Education:
2010-2013: PhD
Environmental Engineering, Princeton University
Advisor: Dr. Eric F. Wood

2008-2010: Master of Art
Environmental Engineering, Princeton University
Advisor: Dr. Eric F. Wood

2004-2008: Bachelor of Science
Geography, Geoinformatics, Nanjing University
(with honor, GPA rank: 1/156)

Professional Experience:
2021-Present: Blue Waters Associate Professor (NRES, NCSA)
2021-Present: Founding Director, Agroecosystem Sustainability Center (iSEE, ACES)
2021-Present: Affiliated Professor at Computer Science
2016-Present: Affiliated Professor (Informatics, Geography)
2016-2021: Assistant Professor (NRES, NCSA)
University of Illinois at Urbana Champaign

2015-2016: Quantitative Researcher
The Climate Corporation

2013-2015: Postdoc Scholar
Earth System Science, Stanford University
Supervisor: Dr. David Lobell, Dr. Joe Berry

Selected Academic Awards:
2022: FoodShot Global Groundbreaker Prize, FoodShot Global and Foundation for Food & Agriculture Research (FFAR)

2022, Clarivate Analytics Highly Cited Researchers list

2022, Illinois Innovation Network (IIN) Innovator of the Year Awards

2021, Finalist of Pritzker Emerging Environmental Genius Award

2021, Blavatnik National Awards for Young Scientists Finalist
2021, Distinguished Promotion Award, University of Illinois Urbana Champaign

2021, Faculty Fellow of Environmental Sustainability, National Great Rivers Research and Education Center

2021, FFAR Seeding Solutions Award, FFAR

2021, Microsoft "AI for Earth" Research Award

2020, High-Performance-Computing (HPC) Innovation Excellence Award, Hyperion Research

2020, CAS Faculty Fellow, Center for Advanced Study, University of Illinois at Urbana Champaign

2019, Faculty Fellowship on Climate Risk, Gies College of Business, University of Illinois at Urbana Champaign

2019, Amazon "Earth on AWS" Award, Amazon

2019, SoAR Foundation's annual selection of scientists to represent the U.S. agricultural research, SoAR Foundation

2019, NSF CAREER Award, NSF

2018, AGU Global Environmental Change Early Career Award, American Geophysical Union (AGU)
Media: UIUC ACES, UIUC NCSA

2017/2019, Excellent Ranking Teacher, University of Illinois at Urbana Champaign

2016, NASA New Investigator Award, NASA

2016, Blue Waters Professorship, National Center for Supercomputing Applications, UIUC

2012, NASA Earth and Space Science Fellowship (NESSF), NASA

2012, Walbridge Fund Graduate Award, Princeton Environmental Institute, Princeton University

2012, Best Student Paper Award, Phenology 2012 Conference, Milwaukee, Wisconsin

2010, CUAHSI Pathfinnder Fellowship, Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI)

2007, National Undergraduate Scholarship (within 1%), Nanjing University, China

2006, Pan Xueping Scholarship (within 1%), Nanjing University, China

2007, Best Student Paper Award (2nd), 15th International Conference on Geoinformatics, Nanjing, China


Contact:
Email: kaiyuguan AT gmail DOT com;
              kaiyug AT illinois DOT edu.

Mail address:
Department of Natural Resources and Environmental Sciences
University of Illinois at Urbana-Champaign
W503, Turner Hall, 1102 S. Goodwin
Urbana, Illinois 61801


 Visitor Locations:

Last updated on February 6, 2023 by Kaiyu Guan
All rights reserved.

Kaiyu Guan
University of Illinois at Urbana Champaign

I am a Blue Waters Associate Professor in agroecosystem sensing and modeling, and I am also the Founding Director of Agroecosystem Sustainability Center (ASC). My major affiliation is with the Department of Natural Resources and Environmental Sciences (NRES), Department of Computer Sciences (CS), Institute for Sustainability, Energy, and Environment, College of Agricultural, Consumer and Environmental Sciences (ACES), and National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign. I use satellite data, computational models, fieldwork, and machine learning approaches to address how climate and human practices affect crop productivity, water resource availability, and ecosystem functioning. I have keen interests in applying my knowledge and skills in solving real-life problems, such as large-scale crop monitoring and forecasting, water management and sustainability, and global food security. My lab closely works with scientists in computer science (deep learning, high performance computing), plant physiologists, agronomists, and economists in addressing the above real-world challenges. I was born in Jiangsu, China. My Chinese name is 管开宇, which carries my grandpa's sincere hope that I could be an astronaut to help explore and discover the universe ("开发宇宙"). 

Mission Statement: We aim to bring domain knowledge (i.e. hydrology, plant physiology, biogeochemistry, agricultural science), satellite data, supercomputing, and machine learning together to revolutionize the agricultural research, such that we can observe every crop field in real-time, monitor crop growth condition, water demands, and nutrient needs, forecast crop yield and risks, and provide farmers our solutions to best manage their fields, across the U.S. Corn Belt and Worldwide. We strive to achieve co-sustainability of environment quality and food security.
 
 Other Links: LinkedIn

For Prospective Students: I recruit PhDs and Masters students from the following programs@UIUC:
PhDs: NRES, PEEC, Informatics
Masters&PhDs: Computer Science

