Vision

Map Our World

Research Interests

I use near-surface and satellite remote sensing to capture and understand the spatial and temporal variations of terrestrial ecosystems at regional and global scales.

Recruitment: We are recruiting highly motivated Ph.D. students and postdocs with full supports in the coming year. Details are available right now: HERE.

Education

Nanjing Tech University Cartography and Geographic Information System B.S., 2007

Nanjing University Cartography and Geographic Information System M.A., 2010

Chinese Academy of Sciences Cartography and Geographic Information System Ph.D., 2014

Previous Appointments

Seoul National University Postdoc Researcher 2014 - 2017

University of Illinois at Urbana Champaign Postdoc Fellow 2018 - 2020

Peer-Reviewed Publications

*Denotes corresponding authorship.

[46] Wang, S., Guan, K., Zhang, C., Jiang, C., Zhou, Q., Li, K., Qin, Z., Ainsworth, E. A., He, J., Wu, J., Schaefer, D., Gentry, L. E., Margenot, A. J., & Herzberger, L. (2023). Airborne hyperspectral imaging of cover crops through radiative transfer process-guided machine learning. Remote Sensing of Environment, 285, 113386. https://doi.org/10.1016/J.RSE.2022.113386

[45] Wang, S., Guan, K., Zhang, C., Zhou, Q., Wang, S., Wu, X., Jiang, C., Peng, B., Mei, W., Li, K., Li, Z., Yang, Y., Zhou, W., Huang, Y., & Ma, Z. (2023). Cross-scale sensing of field-level crop residue cover: Integrating field photos, airborne hyperspectral imaging, and satellite data. Remote Sensing of Environment, 285, 113366. https://doi.org/10.1016/j.rse.2022.113366

[44] Zhou, Q., Guan, K., Wang, S., Jiang, C., Huang, Y., Peng, B., Chen, Z., Wang, S., Hipple, J., Schaefer, D., Qin, Z., Stroebel, S., Coppess, J., Khanna, M., & Cai, Y. (2022). Recent rapid increase of cover crop adoption across the U.S. Midwest detected by fusing multi‐source satellite data. Geophysical Research Letters, 49(22), e2022GL100249. https://doi.org/10.1029/2022gl100249

[43] Wu, G., Guan, K., Jiang, C., Kimm, H., Miao, G., Bernacchi, C. J., Moore, C. E., Ainsworth, E. A., Yang, X., Berry, J. A., Frankenberg, C., & Chen, M. (2022). Attributing differences of solar-induced chlorophyll fluorescence (SIF)-gross primary production (GPP) relationships between two C4 crops: corn and miscanthus. Agricultural and Forest Meteorology, 323, 109046. https://doi.org/10.1016/j.agrformet.2022.109046

[42] Wu, G., Jiang, C.*, Kimm, H., Wang, S., Bernacchi, C., Moore, C. E., Suyker, A., Yang, X., Magney, T., Frankenberg, C., Ryu, Y., Dechant, B., & Guan, K.* (2022). Difference in seasonal peak timing of soybean far-red SIF and GPP explained by canopy structure and chlorophyll content. Remote Sensing of Environment, 279, 113104. https://doi.org/10.1016/j.rse.2022.113104

[41] Müller, J., Faybishenko, B., Agarwal, D., Bailey, S., Jiang, C., Ryu, Y., Tull, C., & Ramakrishnan, L. (2021). Assessing data change in scientific datasets. Concurrency and Computation: Practice and Experience, 33(16), e6245. https://doi.org/10.1002/cpe.6245

[40] Wang, S., Guan, K., Wang, Z., Ainsworth, E. A., Zheng, T., Townsend, P. A., Liu, N., Nafziger, E., Masters, M. D., Li, K., Wu, G., & Jiang, C. (2021). Airborne hyperspectral imaging of nitrogen deficiency on crop traits and yield of maize by machine learning and radiative transfer modeling. International Journal of Applied Earth Observation and Geoinformation, 105, 102617. https://doi.org/10.1016/j.jag.2021.102617

