| Retrieving leaf chlorophyll content using a matrix-based vegetation index combination approach M Xu, R Liu, JM Chen, Y Liu, R Shang, W Ju, C Wu, W Huang Remote Sensing of Environment 224, 60-73, 2019 | 117 | 2019 |
| The relationship between threshold-based and inflexion-based approaches for extraction of land surface phenology R Shang, R Liu, M Xu, Y Liu, L Zuo, Q Ge Remote Sensing of Environment 199, 167-170, 2017 | 48 | 2017 |
| Retrieving global leaf chlorophyll content from MERIS data using a neural network method M Xu, R Liu, JM Chen, R Shang, Y Liu, L Qi, H Croft, W Ju, Y Zhang, Y He, ... ISPRS Journal of Photogrammetry and Remote Sensing 192, 66-82, 2022 | 16 | 2022 |
| A 21-year time series of global leaf chlorophyll content maps from MODIS imagery M Xu, R Liu, JM Chen, Y Liu, A Wolanin, H Croft, L He, R Shang, W Ju, ... IEEE Transactions on Geoscience and Remote Sensing 60, 1-13, 2022 | 16 | 2022 |
| China’s current forest age structure will lead to weakened carbon sinks in the near future R Shang, JM Chen, M Xu, X Lin, P Li, G Yu, N He, L Xu, P Gong, L Liu, ... The Innovation 4 (6), 2023 | 15 | 2023 |
| Determining the start of the growing season from MODIS data in the Indian Monsoon Region: Identifying available data in the rainy season and modeling the varied vegetation … R Shang, R Liu, M Xu, Y Liu, J Dash, Q Ge Remote Sensing 10 (1), 122, 2018 | 13 | 2018 |
| An algorithm differentiating sunlit and shaded leaves for improving canopy conductance and vapotranspiration estimates J Li, W Ju, W He, H Wang, Y Zhou, M Xu Journal of Geophysical Research: Biogeosciences 124 (4), 807-824, 2019 | 10 | 2019 |
| Next step in vegetation remote sensing: synergetic retrievals of canopy structural and leaf biochemical parameters JM Chen, M Xu, R Wang, D Li, R Liu, W Ju, T Cheng New Thinking in GIScience, 207-220, 2022 | 6 | 2022 |
| Declining global sensitivity of stomatal conductance to photosynthesis J Leng, JM Chen, W Li, X Luo, M Xu, C Rogers, Y Yan | 1 | 2024 |
| Improved estimation of the underestimated GEDI footprint LAI in dense forests L Liang, R Shang, JM Chen, M Xu, H Zeng Geo-spatial Information Science, 1-16, 2023 | 1 | 2023 |
| Evaluation of five models for constructing forest NPP-age relationships in China based on 3121 field survey samples P Li, R Shang, JM Chen, M Xu, X Lin, G Yu, N He, L Xu Biogeosciences Discussions 2023, 1-22, 2023 | 1 | 2023 |
| Global datasets of hourly carbon and water fluxes simulated using a satellite-based process model with dynamic parameterizations J Leng, JM Chen, W Li, X Luo, M Xu, J Liu, R Wang, C Rogers, B Li, Y Yan Earth System Science Data Discussions 2023, 1-23, 2023 | 1 | 2023 |
| LACC2. 0: Improving the LACC Algorithm for Reconstructing Satellite-Derived Time Series of Vegetation Biochemical Parameters M Xu, R Shang, JM Chen, L Zeng Remote Sensing 15 (13), 3277, 2023 | 1 | 2023 |
| Comparative assessment of leaf photosynthetic capacity datasets for estimating terrestrial gross primary productivity M Xu, JM Chen, Y Liu, R Wang, R Shang, J Leng, L Shu, J Liu, R Liu, ... Science of The Total Environment 926, 171400, 2024 | | 2024 |
| Simultaneous estimation of leaf directional-hemispherical reflectance and transmittance from multi-angular canopy reflectance J Wang, JM Chen, F Qiu, W Fan, M Xu, R Wang Remote Sensing of Environment 304, 114025, 2024 | | 2024 |
| Global datasets of hourly carbon and water fluxes simulated using a satellite-based process model with dynamic parameterizations J Leng, JM Chen, W Li, X Luo, M Xu, J Liu, R Wang, C Rogers, B Li, Y Yan Earth System Science Data 16 (3), 1283-1300, 2024 | | 2024 |
| Advances in Global Mapping of Leaf Chlorophyll Content By Land Cover Type JM Chen, H Croft, M Xu, R Wang AGU Fall Meeting Abstracts 2022, B35A-01, 2022 | | 2022 |
| Global Leaf Chlorophyll Content Mapping from Multi-spectral Remote Sensing Data M Xu, R Liu, Y Liu, JM Chen, A Wolanin, W Ju AGU Fall Meeting Abstracts 2019, GC52C-07, 2019 | | 2019 |
| Correction: Shang, R.; Liu, R.; Xu, M.; Liu, Y.; Dash, J.; Ge, Q. Determining the Start of the Growing Season from MODIS Data in the Indian Monsoon Region: Identifying … R Shang, R Liu, M Xu, Y Liu, J Dash, Q Ge Remote Sensing 11 (8), 939, 2019 | | 2019 |
| Globally mapping seasonal fluctuations of the open surface water extent independent of cloud mask using MODIS data R Shang, R Liu, Y Liu, M Xu, L Zuo AGU Fall Meeting Abstracts 2016, H51H-1625, 2016 | | 2016 |
Jing M ChenDepartment of Geography, University of TorontoVerified email at geog.utoronto.ca
