发布人：江冲亚 发布日期: 2023-03-01 浏览次数：

姓       名：江冲亚
职       称：教授
办公地址：生命科学楼南楼A5011室
办公电话：025-84399935
电子邮箱：chongya@njau.edu.cn
个人愿景：绘制中国每块田的昨天、今天、明天
研究方向：农情遥感监测、农业信息工程
招生背景：农学、生态学、遥感、地信、计算机、软件工程

教育经历：

工作经历：

科研项目：

发表论文：

Wu, G., Guan, K., Jiang, C., Kimm, H., Miao, G., Yang, X., Bernacchi, C.J., Sun, X., Suyker, A.E., Moore, C.E., 2023. Can upscaling ground nadir SIF to eddy covariance footprint improve the relationship between SIF and GPP in croplands? Agricultural and Forest Meteorology 338, 109532. https://doi.org/10.1016/j.agrformet.2023.109532 

Zhang, J., Guan, K., Zhou, W., Jiang, C., Peng, B., Pan, M., Grant, R.F., Franz, T.E., Suyker, A., Yang, Y., Chen, X., Lin, K., Ma, Z., 2023. Combining Remotely Sensed Evapotranspiration and an Agroecosystem Model to Estimate Center-Pivot Irrigation Water Use at High Spatio-Temporal Resolution. Water Resources Research 59, e2022WR032967. https://doi.org/10.1029/2022WR032967

Zhou, Q., Wang, S., Liu, N., Townsend, P.A., Jiang, C., Peng, B., Verhoef, W., Guan, K., 2023. Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators. ISPRS Journal of Photogrammetry and Remote Sensing 196, 386–401. https://doi.org/10.1016/j.isprsjprs.2022.11.016 

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

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

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

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

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

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

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

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

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

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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

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

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.

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.

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.

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

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.