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Original Articles

Band Selection Using Hyperspectral Data of Subtropical Tree Species

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Pages 3-11 | Published online: 02 Jan 2008

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Read on this site (6)

Mohamad Anuar Izzuddin, Abu Seman Idris, Mohd Noor Nisfariza, Abd Aziz Nordiana, Helmi Zulhaidi Mohd Shafri & Bahrom Ezzati. (2017) The development of spectral indices for early detection of Ganoderma disease in oil palm seedlings. International Journal of Remote Sensing 38:23, pages 6505-6527.
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H. van Deventer, M. A. Cho & O. Mutanga. (2017) Improving the classification of six evergreen subtropical tree species with multi-season data from leaf spectra simulated to WorldView-2 and RapidEye. International Journal of Remote Sensing 38:17, pages 4804-4830.
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JamesH. Everitt, Chenghai Yang, Kenneth Summy & JulieG. Nachtrieb. (2013) Using hyperspectral reflectance data to assess biocontrol damage of giant salvinia. Geocarto International 28:6, pages 502-516.
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K. Mansour, O. Mutanga & T. Everson. (2013) Spectral discrimination of increaser species as an indicator of rangeland degradation using field spectrometry. Journal of Spatial Science 58:1, pages 101-117.
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HelmiZ. M. Shafri, MohdI. Anuar, IdrisA. Seman & NisfarizaM. Noor. (2011) Spectral discrimination of healthy and Ganoderma-infected oil palms from hyperspectral data. International Journal of Remote Sensing 32:22, pages 7111-7129.
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J.H. Everitt, C. Yang, K.R. Summy, C.S. Owens, L.M. Glomski & R.M. Smart. (2011) Using in situ hyperspectral reflectance data to distinguish nine aquatic plant species. Geocarto International 26:6, pages 459-473.
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Articles from other publishers (18)

Chunmei He, Jia Sun, Yuwen Chen, Lunche Wang, Shuo Shi, Feng Qiu, Shaoqiang Wang, Jian Yang & Torbern Tagesson. (2023) PROSPECT-GPR: Exploring spectral associations among vegetation traits in wavelength selection for leaf mass per area and water contents. Science of Remote Sensing 8, pages 100100.
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Youssra Ghoussein, Ghaleb Faour, Ali Fadel, Jacques Haury, Hussein Abou-Hamdan & Hervé Nicolas. (2023) Hyperspectral discrimination of Eichhornia crassipes covers, in the red edge and near infrared in a Mediterranean river. Biological Invasions.
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Hastings Shamaoma, Paxie W. Chirwa, Abel Ramoelo, Andrew T. Hudak & Stephen Syampungani. (2022) The Application of UASs in Forest Management and Monitoring: Challenges and Opportunities for Use in the Miombo Woodland. Forests 13:11, pages 1812.
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Guangman Song, Quan Wang & Jia Jin. (2022) Temporal instability of partial least squares regressions for estimating leaf photosynthetic traits from hyperspectral information. Journal of Plant Physiology, pages 153831.
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Jia Jin, Quan Wang & Guangman Song. (2021) Selecting informative bands for partial least squares regressions improves their goodness-of-fits to estimate leaf photosynthetic parameters from hyperspectral data. Photosynthesis Research 151:1, pages 71-82.
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Jian Yang, Songxi Yang, Yangyang Zhang, Shuo Shi & Lin Du. (2020) Improving characteristic band selection in leaf biochemical property estimation considering interrelations among biochemical parameters based on the PROSPECT-D model. Optics Express 29:1, pages 400.
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Andrew Hennessy, Kenneth Clarke & Megan Lewis. (2020) Hyperspectral Classification of Plants: A Review of Waveband Selection Generalisability. Remote Sensing 12:1, pages 113.
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Heidi van Deventer, Moses Azong Cho & Onisimo Mutanga. (2019) Multi-season RapidEye imagery improves the classification of wetland and dryland communities in a subtropical coastal region. ISPRS Journal of Photogrammetry and Remote Sensing 157, pages 171-187.
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Stéphane Jacquemoud & Susan Ustin. 2019. Leaf Optical Properties. Leaf Optical Properties.
Jia Jin & Quan Wang. (2019) Selection of Informative Spectral Bands for PLS Models to Estimate Foliar Chlorophyll Content Using Hyperspectral Reflectance. IEEE Transactions on Geoscience and Remote Sensing 57:5, pages 3064-3072.
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Jia Jin & Quan Wang. (2019) Evaluation of Informative Bands Used in Different PLS Regressions for Estimating Leaf Biochemical Contents from Hyperspectral Reflectance. Remote Sensing 11:2, pages 197.
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Tomás Acuña-Ruz, Diego Uribe, Richard Taylor, Lucas Amézquita, María Cristina Guzmán, Javier Merrill, Paula Martínez, Leandro Voisin & Cristian Mattar B.. (2018) Anthropogenic marine debris over beaches: Spectral characterization for remote sensing applications. Remote Sensing of Environment 217, pages 309-322.
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A. M. Stellacci, A. Castrignanò, A. Troccoli, B. Basso & G. Buttafuoco. (2016) Selecting optimal hyperspectral bands to discriminate nitrogen status in durum wheat: a comparison of statistical approaches. Environmental Monitoring and Assessment 188:3.
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Heidi van Deventer, Moses Azong Cho, Onisimo Mutanga, Laven Naidoo & Nontembeko Dudeni-Tlhone. (2015) Reducing Leaf-Level Hyperspectral Data to 22 Components of Biochemical and Biophysical Bands Optimizes Tree Species Discrimination. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8:6, pages 3161-3171.
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Kaveh Shahi, Helmi Z.M. Shafri, Ebrahim Taherzadeh, Shattri Mansor & Ratnasamy Muniandy. (2015) A novel spectral index to automatically extract road networks from WorldView-2 satellite imagery. The Egyptian Journal of Remote Sensing and Space Science 18:1, pages 27-33.
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Fabian E. Fassnacht, Carsten Neumann, Michael Forster, Henning Buddenbaum, Aniruddha Ghosh, Anne Clasen, Pawan Kumar Joshi & Barbara Koch. (2014) Comparison of Feature Reduction Algorithms for Classifying Tree Species With Hyperspectral Data on Three Central European Test Sites. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7:6, pages 2547-2561.
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Khalid Mansour, Onisimo Mutanga, Terry Everson & Elhadi Adam. (2012) Discriminating indicator grass species for rangeland degradation assessment using hyperspectral data resampled to AISA Eagle resolution. ISPRS Journal of Photogrammetry and Remote Sensing 70, pages 56-65.
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Yuki Hamada, Douglas A. Stow, Lloyd L. Coulter, Jim C. Jafolla & Leif W. Hendricks. (2007) Detecting Tamarisk species (Tamarix spp.) in riparian habitats of Southern California using high spatial resolution hyperspectral imagery. Remote Sensing of Environment 109:2, pages 237-248.
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