[39] Kimm, H., Guan, K., Jiang, C., Miao, G., Wu, G., Suyker, A. E., Ainsworth, E. A., Bernacchi, C. J., Montes, C. M., Berry, J. A., Yang, X., Frankenberg, C., Chen, M., & Köhler, P. (2021). A physiological signal derived from sun-induced chlorophyll fluorescence quantifies crop physiological response to environmental stresses in the U.S. Corn Belt. Environmental Research Letters, 16(12), 124051. https://doi.org/10.1088/1748-9326/ac3b16

[38] Li, K., Guan, K.*, Jiang, C.*, Wang, S., Peng, B., & Cai, Y. (2021). Evaluation of Four New Land Surface Temperature (LST) Products in the U.S. Corn Belt: ECOSTRESS, GOES-R, Landsat, and Sentinel-3. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 9931–9945. https://doi.org/10.1109/JSTARS.2021.3114613

[37] Jiang, C.*; Guan, K.*; Khanna, M.*; Chen, L.; Peng, J. Assessing Marginal Land Availability Based on Land Use Change Information in the Contiguous United States. Environmental Science & Technology. 2021, 55 (15). https://doi.org/10.1021/acs.est.1c02236.

[36] Zhang, J., Guan, K., Peng, B., Pan, M., Zhou, W., Jiang, C., Kimm, H., Franz, T. E., Grant, R. F., Yang, Y., Rudnick, D. R., Heeren, D. M., Suyker, A. E., Bauerle, W. L., & Miner, G. L. (2021). Sustainable irrigation based on co-regulation of soil water supply and atmospheric evaporative demand. Nature Communications, 12(1), 1–10. https://doi.org/10.1038/s41467-021-25254-7

[35] Khanna, M.; Chen, L.; Basso, B.; Cai, X.; Field, J.; Guan, K.; Jiang, C.; Lark, T.; Richard, T.; Spawn, S.; Yang, P.; Zipp, K. Redefining Marginal Lands for Bioenergy Crop Production. GCB Bioenergy. 2021, p12877. https://doi.org/10.1111/gcbb.12877.

[34] Zhou, W., Guan, K., Peng, B., Tang, J., Jin, Z., Jiang, C., Grant, R. and Mezbahuddin, S. Quantifying carbon budget, crop yields and their responses to environmental variability using the ecosys model for U.S. Midwestern agroecosystems, Agric. For. Meteorol. 2021, 307, 108521, doi:10.1016/J.AGRFORMET.2021.108521.

[33] Zhang, J.; Guan, K.; Peng, B.; Jiang, C.; Zhou, W.; Yang, Y.; Pan, M.; Franz, T. E.; Heeren, D. M.; Rudnick, D. R.; Abimbola, O.; Kimm, H.; Caylor, K.; Good, S.; Khanna, M.; Gates, J.; Cai, Y. Challenges and Opportunities in Precision Irrigation Decision-Support Systems for Center Pivots. Environmental Research Letters. IOP Publishing May 1, 2021, p 53003. https://doi.org/10.1088/1748-9326/abe436.

[32] Jiang, C.*; Guan, K.*; Wu, G.; Peng, B.; Wang, S. A Daily, 250 m, and Real-Time Gross Primary Productivity Product (2000–Present) Covering the Contiguous United States. Earth Syst. Sci. Data 2021, 13 (2), 281–298. https://doi.org/10.5194/essd-2020-36.

[31] Wu, G.; Guan, K.; Li, Y.; Novick, K. A.; Feng, X.; McDowell, N. G.; Konings, A. G.; Thompson, S. E.; Kimball, J. S.; De Kauwe, M. G.; Ainsworth, E. A.; Jiang, C. Interannual Variability of Ecosystem Iso/Anisohydry Is Regulated by Environmental Dryness. New Phytol. 2021, 229 (5), 2562–2575. https://doi.org/10.1111/nph.17040.

[30] Yang, Y.; Guan, K.; Peng, B.; Pan, M.; Jiang, C.; Franz, T. E. High-Resolution Spatially Explicit Land Surface Model Calibration Using Field-Scale Satellite-Based Daily Evapotranspiration Product. J. Hydrol. 2021, 596 (November 2020), 125730. https://doi.org/10.1016/j.jhydrol.2020.125730.