Recruitment: We are recruiting Research Scientists, Postdocs, & PhD Students on Ecosystem Modeling and Remote Sensing. See details here.
Recent News:
Dec 2022: Our cover crop work to map out its availability at every field for the past 22 years, and how this field-level cover crop data contributed to the understanding of the potential yield loss.
Nov 2022: I am extremely excited to see our "system-of-systems" solution for carbon accounting has been acknowledged as the FoodShot Global Groundbreaker Prize, one of the three awardees given annually and globally. Thanks FoodShot Global and Foundation for Food & Agriculture Research (FFAR) for this major award!
Nov 2022: I am excited to be one of the nice Illinois scholars in 2022 Clarivate Analytics Highly Cited Researchers list.
Oct 2022: National Center for Supercomputing Application (NCSA) at UIUC features our group's work on using supercomputing for agroecosystem sensing and modeling.
Aug 2022: Thanks to Illinois Innovation Network and State of Illinois for the recognition of being one of the five receipts for the 2022 IIN Innovator of the Year Awards.
Aug 2022: Associated Press's coverage of the recent Congress bill on the climate deal quotes my comments on farmers' role here: "Not only are they [farmers] doing this to be part of the solution to help the climate, they are doing this to help their land."
Jun 2022: Our lab's new work on modeling nitrogen fertilizer management using the ecosys model for the US Midwest regions provides the scientific foundation to develop decision-making tools for farmers.
Jun 2022: PhD student Qu got the NASA FINNEST graduate fellowship - the most distinguished graduate student fellowship offered by NASA, with the proposed work on mapping cover crop for the whole US cropland.
May 2022: Our new SMARTFARM work, led by Prof. Zhenong Jin from University of Minnesota, hybrids AI with process-based modeling to propose the first-of-its-kind modeling framework called "Knowledge-Guided Machine Learning (KGML)" for modeling agroecosystem GHG.
Apr 2022: Our recent ARPA-E SMARTFARM paper in Geodema: how to develop an estimation strategy that maximizes accuracy while minimizing the number of soil cores sampled.
Mar 2022: Our team's new work in RSE on using hyperspectral sensing and AI to estimate soil carbon in the lab and on assessing its potential to apply in the real world by various satellite sensors.
Jan 2022: Our new airborne hyperspectral work demonstrates the advanced ability to accurately derive canopy nitrogen status and photosynthetic capacity close to the ground truth quality, but at a much lower cost.
Dec 2021: I am honored to be a speaker at C3 Digital Transformation Institute. Whole talk online. 
Oct 2021: We joined a multi-institute USDA $10M project led by Prof. Madhu Khanna in developing agrivoltaics in the broad agricultural landscape.
Sep 2021: White House Briefing highlights three major projects of my group at the national level, in the space of carbon and climate, including our new DOE BETO project and two ARPA-E SMARTFARM projects.
 Sep 2021: Our new study integrates field data and advanced mathematical modeling to understand the relationship between cover crop growth and summer cash crop yield. 
Sep 2021: SMARTFARM Projects are featured in the Planet Lab's blog. 
Sep 2021: We developed a new framework to identify 30m-resolution marginal land for the U.S., by processing 72 billion pixels of satellite data at the Blue Waters Supercomputer. 
Aug 2021: "New Modeling Solution Sets Bar for Quantifying Carbon Budget and Credit." - Our new paper from ARPA-E SMARTFARM project.
Aug 2021: Our collaborative study with University of Minnesota's Zhenong Jin's team led to improved estimation of N2O emission for the U.S. Corn Belt!
Jul 2021: PBS podcast features our work of studying agricultural drought.
Jul 2021: Thanks Larta Institute to nominate me as a finalist of Pritzker Emerging Environmental Genius Award.
Jun 2021: Five SPIN undergraduate interns from our group are featured by NCSA and two of them got the distinguished Fiddle Innovation Award.
Jun 2021: I am humbled and honored to be named as a Blavatnik National Award of Young Scientist Finalist! Thanks to all my students, co-workers, mentors and my family!
Jun 2021: Our group wins an AI for Energy and Climate Security Award from the C3.ai Digital Transformation Institute, focusing on quantifying farmland carbon credit using AI tech.
May 2021: Our group's new review article sheds light on how to improve precision crop irrigation. 
Feb 2021: Our lab developed a new dataset of photosynthesis at the daily and field scale from 2000-present for the continental US.
Nov 2020: Our work on Reliable and Novel Tools for Long-Term Crop Predictions at the Blue Waters Supercomputer wins us the HPC Innovation Excellence Award by Hyperion Research.
Nov 2020: FORBES covered our lab's recent work about better assessments of drought for the U.S. Corn Belt.
Nov 2020: We are integrating airborne data with satellite data to bridge scales from individual plants, to a field, and ultimately to continental applications.
Sep 2020: Recent two papers from my group provide rationales and justification of how we should redefine drought in the US Corn Belt and beyond.
Sep 2020: We are leading a new project with $4.5 million from ARPA-E to develop commercial carbon credit tools for farmland. 
Jun 2020: Ph.D. student Genghong Wu from our lab got award from NASA Future Investigators in NASA Earth and Space Science and Technology.
May 2020: Our "Nature Plants" review paper provides visionary roadmaps of how to develop next-generation crop models for advancing crop breeding, precision agriculture, and assessing climate change adaptations.
Apr 2020: Our group's recent work in Global Change Biology, of quantifying the irrigation cooling benefits of improving crop yield for the U.S. Midwest irrigated maize.
Mar 2020: Our team developed a new algorithm framework to produce real-time field-scale evapotranspiration (ET, or crop water uses) for everywhere in the US. Going to cover everywhere in the planet.
Mar 2020: Our lab's Ph.D. student Hyungsuk Kimm led a new work to enable the monitoring of "Corn productivity in real time: Satellites, field cameras, and farmers team up".
Jan 2020: We lead a team of UIUC scientists to measure corn-soybean carbon emission "gold standard data" through DOE ARPA-e program.
Jan 2020: Our team used Nanosatellites to improve detection of early-season corn nitrogen stress.
Jun 2019: Our lab officially joins NASA Harvest Program, and a new project is developed to provide Illinois farmers actional guidance on field-level management by using NASA satellite data and process-based modeling.
Jun 2019: Thanks for the coverage by SC19 (Supercomputing Conference 2019) on our work and vision: "Food Production & HPC: Understanding Plant Growth From Above and Below".
Jun 2019: Our team, with Prof. Evan DeLucia, conducted a study on understanding increased crop water needs and potential irrigation expansion in the US Midwest in the future.
Jun 2019: Two recent collaborative works on hyperspectral phenotyping, with Prof. Carl Bernacchi, have been published with press releases.
May 2019: Press release on our recent AFM work about Australia wheat yield prediction.
Apr 2019: Press release on our recent GCB work about the excessive rainfall impacts on US maize production.
Apr 2019: Prof. Peng and my lab are awarded Amazon "Earth on AWS" Research Award. 
Mar 2019: Our T-FACE project has been chosen to represent U. of I. in the SoAR Foundation's report of Retaking the Field: Science Breakthroughs for Thriving Farms and a Healthier Nation.
Feb 2019: NSF CAREER Award (UIUC ACES, UIUC NCSA). 
Jan 2019: NCSA "Can you imagine" interview.
Dec 2018: AGU Global Environmental Change Early Career Award (UIUC ACES, UIUC NCSA).
Nov 2018: Highlighted in the NCSA's exhibits in SC18.
Sep 2018: Our algorithm predicts US end-of-season corn yield better than the USDA forecasts.
Aug 2018: R&D Magazine covers a story of our recent work in satellite crop applications.

