Results 41 to 50 of about 35,844 (297)
The chlorophyll-a (Chl-a) concentration of eutrophic lakes fluctuates significantly due to the disturbance of wind and anthropogenic activities on the water body. Consequently, estimation of the Chl-a concentration has become an immense challenge. Due to
Runfei Zhang +10 more
doaj +1 more source
Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches [PDF]
Imaging spectrometers measure electromagnetic energy scattered in their instantaneous field view in hundreds or thousands of spectral channels with higher spectral resolution than multispectral cameras.
Antonio Plaza +8 more
core +8 more sources
Hyperspectral imagery has been widely used in precision agriculture due to its rich spectral characteristics. With the rapid development of remote sensing technology, the airborne hyperspectral imagery shows detailed spatial information and temporal ...
Lifei Wei +7 more
doaj +1 more source
Semi-supervised linear spectral unmixing using a hierarchical Bayesian model for hyperspectral imagery [PDF]
This paper proposes a hierarchical Bayesian model that can be used for semi-supervised hyperspectral image unmixing. The model assumes that the pixel reflectances result from linear combinations of pure component spectra contaminated by an additive ...
Chein-i Chang +4 more
core +6 more sources
Anomaly detection from hyperspectral imagery [PDF]
We develop anomaly detectors, i.e., detectors that do not presuppose a signature model of one or more dimensions, for three clutter models: the local normal model, the global normal mixture model, and the global linear mixture model. The local normal model treats the neighborhood of a pixel as having a normal probability distribution.
D.W.J. Stein +5 more
openaire +1 more source
Selection of the key earth observation sensors and platforms focusing on applications for Polar Regions in the scope of Copernicus system 2020-2030 [PDF]
An optimal payload selection conducted in the frame of the H2020 ONION project (id 687490) is presented based on the ability to cover the observation needs of the Copernicus system in the time period 2020–2030.
Camps Carmona, Adriano José +6 more
core +2 more sources
In this study, we automate tree species classification and mapping using field-based training data, high spatial resolution airborne hyperspectral imagery, and a convolutional neural network classifier (CNN).
Geoffrey A. Fricker +5 more
doaj +1 more source
Assessment of hydrogen fluoride damage to vegetation using optical remote sensing data [PDF]
This research assesses damage to vegetation from accidental gaseous hydrogen fluoride leakage, through the analysis of spectral features of the damaged plants using digital aerial photographs and airborne hyperspectral imagery.
C. U. Hyun, J. S. Lee, I. Lee
doaj +1 more source
Adaptive Markov random fields for joint unmixing and segmentation of hyperspectral image [PDF]
Linear spectral unmixing is a challenging problem in hyperspectral imaging that consists of decomposing an observed pixel into a linear combination of pure spectra (or endmembers) with their corresponding proportions (or abundances). Endmember extraction
Benediktsson, Jon Atli +3 more
core +4 more sources
Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha +18 more
wiley +1 more source

