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Takeshi Ise
Takeshi Ise
Associate Professor, FSERC, Kyoto University, Japan
Verified email at kais.kyoto-u.ac.jp - Homepage
Title
Cited by
Cited by
Year
MIROC-ESM 2010: Model description and basic results of CMIP5-20c3m experiments
S Watanabe, T Hajima, K Sudo, T Nagashima, T Takemura, H Okajima, ...
Geoscientific Model Development 4 (4), 845-872, 2011
11612011
High sensitivity of peat decomposition to climate change through water-table feedback
T Ise, AL Dunn, SC Wofsy, PR Moorcroft
Nature Geoscience 1 (11), 763-766, 2008
4582008
MIROC-ESM 2010: model description and basic results of CMIP5-20c3m experiments, Geosci. Model Dev., 4, 845–872
S Watanabe, T Hajima, K Sudo, T Nagashima, T Takemura, H Okajima, ...
3372011
Early stage litter decomposition across biomes
I Djukic, S Kepfer-Rojas, IK Schmidt, KS Larsen, C Beier, B Berg, ...
Science of the total environment 628, 1369-1394, 2018
2592018
The global-scale temperature and moisture dependencies of soil organic carbon decomposition: an analysis using a mechanistic decomposition model
T Ise, PR Moorcroft
Biogeochemistry 80, 217-231, 2006
1882006
Explainable identification and mapping of trees using UAV RGB image and deep learning
M Onishi, T Ise
Scientific reports 11 (1), 903, 2021
1732021
MIROC-ESM: model description and basic results of CMIP5-20c3m experiments
S Watanabe, T Hajima, K Sudo, T Nagashima, T Takemura, H Okajima, ...
Geosci. Model Dev. Discuss 4 (2), 1063-1128, 2011
1322011
Comparison of modeling approaches for carbon partitioning: impact on estimates of global net primary production and equilibrium biomass of woody vegetation from MODIS GPP
T Ise, CM Litton, CP Giardina, A Ito
Journal of Geophysical Research: Biogeosciences 115 (G4), 2010
892010
Effect of plant dynamic processes on African vegetation responses to climate change: Analysis using the spatially explicit individual‐based dynamic global vegetation model …
H Sato, T Ise
Journal of Geophysical Research: Biogeosciences 117 (G3), 2012
612012
Effect of plant dynamic processes on African vegetation responses to climate change: Analysis using the spatially explicit individual‐based dynamic global vegetation model …
H Sato, T Ise
Journal of Geophysical Research: Biogeosciences 117 (G3), 2012
612012
Automatic classification of trees using a UAV onboard camera and deep learning
M Onishi, T Ise
arXiv preprint arXiv:1804.10390, 2018
602018
Forecasting climatic trends using neural networks: an experimental study using global historical data
T Ise, Y Oba
Frontiers in Robotics and AI 6, 446979, 2019
362019
Identifying 3 moss species by deep learning, using the" chopped picture" method
T Ise, M Minagawa, M Onishi
arXiv preprint arXiv:1708.01986, 2017
332017
Identifying the vegetation type in Google Earth images using a convolutional neural network: a case study for Japanese bamboo forests
S Watanabe, K Sumi, T Ise
BMC ecology 20, 1-14, 2020
302020
Simulating boreal forest dynamics from perspectives of ecophysiology, resource availability, and climate change
T Ise, PR Moorcroft
Ecological research 25, 501-511, 2010
262010
MIROC-ESM 2010: Model description and basic results of CMIP5-20c3m experiments. Geosci. Model Dev. 2011; 4: 845–872. doi: 10.5194
S Watanabe, T Hajima, K Sudo, T Nagashima, T Takemura, H Okajima, ...
gmd-4-845-2011.[CrossRef][Google Scholar], 0
25
Reconciliation of top-down and bottom-up CO2 fluxes in Siberian larch forest
K Takata, PK Patra, A Kotani, J Mori, D Belikov, K Ichii, T Saeki, T Ohta, ...
Environmental Research Letters 12 (12), 125012, 2017
202017
Explainable deep learning reproduces a ‘professional eye’on the diagnosis of internal disorders in persimmon fruit
T Akagi, M Onishi, K Masuda, R Kuroki, K Baba, K Takeshita, T Suzuki, ...
Plant and Cell Physiology 61 (11), 1967-1973, 2020
192020
Climate change, allowable emission, and earth system response to representative concentration pathway scenarios
T Hajima, T Ise, K Tachiiri, E Kato, S Watanabe, M Kawamiya
Journal of the Meteorological Society of Japan. Ser. II 90 (3), 417-434, 2012
162012
Practicality and robustness of tree species identification using UAV RGB image and deep learning in temperate forest in Japan
M Onishi, S Watanabe, T Nakashima, T Ise
Remote Sensing 14 (7), 1710, 2022
142022
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Articles 1–20