Short Bio: Before I joined UIUC, I was a post-doctoral scholar working with Prof. David Lobell in the Center on Food Security and the Environment and Department of Environmental Earth System Science, Stanford University. My postdoc research was to study climate change impacts and adaptations on crop production and food security in West African and US. Specifically, I used empirical and process-based approaches to model drought and heat stress effects on staple crop production and assess possible adaptation pathways. I also worked with Dr. Joe Berry on using satellite-based photosynthesis measurements (sun-induced chlorophyll fluorescence) to quantify crop productivity. I briefly worked in the Climate Corporation to help their nitrogen modeling development between my Stanford and UIUC time.
I got my Ph.D. from Princeton University in 2013, and I worked with Prof. Eric F. Wood in the Land Surface Hydrology Research Group. I also closely worked with Prof. Kelly K. Caylor and Prof. David Medvigy. My Ph.D. research focused on understanding how hydrological variability impacts vegetation dynamics (vegetation phenology, ecosystem productivity, and biome distributions) at the continent scale of tropics using multiple remote sensing datasets and ecosystem/land surface models (e.g. SEIB and VIC). 

Research Interests:
Ecohydrology, Terrestrial Carbon Cycle, Remote Sensing Applications (optical/thermal/microwave), Airborne Hyperspectral Application, Agro-ecosystem modeling, Crop Modeling and Forecasting, Biogeochemistry, Agriculture Adaptation to Climate Change

Peer-Reviewed Publications: (Google Scholar)

Our group's research portfolio includes the following three major categories with six specific areas (see below). Our group develops holistic solutions from sensing and monitoring, to modeling and quantification, for agricultural management practices, crop/feedstock carbon and GHG, and environmental conditions. The unique strength and innovation of our research group is the systematic thinking to integrate sensing (from satellite, airborne and ground sensing) with process models and AI to infer holistic agroecosystem dynamics, from aboveground to belowground conditions, covering the coupled water, carbon, nitrogen and energy cycles.  

 
Sensing & Monitoring
         Area 1: Satellite technology innovation and applications
         Area 2: Hyperspectral sensing in ground and airborne platforms

Modeling & quantification
         Area 3: Carbon, GHG and crop yield quantification
         Area 4: Water resources and irrigation

Advancing theory and mechanisms
         Area 5: Ecosystem-level ecohydrology and physiology
         Area 6: Agricultural sustainability and climate change

All the peer-reviewed publications:
(* indicates corresponding authorship, bold italics underline indicates group members at Guan's group)

 [140] Kimball, B.A. et al. (including Guan, K., Zhou, W., Peng, B.) (2023) " Prediction of Evapotranspiration and Yield of Maize An Inter-comparison among 41 Maize Models". Agricultural and Forest Meteorology.

[139] Liu, K., Harrison, M. et al. (including Guan, K.) (2023)" Silver lining to a climate crisis in multiple prospects for alleviating crop waterlogging under future climates". Nature Communication.

[138] Burroughs, C.H., Montes, C.M., Moller, C.A., Mitchell, N.G., Michael, A.M., Peng, B., Kimm, H., Pederson, T.L., Lipka, A.E., Bernacchi, C.J., Guan, K., Ainsworth, E.A. (2022). "Reductions in Leaf Area Index, Pod Production, Seed Size and Harvest Index Drive Yield Loss to High Temperatures in Soybean". Journal of Experimental Botany, p.erac503.

[137] Qin, Z.*, Guan, K.*, Zhou, W., Peng, B., Tang, J., Jin, Z., Grant, R., Hu, T., Villamil, M.B., DeLucia, E., Margenot, A., Umakant, M., Chen, Z., and Coppess, J. (2023) "Assessing long-term impacts of cover crops on soil organic carbon in the central U.S. Midwestern agroecosystems". Global Change Biology.

[136] Ma, Z., Guan, K.*, Peng, B.*, Sivapalan, M., Li, L., Pan, M., Zhou, W., Warner, R., and Zhang, J. (2023) "Agricultural nitrate export patterns shaped by crop rotation and tile drainage". Water Research 229, 119468.

[135] Wang, S.*, Guan, K.*, Zhang, C., Jiang, C., Zhou, Q., Li, K., Qin, Z., Ainsworth, E.A., Margenot, A., and Herzberger, L. (2023) "Airborne hyperspectral imaging of cover crops through radiative transfer process-guided machine learning". Remote Sensing of Environment, 285, 113386.

[134] Zhou, Q., Wang, S., Liu, N., Townsend, P., Jiang, C., Peng, B., Verhoef, W. and Guan, K.* (2023) "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.

[133] 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. and Ma, Z. (2022) "Cross-scale sensing of field-level crop residue fraction and tillage intensity: integrating field photos, airborne hyperspectral imaging, and satellite data". Remote Sensing of Environment, 285, 113366.

[132] Deines, J. M., Guan, K., Lopez, B., Zhou, Q., White, C. S., Wang, S., and Lobell, D. B. (2022) "Recent cover crop adoption is associated with small maize and soybean yield losses in the United States". Global Change Biology, 29, 794–807.

[131] 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., and Cai, Y. (2022) "Recent rapid increase of cover crop adoption across the US Midwest detected by fusing multi-source satellite data". Geophysical Research Letters, p.e2022GL100249.

[130] Gustafson, D., Asseng, S., Fraisse, C., Guan, K., Hoogenboom, G., Kruger, C., Kruse, J., Matlock, M., Melnick, R., Parajuli, R., Rajagopalan, K. and et al. (2022) "In pursuit of more fruitful food systems". The International Journal of Life Cycle Assessment, pp.1-3.

[129] Wu, J., He, R.J., Elizabeth, A.A., Wang, S., and Guan, K. (2022) "Distribution-Informed Neural Networks for Domain Adaptation Regression". NeurIPS 2022.

[128] Zhao, C., Stöckle, C.O., Karimi, T., Nelson, R.L., Evert, F.V.K., Pronk, A.A., Riddle, A.A., Marshall, E., Raymundo, R., Li, Y., Guan, K., Gustafson, D., Hoogenboom, G., and Asseng, S. (2022) "Potential benefits of climate change for potatoes in the United States". Environmental Research Letters, 17, 104034.

[127] Yang, Y., Liu, L., Zhou, W., Guan, K., Tang, J., Kim, T., Grant, R.F., Peng, B., Zhu, P., Li, Z., Griffis, T.J. and Jin, Z*. (2022) "Distinct driving mechanisms of non-growing season N2O emissions call for spatial-specific mitigation strategies in the US Midwest". Agricultural and Forest Meteorology, 324, p.109108.

[126] Jong, M., Guan, K.*, Wang, S., Huang, Y., and Peng, B. (2022) "Improving field boundary delineation in ResUnets via adversarial deep learning". International Journal of Applied Earth Observation and Geoinformation, 112, 102877.

[125] Wu, G.*, Guan, K.*, Jiang, C., Kimm, H., Miao, G., Bernacchi, K., Moore, C.E., Ainsworth, E.A., Yang, X., Berry, J.A., Frankenberg, C., and Min, C. (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.

