Crop classification from Sentinel-2-derived vegetation indices using ensemble learning R Sonobe, Y Yamaya, H Tani, X Wang, N Kobayashi, K Mochizuki Journal of Applied Remote Sensing 12 (2), 026019-026019, 2018 | 169 | 2018 |
Assessing the suitability of data from Sentinel-1A and 2A for crop classification R Sonobe, Y Yamaya, H Tani, X Wang, N Kobayashi, K Mochizuki GIScience & Remote Sensing 54 (6), 918-938, 2017 | 156 | 2017 |
Crop classification using spectral indices derived from Sentinel-2A imagery N Kobayashi, H Tani, X Wang, R Sonobe Journal of Information and Telecommunication 4 (1), 67-90, 2020 | 138 | 2020 |
Random forest classification of crop type using multi-temporal TerraSAR-X dual-polarimetric data R Sonobe, H Tani, X Wang, N Kobayashi, H Shimamura Remote Sensing Letters 5 (2), 157-164, 2014 | 138 | 2014 |
Using spectral reflectance to estimate leaf chlorophyll content of tea with shading treatments R Sonobe, T Sano, H Horie Biosystems engineering 175, 168-182, 2018 | 71 | 2018 |
Parameter tuning in the support vector machine and random forest and their performances in cross-and same-year crop classification using TerraSAR-X R Sonobe, H Tani, X Wang, N Kobayashi, H Shimamura International Journal of Remote Sensing 35 (23), 7898-7909, 2014 | 66 | 2014 |
Estimation of Leaf Chlorophyll a, b and Carotenoid Contents and Their Ratios Using Hyperspectral Reflectance R Sonobe, H Yamashita, H Mihara, A Morita, T Ikka Remote Sensing 12 (19), 3265, 2020 | 59 | 2020 |
Discrimination of crop types with TerraSAR-X-derived information R Sonobe, H Tani, X Wang, N Kobayashi, H Shimamura Physics and Chemistry of the Earth, Parts A/B/C 83, 2-13, 2015 | 48 | 2015 |
Mapping crop cover using multi-temporal Landsat 8 OLI imagery R Sonobe, Y Yamaya, H Tani, X Wang, N Kobayashi, K Mochizuki International Journal of Remote Sensing 38 (15), 4348-4361, 2017 | 47 | 2017 |
Dissection of hyperspectral reflectance to estimate nitrogen and chlorophyll contents in tea leaves based on machine learning algorithms H Yamashita, R Sonobe, Y Hirono, A Morita, T Ikka Scientific reports 10 (1), 17360, 2020 | 44 | 2020 |
Non-destructive detection of tea leaf chlorophyll content using hyperspectral reflectance and machine learning algorithms R Sonobe, Y Hirono, A Oi Plants 9 (3), 368, 2020 | 43 | 2020 |
Classifying the severity of basal stem rot disease in oil palm plantations using WorldView-3 imagery and machine learning algorithms H Santoso, H Tani, X Wang, AE Prasetyo, R Sonobe International Journal of Remote Sensing 40 (19), 7624-7646, 2019 | 43 | 2019 |
Hyperspectral indices for quantifying leaf chlorophyll concentrations performed differently with different leaf types in deciduous forests R Sonobe, Q Wang Ecological Informatics 37, 1-9, 2017 | 38 | 2017 |
Towards a universal hyperspectral index to assess chlorophyll content in deciduous forests R Sonobe, Q Wang Remote Sensing 9 (3), 191, 2017 | 34 | 2017 |
Parcel-based crop classification using multi-temporal TerraSAR-X dual polarimetric data R Sonobe Remote Sensing 11 (10), 1148, 2019 | 33 | 2019 |
Hyperspectral reflectance sensing for quantifying leaf chlorophyll content in wasabi leaves using spectral pre-processing techniques and machine learning algorithms R Sonobe, H Yamashita, H Mihara, A Morita, T Ikka International Journal of Remote Sensing 42 (4), 1311-1329, 2021 | 31 | 2021 |
Estimating leaf carotenoid contents of shade-grown tea using hyperspectral indices and PROSPECT–D inversion R Sonobe, Y Miura, T Sano, H Horie International journal of remote sensing 39 (5), 1306-1320, 2018 | 31 | 2018 |
An experimental comparison between KELM and CART for crop classification using Landsat-8 OLI data R Sonobe, H Tani, X Wang Geocarto international 32 (2), 128-138, 2017 | 24 | 2017 |
Nondestructive assessments of carotenoids content of broadleaved plant species using hyperspectral indices R Sonobe, Q Wang Computers and electronics in agriculture 145, 18-26, 2018 | 21 | 2018 |
Quantifying chlorophyll-a and b content in tea leaves using hyperspectral reflectance and deep learning R Sonobe, Y Hirono, A Oi Remote Sensing Letters 11 (10), 933-942, 2020 | 20 | 2020 |