[29] Wang, S.; Guan, K.; Wang, Z.; Ainsworth, E. A.; Zheng, T.; Townsend, P. A.; Li, K.; Moller, C.; Wu, G.; Jiang, C. Unique Contributions of Chlorophyll and Nitrogen to Predict Crop Photosynthetic Capacity from Leaf Spectroscopy. J. Exp. Bot. 2021, 72 (2), 341–354. https://doi.org/10.1093/jxb/eraa432.

[28] Zhou, W.; Guan, K.; Peng, B.; Shi, J.; Jiang, C.; Wardlow, B.; Pan, M.; Kimball, J. S.; Franz, T. E.; Gentine, P.; He, M.; Zhang, J. Connections between the Hydrological Cycle and Crop Yield in the Rainfed U.S. Corn Belt. J. Hydrol. 2020, 590 (August), 125398. https://doi.org/10.1016/j.jhydrol.2020.125398.

[27] Jiang, C.*, Ryu, Y.*, Wang, H., Keenan, T.F., 2020. An optimality-based model explains seasonal variation in C3 plant photosynthetic capacity. Glob. Chang. Biol. 26, 6493–6510. https://doi.org/10.1111/gcb.15276

[26] Forzieri, G.; Miralles, D. G.; Ciais, P.; Alkama, R.; Ryu, Y.; Duveiller, G.; Zhang, K.; Robertson, E.; Kautz, M.; Martens, B.; Jiang, C.; Arneth, A.; Georgievski, G.; Li, W.; Ceccherini, G.; Anthoni, P.; Lawrence, P.; Wiltshire, A.; Pongratz, J.; Piao, S.; Sitch, S.; Goll, D. S.; Arora, V. K.; Lienert, S.; Lombardozzi, D.; Kato, E.; Nabel, J. E. M. S.; Tian, H.; Friedlingstein, P.; Cescatti, A. Increased Control of Vegetation on Global Terrestrial Energy Fluxes. Nat. Clim. Chang. 2020, 10 (4), 356–362. https://doi.org/10.1038/s41558-020-0717-0.

[25] Pei, Y.; Dong, J.; Zhang, Y.; Yang, J.; Zhang, Y.; Jiang, C.; Xiao, X. Performance of Four State-of-the-Art GPP Products (VPM, MOD17, BESS and PML) for Grasslands in Drought Years. Ecol. Inform. 2020, 56, 101052. https://doi.org/10.1016/j.ecoinf.2020.101052.

[24] Jiang, C.*, Guan, K.*, Pan, M., Ryu, Y., Peng, B., Wang, S., 2020. BESS-STAIR: a framework to estimate daily, 30-meter, and all weather crop evapotranspiration using multi-source satellite data for the U.S. Corn Belt. Hydrol. Earth Syst. Sci. 24, 1251–1273. https://doi.org/10.5194/hess-2019-376

[23] Wu, G., Guan, K.*, Jiang, C.*, Peng, B., Kimm, H., Chen, M., Yang, X., Wang, S., Suyker, A.E., Bernacchi, C.J., Moore, C.E., Zeng, Y., Berry, J.A., Cendrero-Mateo, M.P., 2020. Radiance-based NIRv as a proxy for GPP of corn and soybean. Environ. Res. Lett. 15, 034009. https://doi.org/10.1088/1748-9326/ab65cc

[22] Kimm, H.; Guan, K.; Jiang, C.; Peng, B.; Gentry, L. F.; Wilkin, S. C.; Wang, S.; Cai, Y.; Bernacchi, C. J.; Peng, J.; Luo, Y. Deriving High-Spatiotemporal-Resolution Leaf Area Index for Agroecosystems in the U.S. Corn Belt Using Planet Labs CubeSat and STAIR Fusion Data. Remote Sens. Environ. 2020, 239, 111615. https://doi.org/10.1016/j.rse.2019.111615.

