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Parcel-Based Crop Classification Using Multi-Temporal TerraSAR-X Dual Polarimetric Data

Remote sensing (Basel, Switzerland), 2019-05, Vol.11 (10), p.1148

Sonobe, Rei

2019

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Combining ASNARO-2 XSAR HH and Sentinel-1 C-SAR VH/VV Polarization Data for Improved Crop Mapping

Remote sensing (Basel, Switzerland), 2019-08, Vol.11 (16), p.1920

Sonobe, Rei

2019

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Carotenoid Content Estimation in Tea Leaves Using Noisy Reflectance Data

Remote sensing (Basel, Switzerland), 2023-09, Vol.15 (17), p.4303

2023

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Applying Variable Selection Methods and Preprocessing Techniques to Hyperspectral Reflectance Data to Estimate Tea Cultivar Chlorophyll Content

Remote sensing (Basel, Switzerland), 2023-01, Vol.15 (1), p.19

2023

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Crop classification from Sentinel-2-derived vegetation indices using ensemble learning

Journal of applied remote sensing, 2018-05, Vol.12 (2), p.1

2018

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Estimation of Leaf Chlorophyll a, b and Carotenoid Contents and Their Ratios Using Hyperspectral Reflectance

Remote sensing (Basel, Switzerland), 2020-10, Vol.12 (19), p.3265

2020

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Crop classification using spectral indices derived from Sentinel-2A imagery

Journal of information and telecommunication (Print), 2020-01, Vol.4 (1), p.67-90

2020

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Towards a Universal Hyperspectral Index to Assess Chlorophyll Content in Deciduous Forests

Remote sensing (Basel, Switzerland), 2017-02, Vol.9 (3), p.191

2017

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Laboratory of Macroecology, Faculty of Agriculture, Shizuoka University

Journal of The Remote Sensing Society of Japan, 2019/02/28, Vol.39(1), pp.75-76

SONOBE, Rei

2019

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Assessing the suitability of data from Sentinel-1A and 2A for crop classification

GIScience and remote sensing, 2017-11, Vol.54 (6), p.918-938

2017

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Potential of spectroscopic analyses for non-destructive estimation of tea quality-related metabolites in fresh new leaves

Scientific reports, 2021-02, Vol.11 (1), p.4169-4169, Article 4169

2021

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Non-Destructive Detection of Tea Leaf Chlorophyll Content Using Hyperspectral Reflectance and Machine Learning Algorithms

Plants (Basel), 2020-03, Vol.9 (3), p.368

2020

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Estimating leaf carotenoid contents of shade-grown tea using hyperspectral indices and PROSPECT-D inversion

International journal of remote sensing, 2018-03, Vol.39 (5), p.1306-1320

2018

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Random forest classification of crop type using multi-temporal TerraSAR-X dual-polarimetric data

Remote sensing letters, 2014-02, Vol.5 (2), p.157-164

2014

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Monitoring Photosynthetic Pigments of Shade-Grown Tea from Hyperspectral Reflectance

Canadian journal of remote sensing, 2018-03, Vol.44 (2), p.104-112

2018

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Evaluation of a One-Dimensional Convolution Neural Network for Chlorophyll Content Estimation Using a Compact Spectrometer

Remote sensing (Basel, Switzerland), 2022-04, Vol.14 (9), p.1997

2022

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Hyperspectral wavelength selection for estimating chlorophyll content of muskmelon leaves

European journal of remote sensing, 2021-01, Vol.54 (1), p.513-524

2021

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Assessing hyperspectral indices for tracing chlorophyll fluorescence parameters in deciduous forests

Journal of environmental management, 2018-12, Vol.227, p.172-180

2018

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Using spectral reflectance to estimate leaf chlorophyll content of tea with shading treatments

Biosystems engineering, 2018-11, Vol.175, p.168-182

2018

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Evaluating metrics derived from Landsat 8 OLI imagery to map crop cover

Geocarto international, 2019-07, Vol.34 (8), p.839-855

2019

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Nondestructive assessments of carotenoids content of broadleaved plant species using hyperspectral indices

Computers and electronics in agriculture, 2018-02, Vol.145, p.18-26

2018

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Dissection of hyperspectral reflectance to estimate nitrogen and chlorophyll contents in tea leaves based on machine learning algorithms

Scientific reports, 2020-10, Vol.10 (1), p.17360-17360, Article 17360

2020

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Hyperspectral reflectance sensing for quantifying leaf chlorophyll content in wasabi leaves using spectral pre-processing techniques and machine learning algorithms

International journal of remote sensing, 2021-02, Vol.42 (4), p.1311-1329

2021

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Assessing the xanthophyll cycle in natural beech leaves with hyperspectral reflectance

Functional plant biology : FPB, 2016-01, Vol.43 (5), p.438

2016

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Extreme Learning Machine-based Crop Classification using ALOS/PALSAR Images

Japan Agricultural Research Quarterly: JARQ, 2015/10/01, Vol.49(4), pp.377-381

2015

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Parcel-Based Crop Classification Using Multi-Temporal TerraSAR-X Dual Polarimetric Data

Combining ASNARO-2 XSAR HH and Sentinel-1 C-SAR VH/VV Polarization Data for Improved Crop Mapping

Carotenoid Content Estimation in Tea Leaves Using Noisy Reflectance Data

Applying Variable Selection Methods and Preprocessing Techniques to Hyperspectral Reflectance Data to Estimate Tea Cultivar Chlorophyll Content

Crop classification from Sentinel-2-derived vegetation indices using ensemble learning

Estimation of Leaf Chlorophyll a, b and Carotenoid Contents and Their Ratios Using Hyperspectral Reflectance

Crop classification using spectral indices derived from Sentinel-2A imagery

Towards a Universal Hyperspectral Index to Assess Chlorophyll Content in Deciduous Forests

Laboratory of Macroecology, Faculty of Agriculture, Shizuoka University

Assessing the suitability of data from Sentinel-1A and 2A for crop classification

Potential of spectroscopic analyses for non-destructive estimation of tea quality-related metabolites in fresh new leaves

Non-Destructive Detection of Tea Leaf Chlorophyll Content Using Hyperspectral Reflectance and Machine Learning Algorithms

Estimating leaf carotenoid contents of shade-grown tea using hyperspectral indices and PROSPECT-D inversion

Random forest classification of crop type using multi-temporal TerraSAR-X dual-polarimetric data

Monitoring Photosynthetic Pigments of Shade-Grown Tea from Hyperspectral Reflectance

Evaluation of a One-Dimensional Convolution Neural Network for Chlorophyll Content Estimation Using a Compact Spectrometer

Hyperspectral wavelength selection for estimating chlorophyll content of muskmelon leaves

Assessing hyperspectral indices for tracing chlorophyll fluorescence parameters in deciduous forests

Using spectral reflectance to estimate leaf chlorophyll content of tea with shading treatments

Evaluating metrics derived from Landsat 8 OLI imagery to map crop cover

Nondestructive assessments of carotenoids content of broadleaved plant species using hyperspectral indices

Dissection of hyperspectral reflectance to estimate nitrogen and chlorophyll contents in tea leaves based on machine learning algorithms

Hyperspectral reflectance sensing for quantifying leaf chlorophyll content in wasabi leaves using spectral pre-processing techniques and machine learning algorithms

Assessing the xanthophyll cycle in natural beech leaves with hyperspectral reflectance

Extreme Learning Machine-based Crop Classification using ALOS/PALSAR Images

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