: (2013-07-01) -
Auto-Calibrated Charge-Sensitive Infrared Phototransistor at 9.3 µm
by: Mohsen Bahrehmand, et al.
Published: (2023-03-01) -
PolSAR Image Classification Method Based on Markov Discriminant Spectral Clustering
by: ZHANG Xiangrong, et al.
Published: (2019-08-01)