[124] Khanna, M., Atallah, S.S., et al. (including Guan, K.) (2022). "Digital Transformation for a Sustainable Agriculture in the US: Opportunities and Challenges". Agricultural Economics, 53, 924–937.

[123] Zhou, W., Guan K.*, Peng, B., Margenot, A., Lee, D.K., Tang, J., Jin, Z., Grant, R., DeLucia, E., Qin, Z., Wander, M.M., and Sheng, W. (2022)."How does uncertainty of soil organic carbon stock affect the calculation of carbon budgets and soil carbon credits for croplands in the U.S. Midwest?". Geoderma, 429, 116254.

[122] Wu, G., Jiang, C.*, Kimm, H., Wang, S., Bernacchi, K., Moore, C.E., Suyker, A., Yang, X., Magney, T., Frankenberg, C., Ryu, Y., Dechant, B., and Guan, K.* (2022). "Difference in seasonal peak timing of soybean SIF and GPP explained by canopy structure and chlorophyll content". Remote Sensing of Environment, 279, 113104.

[121] Li, Z.*, Guan, K.*, Zhou, W., Peng, B., Jin, Z., Tang, J.,  Grant, R.F., Nafziger, E.D., Margenot, A.J., Gentry, L.E., DeLucia, E.H., Yang, W.H., Cai, Y., Qin, Z., Archontoulis, S., Fernández, F.G., Yu, Z., Lee, D.K., and Yang, Y. (2022). "Assessing the impacts of pre-growing-season weather conditions on soil nitrogen dynamics and corn productivity in the US Midwest". Field Crops Research, 284, 108563.

[120] Becker-Reshef, I. et al. (including Guan, K.) (2022). "The NASA Harvest Program on Agriculture and Food Security. In: Vadrevu, K.P., Le Toan, T., Ray, S.S., Justice, C. (eds.) Remote Sensing of Agriculture and Land Cover/Land Use Changes in South and Southeast Asian Countries". Springer, Cham, pp. 53–80. 

[119] Liu, L., Xu, S., Tang, J., Guan, K., Griffis, J.T., Erickson, M.D., Frie, A.L., Jia, X., Kim, T., Miller, L.T., Peng, B., Wu, S., Yang, Y., Zhou, W., Kumar, V., and Jin, Z. (2022) "KGML-ag: a modeling framework of knowledge-guided machine learning to simulate agroecosystems: a case study of estimating N2O emission using data from mesocosm experiments". Geoscientific Model Development 15, no. 7 (2022): 2839-2858.

[118] Novick, K.A.*, Metzger, S., Anderegg, W.R., Barnes, M., Cala, D.S., Guan, K., Hemes, K.S., Hollinger, D.Y., Kumar, J., Litvak, M., Lombardozzi, D., Normile, C.P., Oikawa, P., Runkle, B.R., Torn, M. and Wiesner, S. (2022) "Informing Nature-based Climate Solutions for the U.S. with the best-available science". Global Change Biology, 28, 3778–3794.

[117] Li, R.*, Lombardozzi, D., Shi, M., Frankenberg, C., Parazoo, N.C., Köhler, P., Yi, K., Guan, K. and Yang, X.* (2022). "Representation of leaf-to-canopy radiative transfer processes improves simulation of far-red solar-induced chlorophyll fluorescence in the Community Land Model version 5". Journal of Advances in Modeling Earth Systems, p.e2021MS002747.

[116] Potash, R.*, Guan, K.*, Margenot, A., Lee, D., Delucia, E., Wang, S., and Jang, C. (2022) "How to estimate soil organic carbon stocks of agricultural fields? Perspectives using ex ante evaluation". Geodema, 411, 115693.

[115] Vardon, D. R., Sherbacow, B. J., Guan, K., Heyne, J. S., and Abdullah, Z. (2022) "Realizing "Net-Zero-Carbon" sustainable aviation fuel". Joule, 6, 16–21.
 
[114] Wang, S.*, Guan, K.*, Zhang, C., Lee, D., Margenot, A, J., Ge, Y., Peng, J., Zhou, W., Zhou, Q., and Huang, Y. (2022) "Using soil library hyperspectral reflectance and machine learning to predict soil organic carbon: Assessing potential of airborne and spaceborne optical soil sensing". Remote Sensing of Environment, 271, p.112914.

[113] Xu, R., Li, Y., Guan, K., Zhao, L., Peng, B., Miao, C., and Fu, B. (2021). "Divergent responses of maize yield to precipitation in the United States". Environmental Research Letters, 17, 014016.

[112] Peng, B.*, Guan, K. (2021) "Harmonizing climate-smart and sustainable agriculture". Nature Food, 2, 853–854.

[111] Wang, S.*, Guan, K.*, Wang, Z., Ainsworth, E. A., Zheng, T., Townsend, P. A., Liu, N., Nafziger, E., MIchael, M. D., Li, K., Wu G., and 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.

[110] 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., and 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, 124051.
[109] Dechant, B., Ryu, Y., Badgley, G., Köhler, P., Rascher, U., Migliavacca, M., Zhang, Y., Tagliabue, G., Guan, K., Rossini, M., Goulas, Y., Frankenberg, C., and Berry, J. A. (2021) "NIRvP: a robust structural proxy for sun-induced chlorophyll fluorescence and photosynthesis across scales". Remote Sensing of Environment, 268, 112763.

[108] Rastogi, B., Miller, J., Trudeau, M., Andrews, A., Hu, L., Mountain, M., Nehrkorn, T., Mund, J., Guan, K., and Alden, C. (2021) "Evaluating consistency between total column CO2 retrievals from OCO-2 and the in-situ network over North America: Implications for carbon flux estimation". Atmospheric Chemistry and Physics, 21, 14385–14401.

[107] Li, K., Guan, K.*, Jiang, C.*, Wang, S., Peng, B., and 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.

[106] Kumagai, E., Burroughs, C., Pederson, T., Montes, C., Peng, B., Kimm, H., Guan, K., Ainsworth, E., and Bernacchi,. C. (2021) "Predicting biochemical acclimation of leaf photosynthesis in soybean under in-field canopy warming using hyperspectral reflectance". Plant, Cell & Environment, 45, 80–94.

[105] Zhang, J.*, Guan, K.*, Peng, B., Pan, M., Zhou, W., Grant, R.F., Franz, T.E., Rudnick, D.R., Heeren, D.M., Suyker, A., Yang, Y. and Wu, G. (2021) "Assessing different plant-centric water stress metrics for irrigation efficacy using soil-plant-atmosphere-continuum simulation". Water Resources Research, 57, e2021WR030211.