[21] Wang, C.; Guan, K.; Peng, B.; Chen, M.; Jiang, C.; Zeng, Y.; Wu, G.; Wang, S.; Wu, J.; Yang, X.; Frankenberg, C.; Köhler, P.; Berry, J.; Bernacchi, C.; Zhu, K.; Alden, C.; Miao, G. Satellite Footprint Data from OCO-2 and TROPOMI Reveal Significant Spatio-Temporal and Inter-Vegetation Type Variabilities of Solar-Induced Fluorescence Yield in the U.S. Midwest. Remote Sens. Environ. 2020, 241 (February), 111728. https://doi.org/10.1016/j.rse.2020.111728.

[20] Peng, B.; Guan, K.; Zhou, W.; Jiang, C.; Frankenberg, C.; Sun, Y.; He, L.; Köhler, P. Assessing the Benefit of Satellite-Based Solar-Induced Chlorophyll Fluorescence in Crop Yield Prediction. Int. J. Appl. Earth Obs. Geoinf. 2020, 90 (December 2019), 102126. https://doi.org/10.1016/j.jag.2020.102126.

[19] Jiang, C.*, Fang, H., 2019. GSV: a general model for hyperspectral soil reflectance simulation. Int. J. Appl. Earth Obs. Geoinf. 83, 101932. https://doi.org/10.1016/j.jag.2019.101932

[18] Wei, J.; Chen, Y.; Gu, Q.; Jiang, C.; Ma, M.; Song, L.; Tang, X. Potential of the Remotely-Derived Products in Monitoring Ecosystem Water Use Efficiency across Grasslands in Northern China. Int. J. Remote Sens. 2019, 40 (16), 6203–6223. https://doi.org/10.1080/01431161.2019.1587208.

[17] Yuan, W.; Zheng, Y.; Piao, S.; Ciais, P.; Lombardozzi, D.; Wang, Y.; Ryu, Y.; Chen, G.; Dong, W.; Hu, Z.; Jain, A. K.; Jiang, C.; Kato, E.; Li, S.; Lienert, S.; Liu, S.; Nabel, J. E. M. S.; Qin, Z.; Quine, T.; Sitch, S.; Smith, W. K.; Wang, F.; Wu, C.; Xiao, Z.; Yang, S. Increased Atmospheric Vapor Pressure Deficit Reduces Global Vegetation Growth. Sci. Adv. 2019, 5 (8), eaax1396. https://doi.org/10.1126/sciadv.aax1396.

[16] Kim, J., Ryu, Y., Jiang, C., & Hwang, Y. (2019). Continuous observation of vegetation canopy dynamics using an integrated low-cost, near-surface remote sensing system. Agricultural and Forest Meteorology, 264(September 2018), 164–177. https://doi.org/10.1016/j.agrformet.2018.09.014

[15] Baldocchi, D.; Dralle, D.; Jiang, C.; Ryu, Y. How Much Water Is Evaporated Across California?: A Multi-Year Assessment Using a Biophysical Model Forced with Satellite Remote Sensing Data. Water Resour. Res. 2019, 55 (4), 2722–2741. https://doi.org/10.1029/2018WR023884.

[14] Yang, K.; Ryu, Y.; Dechant, B.; Berry, J. A.; Hwang, Y.; Jiang, C.; Kang, M.; Kim, J.; Kimm, H.; Kornfeld, A.; Yang, X. Sun-Induced Chlorophyll Fluorescence Is More Strongly Related to Absorbed Light than to Photosynthesis at Half-Hourly Resolution in a Rice Paddy. Remote Sens. Environ. 2018, 216 (June), 658–673. https://doi.org/10.1016/j.rse.2018.07.008.

[13] Ryu, Y.; Jiang, C.; Kobayashi, H.; Detto, M. MODIS-Derived Global Land Products of Shortwave Radiation and Diffuse and Total Photosynthetically Active Radiation at 5 Km Resolution from 2000. Remote Sens. Environ. 2018, 204 (January 2018), 812–825. https://doi.org/10.1016/j.rse.2017.09.021.

