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Alignment of UAV-hyperspectral bands using keypoint descriptors in a spectrally complex environment
In this study, the different feature descriptor techniques such as Harris-Stephens Features (HSF), Min Eigen Features (MEF), Scale Invariant Feature Transformation (SIFT), Speeded-Up Robust Features (SURF), Binary Robust Invariants Scalable Keypoints (BRISK), and Features from Accelerated Segment Test (FAST) were evaluated to align hyperspectral bands in a spectrally complex environment.
UAV-hyperspectral imaging of spectrally complex environments
The challenges in the methods of sensor calibration, data acquisition, radiometric correction for illumination variation, mosaicking and geometric correction for UAV-hyperspectral imaging of highly heterogeneous environments, such as swamps are addressed.
Fusion of Spectral and Structural Information from Aerial Images for Improved Biomass Estimation
The implemented approach outperformed commonly used VIs for estimation of biomass at all growth stages in wheat, and strongly support the applicability of the proposed approach for high-throughput phenotyping of germplasm in wheat and other crop species.
Estimating early season growth and biomass of field pea for selection of divergent ideotypes using proximal sensing
A robust approach to identify roof bolts in 3D point cloud data captured from a mobile laser scanner
Automated structural discontinuity mapping in a rock face occluded by vegetation using mobile laser scanning
High-throughput phenotyping using digital and hyperspectral imaging-derived biomarkers for genotypic nitrogen response
A novel vegetation index was derived to estimate chlorophyll and was shown to be effective for high-throughput phenotyping of wheat germplasm for nitrogen response.
Development of a UAV-mounted system for remotely collecting mine water samples
- B. Banerjee, S. Raval, Thomas Maslin, W. Timms
- Environmental ScienceInternational Journal of Mining, Reclamation and…
- 29 November 2018
ABSTRACT Accurate and frequent measurement of mine water quality is essential for timely management and regulatory requirements. At mines, traditional water sample collection practices are sometimes…
Roof bolt identification in underground coal mines from 3D point cloud data using local point descriptors and artificial neural network
An automated method of roof bolt identification from 3D point cloud data is presented to assist in spatio-temporal monitoring efforts at mine sites and was found to be superior by up to 8% in terms of the achieved quality metric.
A Particle Swarm Optimization Based Approach to Pre-tune Programmable Hyperspectral Sensors
This article presents development of an innovative approach to identify spectrally significant wavelength bands, for a given environment, to tune hyperspectral sensor acquisition before UAV borne surveys, to pre-tune UAV-hyperspectral sensors before the survey.