[104] Zhou, W.*, Guan, K.*, Peng, B.*, Wang, Z., Fu, R., Li, B., Ainsworth, A., E., DeLucia E., Zhao, L., and Chen, Z. (2021) "A generic risk assessment framework to evaluate historical and future climate-induced risk for rainfed corn and soybean yield in the U.S. Midwest". Weather and Climate Extremes, 33, 100369.

 [103] Zhang, J.*, Guan, K.*, Peng, B.*, Pan, M., Zhou, W., Jiang, C., ‌‌Kimm‌, H. and et al. (2021) "Sustainable irrigation based on co-regulation of soil water supply and atmospheric evaporative demand". Nature Communications, 12, 5549.

 [102] Qin, Z.*, Guan, K*, Zhou, W., Peng, B., Villamil, B., Jin, Z., Tang, J., Grant, R., Gentry, L., Margenot, A., Bollero, G. and Li, Z., (2021) "Assessing the impacts of cover crops on maize and soybean yield in the U.S. Midwestern agroecosystems". Field Crops Research, 273, 108264.

 [101] Jiang, C.*, Guan, K.*, Khanna, M.*, Chen, L. and Peng, J. (2021) "Assessing marginal land availability based on land use change information in the Contiguous United States". Environmental Science & Technology, 55, 10794–10804.

 [100] Kim, T., Jin, Z., Smith, T., Yang, Y., Yang, Y., Liu, L., Phillips, K., Guan, K., Hunter, L., and Zhou., W. (2021) "A metamodeling approach to identifying nitrogen loss hotspots and mitigation potential in the US Corn Belt". Environmental Research Letters.

[99] Zhou, W.*, Guan, K.*, Peng, B.*, Tang, J., Jin, Z., Jiang, C., Grant R., and Mezbahuddin S. (2021)  "Quantifying carbon budget, crop yields and their responses to environmental variability using the ecosys model for U.S. Midwestern agroecosystems". Agricultural and Forest Meteorology, 307, 108521.

[98] Khanna, M., Chen, L. et al (including Guan, K., Jiang, C.) (2021) "Redefining Marginal Lands for Bioenergy Crop Production". GCB Bioenergy.

[97] Gustafson, D., Asseng, S. Kruse, J., Thoma, G., Guan, K. et al. (2021)  "Supply chains for processed potato and tomato products in the United States will have enhanced resilience with planting adaptation strategies". Nature Food.

[96] Lin, C., Jin, Z., Mulla, D., Ghosh, R., Guan, K., Kumar, V., and Cai, Y., (2021) "Toward Large-Scale Mapping of Tree Crops with High-Resolution Satellite Imagery and Deep Learning Algorithms: A Case Study of Olive Orchards in Morocco". Remote Sensing, 13(9), 1740.

[95] Xu, T., Guan, K., Peng, B. and Zhao, L., (2021) "Machine Learning-based Modeling of Spatio-temporally Varying Responses of Rainfed Corn Yield to Climate, Soil and Management in the U.S. Corn Belt". Frontiers in Artificial Intelligence.

[94] Kimm, H.*, Guan, K.*, Burroughs, C., Peng, B., Ainsworth, E., Bernacchi, C., Moore, C., Kumagai, E., Yang, X., Berry, J. and Wu, G., (2021) "Quantifying high-temperature stress on soybean canopy photosynthesis: the unique role of sun-induced chlorophyll fluorescence". Global Change Biology.

[93] Zhang, J.*, Guan, K.* (Equal Contribution), Peng, B., Jiang, C., Zhou, W., Yang, Y., Pan, M., Franz, T.E., Heeren, D.M., Rudnick, D.R. and Abimbola, O., Kimm, H., Caylor, K., Good, P, S., Khanna, M., Gates, J. and Cai, Y., (2021) "Challenges and opportunities in precision irrigation decision-support systems for center pivots". Environmental Research Letters.
Media: NSF, FutureFarming

[92] Hao, D., Asrar, R. G., Zeng, Y., Yang, X., Li, X., Xiao, J., Guan, K., Wen, J., Xiao, Q., Berry A., J., and Chen, M., (2021) "Potential of hotspot solar-induced chlorophyll fluorescence for better tracking terrestrial photosynthesis". Global Change Biology.

[91] Kong, J., Ryu, Y., Huang, Y., Dechant, B., Houborg, R., Guan, K., and Zhu, X. (2021). "Evaluation of four image fusion NDVI products against in-situ spectral-measurements over a heterogeneous rice paddy landscape". Agricultural and Forest Meteorology, 297, 108255.

 [90] Jiang, C.*, Guan, K.*, Wu, G., Peng, B., and Wang, S. (2021) "A daily, 250 m, and real-time gross primary productivity product (2000-present) covering the Contiguous United States". Earth System Science Data, 13, 281-298, 2021.
Media: CABBI

[89] Zeng, Z. et al. (including Guan, K.) (2020) "Deforestation-induced warming over tropical mountain regions regulated by elevation". Nature Geoscience, 1-7.

[88] Xia, Y., Guan, K., Copenhaver, K., and Wander, M. (2020) "A Multi-site Estimation of Cover Crop Biomass and N Credits using Sentinel-2 Satellite Imagery and Site-based Covariates". Agronomy Journal.

[87] Yang, Y.*, Guan, K.*, Peng, B., Pan, M., Jiang, C., and Franz, E., T. (2020) "High-resolution spatially explicit land surface model calibration using field-scale satellite-based daily evapotranspiration product". Journal of Hydrology.

[86] Wu, G.*, Guan, K.*, Li, Y., Novick, K., Feng, X., McDowell, N., Konings, A., Thompson, S., Kimball, J., De Kauwe, M., Ainsworth, E.A., and Jiang, C. (2020) "Interannual variability of ecosystem iso/anisohydry is regulated by environmental dryness". New Phytologist.

[85] Luo, Y., Guan, K.*, Peng, J., Wang, S., and Huang, Y. (2020) "Stair 2.0: A Generic and Automatic Algorithm to Fuse Modis, Landsat, and Sentinel-2 to Generate 10m, Daily, and Cloud-/Gap-Free Surface Reflectance Product". Remote Sensing, 12(19), 3209.

 [84] Wang, S.*, Guan, K.*, Zhou, W., Ainsworth, E.A., Zheng, T., Townsend, P.A., Li, K., Moller, C., Wu, G., and Jiang, C. (2020) "Unique contributions of chlorophyll and nitrogen to predict crop photosynthetic capacity from leaf spectroscopy". Journal of Experimental Botany.

[83]  Zhou, W.*, Guan, K.*, Peng, B., Shi, J., Jiang, C., Wardlow, B., Pan, M., Kimball, J.S.,Franz,  T.E.,  Gentine,  P.,  He,  M., and  Zhang,  J., (2020) "Connections between the hydrological cycle and crop yield in the rainfed U.S. Corn Belt". Journal of Hydrology, 125398.