[12] Luo, X.; Keenan, T. F.; Fisher, J. B.; Jiménez-Muñoz, J.-C.; Chen, J. M.; Jiang, C.; Ju, W.; Perakalapudi, N.-V.; Ryu, Y.; Tadić, J. M. The Impact of the 2015/2016 El Niño on Global Photosynthesis Using Satellite Remote Sensing. Philos. Trans. R. Soc. B Biol. Sci. 2018, 373 (1760), 20170409. https://doi.org/10.1098/rstb.2017.0409.

[11] Huang, Y.; Ryu, Y.; Jiang, C.; Kimm, H.; Kim, S.; Kang, M.; Shim, K. BESS-Rice: A Remote Sensing Derived and Biophysical Process-Based Rice Productivity Simulation Model. Agric. For. Meteorol. 2018, 256–257 (March), 253–269. https://doi.org/10.1016/j.agrformet.2018.03.014.

[10] Jiang, C.; Ryu, Y.; Fang, H.; Myneni, R.; Claverie, M.; Zhu, Z. Inconsistencies of Interannual Variability and Trends in Long-Term Satellite Leaf Area Index Products. Glob. Chang. Biol. 2017, 23 (10), 4133–4146. https://doi.org/10.1111/gcb.13787.

[9] Jiang, C.; Ryu, Y. Multi-Scale Evaluation of Global Gross Primary Productivity and Evapotranspiration Products Derived from Breathing Earth System Simulator (BESS). Remote Sens. Environ. 2016, 186, 528–547. https://doi.org/10.1016/j.rse.2016.08.030.

[8] Hwang, Y.; Ryu, Y.; Kimm, H.; Jiang, C.; Lang, M.; Macfarlane, C.; Sonnentag, O. Correction for Light Scattering Combined with Sub-Pixel Classification Improves Estimation of Gap Fraction from Digital Cover Photography. Agric. For. Meteorol. 2016, 222, 32–44. https://doi.org/10.1016/j.agrformet.2016.03.008.

[7] Lee, S.; Ryu, Y.; Jiang, C. Urban Heat Mitigation by Roof Surface Materials during the East Asian Summer Monsoon. Environ. Res. Lett. 2015, 10 (12), 124012. https://doi.org/10.1088/1748-9326/10/12/124012.

[6] Fang, H.; Li, W.; Wei, S.; Jiang, C. Seasonal Variation of Leaf Area Index (LAI) over Paddy Rice Fields in NE China: Intercomparison of Destructive Sampling, LAI-2200, Digital Hemispherical Photography (DHP), and AccuPAR Methods. Agric. For. Meteorol. 2014, 198–199, 126–141. https://doi.org/10.1016/j.agrformet.2014.08.005.

[5] Fang, H.; Jiang, C.; Li, W.; Wei, S.; Baret, F.; Chen, J. M.; Garcia-Haro, J.; Liang, S.; Liu, R.; Myneni, R. B.; Pinty, B.; Xiao, Z.; Zhu, Z. Characterization and Intercomparison of Global Moderate Resolution Leaf Area Index (LAI) Products: Analysis of Climatologies and Theoretical Uncertainties. J. Geophys. Res. Biogeosciences 2013, 118 (2), 529–548. https://doi.org/10.1002/jgrg.20051.

[4] Fang, H.; Wei, S.; Jiang, C.; Scipal, K. Theoretical Uncertainty Analysis of Global MODIS, CYCLOPES, and GLOBCARBON LAI Products Using a Triple Collocation Method. Remote Sens. Environ. 2012, 124, 610–621. https://doi.org/10.1016/j.rse.2012.06.013.

[3] Jiang, C.; Fang, H.; Wei, S. Review of Land Surface Roughness Parameterization Study. Adv. Earth Sci. (In Chinese). 2012, 27 (3), 292–303.

[2] Jiang, C.; Li, M.; Liu, Y. Full Automatic Method for Coastal Water Information Extraction from Remote Sensing Image. Acta Geod. Cartogr. Sin. (In Chinese). 2011, 40 (3), 332–340.

[1] Jiang, C.; Li, M.; Li, F.; Li, X.; Liu, Y. Construction of Geographic Information System (GIS) Virtual Inter-Active Experiment Zone. Geomatics World. (In Chinese). 2010, No. 2, 84–89.