Examining the utility of hyperspectral remote sensing and partial least squares to predict plant stress responses to sulphur dioxide pollution: a case study of Trichilia dregeana Sond.
Author:
Affiliation:
1. Plant Germplasm Conservation Research, School of Life Sciences, University of KwaZulu-Natal, Durban, South Africa
2. Department of Geography and Environmental Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa
Publisher
Informa UK Limited
Subject
General Earth and Planetary Sciences,Geography, Planning and Development
Link
https://www.tandfonline.com/doi/pdf/10.1080/03736245.2016.1231627
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1. Random forest regression and spectral band selection for estimating sugarcane leaf nitrogen concentration using EO-1 Hyperion hyperspectral data
2. A comparison of partial least squares (PLS) and sparse PLS regressions for predicting yield of Swiss chard grown under different irrigation water sources using hyperspectral data
3. CUTOFF THRESHOLD OF VARIABLE IMPORTANCE IN PROJECTION FOR VARIABLE SELECTION
4. An Assessment of Morphological, Physiological and Biochemical Biomarkers of Industrial Air Pollution in the Leaves of Brachylaena discolor
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1. ML based assessment and prediction of air pollution from satellite images during COVID-19 pandemic;Multimedia Tools and Applications;2024-01-13
2. Responses of Trichilia dregeana leaves to sulphur dioxide pollution: A comparison of morphological, physiological and biochemical biomarkers;Atmospheric Pollution Research;2017-07
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