[82] Paul, R. F., Cai, Y., Peng, B., Yang, W. H., Guan, K., & DeLucia, E. H., (2020) "Spatiotemporal Derivation of Intermittent Ponding in a Maize-Soybean Landscape from Planet Labs CubeSat Images". Remote Sensing, 12(12), 1942.

 [81] Franz,E.T., Pokal,S., Gibson,P.J., Zhou,Y., Gholizadeh,H., TenorioA.F., Rudnick,D.,Heeren,D., McCabe,M., Ziliani,M., Jin,Z., Guan,K., Pan,M, Gates,J., and Wardlow,B., (2020) "The role of topography, soil, and remotely sensed vegetation condition towards predicting crop yield". Field Crops Research, 252.

[80] Wang,J., Yang,D., Detto,M., Nelson,B., Chen,M., Guan,K., Wu,S., Yan,Z., and Wu,J., (2020) "Multi-scale integration of satellite remote sensing improves characterization of dry-season green-up in an Amazon tropical evergreen forest". Remote Sensing of Environment, 246, 111865.

[79] Peng,B.*, Guan,K.*, Zhou,W., Jiang,C., Frankenberg,C., Sun,Y., He,L., and Kohler,P. (2020) "Assessing the benefit of satellite-based Solar-Induced Chlorophyll Fluorescence in crop yield prediction". International Journal of Applied Earth Observation and Geoinformation, 90, 102126.

[78] Gao,Y., Wang,S., Guan,K., Wolanin,A., You,L., Ju,W., and Zhang,Y. (2020) "The ability of sun-induced chlorophyll fluorescence from OCO-2 and MODIS-EVI to monitor spatial variations of soybean and maize yields in the Midwestern USA". Remote Sensing, 12(7), 1111.

[77] Peng,B.*, Guan,K.*, et al. (2020) "Towards a multiscale crop modelling framework for climate change adaptation assessment". Nature Plants, 6(4), 338-348.
Media: U of I news bureau, AAAS

[76] He,L.,Magney,T.,Dutta,D.,Yin,Y.,Kohler,P.,Grossmann,K.,Stutz,J.,Dold,C.,Hatfield,J., Guan,K., Peng,B., and Frankenberg,C. (2020) "From the ground to space: Using solar-induced fluorescence (SIF) to estimate crop productivity". Geophysical Research Letters, 47(7), e2020GL087474.

[75] Wang,C.*, Guan,K.*, Peng,B.,Chen,M., Jiang,C.,Zeng,Y., Wu,G., Wang,S., Wu,J., Yang,X., Frankenberg,C., Kohler,P., Berry,J., Bernacchi,C., Zhu,K, Alden,C., and Miao,G. (2020) "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 Sensing of Environment, 241.

[74] Jiang,C.*, Guan,K.*, Pan,M., Ryu,Y., Peng,B., and Wang,S. (2020) "BESS-STAIR: a framework to estimate daily, 30-meter, and allweather crop evapotranspiration using multi-source satellite data for the U.S. Corn Belt". Hydrology and Earth System Science, 24, 1251-1273.
Media: AAAS, CABBI, EGU

[73] Kimm,H.*, Guan,K.*, Gentine,P., Wu,J., Lin,C., Bernacchi,C.J., and Sulman,B.N. (2020) "Redefining droughts for the U.S. Corn Belt: The dominant role of atmospheric vapor pressure deficit over soil moisture in regulating stomatal behavior of Maize and Soybean". Agricultural and Forest Meteorology, 287.

[72] Benes,B., Guan,K., Lang,M., Long,S., Lynch,J., Marshall-Colon,A., Peng,B., Schnable,J., Sweetlove,L. and Turk,M. (2020) "Multiscale computational models can guide experimentation and targeted measurements for crop improvement". The Plant Journal.

 [71] Meacham-Hensold,K., Fu,P., Wu,J., Serbin,S., Montes,C.M., Ainsworth,E. Guan,K., Dracup,E., Pederson,T. and Bernacchi C. (2020) "Plot level rapid screening for photosynthetic parameters using proximal hyperspectral imaging". Journal of Experimental Botany, 71(7), 2312-2328.

 [70] Miao,G.*, Guan,K.*, Suyker,A.E., Yang,X., Arkebauer,T.J., Walter-Shea,E.A., Kimm,H., Hmimina,G.Y., Gamon,J.A., Franz,T.E., Frankenberg,C., Berry,J.A., and Wu,G. (2020) "Varying contributions of drivers to the relationship between canopy photosynthesis and far-red sun-induced fluorescence for two maize sites at different temporal scales". Journal of Geophysical Research - Biogeosciences, 125, e2019JG005051.

[69] Fu,P., Meacham,K., Guan,K., Jin,W., and Bernacchi, C. (2020) "Estimating photosynthetic traits from reflectance spectra: A synthesis of spectral indices, numerical inversion, and partial least square regression". Plant, Cell & Environment, 00, 1-18.

[68] Kimm,H.*, Guan,K.*, Jiang,C., Peng,B., Gentry,L.F., Wilkin,S.C., Wang,S., Cai,Y., Bernacchi,C.J., Peng,J., and Luo,Y. (2020) "Deriving high-spatiotemporal-resolution leaf area index for agroecosystems in the U.S. Corn Belt using Planet Labs CubeSat and STAIR fusion data". Remote Sensing of Environment, 239.
Media: U. of I. ACES, Youtube

[67] Cheng,Y. Huang,M., Chen,M., Guan,K., Bernacchi,C., Peng,B., and Tan,Z. (2020) "Parameterizing Perennial Bioenergy Crops in Version 5 of the Community Land Model Based on Site-Level Observations in the Central Midwestern United States". Journal of Advances for Modeling the Earth System, 12, e2019MS001719.

[66] Li,Y.*, Guan,K.*, Peng,B., Franz,T.E., Wardlow,B., and Pan,M. (2020)"Quantifying irrigation cooling benefits to maize yield in the Midwest US". Global Change Biology, 00, 1-14.
Media: U. of I. ACES
[65] Kim,N., Zabaloy,M.C., Guan,K., Villamil,M.B. (2020) "Do cover crops benefit soil microbiome? A meta-analysis of current research". Soil Biology and Biochemistry, 142.

[64] Wu,G., Guan,K.*, Jiang,C.*, Peng,B., Kimm,H., Chen,M., Yang,X., Wang,S., Suyker.A.E.,Bernacchi,C. and Moore, C.E. (2019) "Radiance-based NIRv as a proxy for GPP of corn and soybean". Environmental Research Letters, 15.

[63] Cai,Y., Guan,K.*, Nafziger,E., Chowdhary,G., Peng,B., Jin,Z., Wang,SW, and Wang,Sibo (2019) "Detecting In-Season Crop Nitrogen Stress of Corn for Field Trials Using UAV- and CubeSat-Based Multispectral Sensing". IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(12), 5153-5166.
Media: U. of I. ACES, Successful Farming

[62] Riccetto,S., Davis,A.S., Guan,K., and Pittelkow,C.M. (2019) "Integrated assessment of crop production and resource use efficiency indicators for the U.S. Corn Belt". Global Food Security, 24.

[61] He,M., Kimball,J., Yi,Y., Running,S., Guan,K., Jencso,K., Maxwell,B., and Maneta,M. (2019), "Impacts of the 2017 flash drought in the US Northern Plains informed by satellite-based evapotranspiration and solar-induced fluorescence". Environmental Research Letters, 14.  

[60] Fu,P., Meacham-Hensold,K., Guan,K., and Bernacchi,C. (2019), "Hyperspectral Leaf Reflectance as Proxy for Photosynthetic Capacities: An Ensemble Approach Based on Multiple Machine Learning Algorithms". Frontiers in Plant Science, 10.
Media: UIUC RIPE

 [59] Meacham-Hensold,K., Montes,C.M., Wu,J., Guan,K., Ainsworth,E.A., Pederson,T., Moore,C.E., Brown,K.L., Raines,C., and Bernacchi,C. (2019) "High-throughput field phenotyping using hyperspectral reflectance and partial least squares regression (PLSR) reveals genetic modifications to photosynthetic capacity". Remote Sensing of Environment, 231.
Media: UIUC RIPE

[58] He,M., Kimball,J.S., Yi,Y., Mu,Q., Running,S., Guan,K., Maneta,M., Moreno,A., and Wu,X. (2019) "Satellite data-driven modeling of field scale evapotranspiration in croplands using the MOD16 algorithm framework ", Remote Sensing of Environment, 230.

[57] DeLucia,E.H., Chen,S., Guan,K., Peng,B., Li,Y. et al. (2019) "Are We Approaching a Water Ceiling to Maize Yields in the United States?". Ecosphere, 10(6) e02773.
Media: U. of I. News Bureau, WIRED, Phys.org, Earth.com

[56] Li,Y.*, Guan,K.*, Schnitkey,G., DeLucia,E.H., & Peng,B. (2019) "Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States". Global Change Biology, 25, 2325- 2337.
Media: U. of I. News Bureau, PrairiePress

[55] Li,Y.*, Guan,K.* et al. (2019) "Towards building a transparent statistical model for improving crop yield prediction: Modeling rainfed corn in the U.S.". Field Crop Research, 234, 55-66.

[54] Cai,Y., Guan,K.*, Lobell,D.B., Potgieter,A. et al. (2019) "Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches".  Agricultural and Forest Meteorology, 274, 144-159.
Media: U. of I. ACES, NSF

[53] Felfelani,F., Pokhrel,Y., Guan,K., and Lawrence,D. M. (2018) "Utilizing SMAP Soil Moisture Data to Constrain Irrigation in the Community Land Model". Geophysical Research Letters, 45(23), 12,892-12,902. 

[52] Peng, B.*, Guan, K.*, Pan, M., and Li, Y. (2018) "Benefits of seasonal climate prediction and satellite data for forecasting US maize yield". Geophysical Research Letters, 45.
Media: U of I ACES, AgWeb, Phys.org, GrainCentral

[51] Xu,Z., Guan,K., Casler,N., Peng,B., and Wang,S. (2018) "A 3D convolutional neural network method for land cover classification using LiDAR and multi-temporal Landsat imagery". ISPRS Journal of Photogrammetry and Remote Sensing, 114, 423-434.

[50] Xia,Y., Ugarte,C.M., Pentrak,M., Guan,K., and Wander,M.(2018) "Developing Near- and Mid-Infrared Spectroscopy Analysis Methods for Rapid Assessment of Soil Quality in Illinois". Soil Science Society of America Journal, 82(6), 1415-1427.

[49] Yang,X., Shi,H., Stovall,A., Guan,K., Miao,G., et al. (2018) "FluoSpec2 - An automated field spectroscopy system to monitor canopy solar-induced fluorescence". Sensors, 18.

[48] Zeng,Z., Estes,L., Chen,A., Searchinger,T., Hua,F., Guan,K., and Wood,E.F. (2018) "Highland cropland expansion and forest loss in Southeast Asia in the 21st century". Nature Geoscience, 11, 556-562. 
Media: Princeton University

[47] Guan,K.*, Li,Z., Rao,N., Feng,G, etc (2018) "Mapping Paddy Rice Area and Yields Over Thai Binh Province in Viet Nam From MODIS, Landsat, and ALOS-2/PALSAR-2". IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11, 2238-2252.

[46] Song,L., Guanter,L., Guan,K., ..., Zhang,Y. (2018) "Satellite chlorophyll fluorescence captures heat stress for the winter wheat in the Indo-Gangetic Plains, India". Global Change Biology, 24, 4023- 4037.

[45] Luo,Y., Guan,K.*, and Peng,J.* (2018) "STAIR: A generic and fully-automated method to fuse multiple sources of optical satellite data to generate a high-resolution, daily and cloud-/gap-free surface reflectance product". Remote Sensing of Environment, 214, 87-99.  
Media: UIUC, Youtube, NSF, Phys.org

[44] Urban,D.*, Guan,K.*, and Jain,M. (2018) "Estimating sowing dates from satellite data over the U.S. Midwest: a comparison of multiple sensors and metrics". Remote Sensing of Environment, 211, 400-412.

[43] Liu,Y.Y. et al. (including Guan,K.) (2018) "Enhanced canopy growth precedes senescence in 2005 and 2010 Amazonian droughts". Remote Sensing of Environment, 211, 26-37.

[42] Zhang,Y., Guanter,L., Joiner,J., Lian,S., and Guan,K. (2018) "Spatially-explicit monitoring of crop photosynthetic capacity through space-based chlorophyll fluorescence data". Remote Sensing of Environment, 210, 362-374.

[41] Cai,Y., Guan,K.*, Peng,J.*, Wang,S., Seifert,C., Wardlow,B., and Li,Z. (2018) "A high-performance and in-season classification system of field-level crop types using time-series Landsat data and a machine learning approach". Remote Sensing of Environment,210, 35-47. 
Media: UIUC ACES, NVIDIA, R&DMag, WeatherNation, Phys.org, Landsat.USGS.gov, HPCwire

[40] Miao,G.*, Guan,K.*, Yang,Xi, et al. (2018) "Sun-induced chlorophyll fluorescence, photosynthesis, and light use efficiency of a soybean field from seasonally continuous measurements". Journal of Geophysical Research-Biogeosciences, 123, 610-623.
Media: UIUC IGB, EurekAlert/AAAS, UIUC ACES, New Food, Phys.org, University of Virginia

[39] Lin,C., Gentine,P., Huang,Y., Guan,K., Kimm,H. et al. (2018) "Diel ecosystem conductance response to vapor pressure deficit is suboptimal and independent of soil moisture". Agricultural and Forest Meteorology, 250-251, 24-34.

[38] Zhao,L., Oppenheimer,M., Qing,Z., Baldwin,J., Bou-Zeid,E., Ebi,K., Guan,K., and Liu,X. (2018) "Interactions between urban heat islands and heat waves". Environmental Research Letters, 13.  
Media: Princeton University, EurekAlert/AAAS, ERL Editor's Featured Article

[37] Guan,K.*, Good,S.P., Caylor,K. K., Medvigy,D., Pan,M., Wood,E. F., SATO,H., Biasutti,M., Chen,M., Ahlstrom,A. and Xu,X. (2018) "Simulated sensitivity of African terrestrial ecosystem photosynthesis to rainfall frequency, intensity and rainy season length". Environmental Research Letters, 13.

[36] Xu,X., Medvigy,D., Trugman,A., Guan,K., Good,S.P., and Rodriguez-Iturbe,I. (2018) "Tree cover shows strong sensitivity to precipitation variability across global tropics". Global Ecology and Biogeography, 27, 450- 460.

[35] Peng,B.*, Guan,K.*, Chen,M., Lawrence,D.M., Pokhrel,Y., Suyker,A., ... Lu,Y. (2018) "Improving Maize Growth Processes in the Community Land Model: Implementation and Evaluation". Agricultural and Forest Meteorology, 250-251, 64-89.
Media: UIUC, NCSA, phys.org, Eurek/AAAS, ScienceDaily, MorningAgClips, HPCwire.

[34] Wu,J., Kobayashi,H., Stark,S., Meng,R., Guan,K., Tran,N. et al. (2018) "Biological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest". New Phytologist, 217: 1507-1520. 
Media: NSF, Brookhaven Lab

[33] Li,Y.*, Guan,K.* et al. (2017) "Estimating global ecosystem iso/anisohydry using active and passive microwave satellite data". Journal of Geophysical Research-Biogeosciences, 122, 3306-3321.

[32] Peng,B., Zhao,T., Shi,J., Lu,H., Mialon,A., Kerr,Y.H., Liang,X., and Guan,K. (2017) "Reappraisal of the roughness effect parameterization schemes for L-band radiometry over bare soil". Remote Sensing of Environment.,199, 63-77.

[31] Guan,K.*, Wu,J., Kimball,J., Anderson,M., Li,B., and Lobell,D.B. (2017) "The shared and unique values of optical, fluorescence, thermal and microwave satellite data for estimating large-scale crop yields". Remote Sensing of Environment., 199, 333-349.
Media: UIUC, eoPortal
 
[30] Ahlstrom,A., Canadell,J.G., Schurgers,G., Wu,M., Berry,J.A., Guan,K., and Jackson,R.B. (2017) "Hydrologic resilience and Amazon productivity". Nature Communications, 8(387).

[29] Madani, N., Kimball,J., Jones,L., Parazoo,N.C., and Guan,K. (2017) "Global analysis of bioclimatic controls on ecosystem productivity using satellite observations of solar-induced chlorophyll fluorescence". Remote Sensing, 9(6), 530. 

[28] Wu,J., Guan,K., Hayek,M. et al. (2017) "Partitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to inter-annual time scales". Global Change Biology, 23(3), 1240-1257.

[27] Guan,K.*, Sultan,B., Biasutti,M., Baron.C. and Lobell,D.B. (2017) "Assessing climate adaptation options and uncertainties for cereal systems in West Africa". Agricultural and Forest Meteorology, 232, 291-305.
Media: UIUC

[26] Zhan,W., Guan,K., Wood,E.F. et al (2016) "Depiction of droughts over Sub-Saharan Africa using reanalysis precipitation datasets". Journal of Geophysical Research-Atmospheres, 121(18), 10555-10574.

[25] He,M., Kimball,J.S., Running,S, Ballantyne,A., Guan,K., and Heummrich,F. (2016) "Satellite detection of soil moisture related impacts on ecosystem productivity using the MODIS-based Photochemical Reflectance Index". Remote Sensing of Environment, 186, 173-183.

[24] Wagner,F.H. et al. (including Guan,K.) (2016) "Climate seasonality limits carbon assimilation and storage in tropical forests". Biogeosciences, 13, 2537-2562.

[23] Alden,C.B., Miller,J.B., Gatti,L.V., Gloor,M.M., Guan,K., ..., and Diffenbaugh,N.S. (2016) "Regional atmospheric CO2 inversion reveals seasonal and geographic differences in heat and drought impacts in the Amazon". Global Change Biology, 22, 3427-3443.
Media: CIRES, Stanford News

[22] Xu,X., Medvigy,D., Powers,J., Becknell,J., and Guan,K. (2016) "Diversity in plant hydraulic traits explains seasonal and inter-annual variations of vegetation dynamics in seasonally dry tropical forests". New Phytologist, 212, 80-95.
Comments: New Phytologist

[21] Wu,J., Chavana-Bryant,C., Prohaska,N., Serbin,S.P., Guan,K., Albert,L.P., Yang,X. ... and Saleska,S.R. (2016) "Convergence in relations among leaf traits, spectra and age across canopy environments and two contrasting tropical forests". New Phytologist, 214, 1033-1048.

[20] Saleska,S.R., Wu,J., Guan,K., Nobre,A.D. and Restrepo-Coupe,N. (2016) "Dry-season greening of Amazon forests". Nature, 531, pagesE4-E5.
Media: U. Arizona; UTS; ScienceDaily.

[19] Wu,J., Albert,L.P., Lopes,A.P., Restrepo-Coupe,N., Hayek,M. Wiedemann.,K. T., Guan,K., Stark,S.C., ..., and Saleska.,S.R. (2016) "Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests". Science, 351 (6276).
Media: Science; U. of Arizona; BNL; NSF.

[18] Good,S.P., Guan,K., and Caylor,K.K. (2016) "Global patterns of the contributions of storm frequency, intensity, and seasonality to inter-annual variability of precipitation". Journal of Climate, 29, 3-15.

[17] Guan,K.*, Lobell,D.B., Berry,J.,  Joiner,J., Guanter,L., Zhang,Y., and Badgley,G. (2015) "Improving the monitoring of crop productivity using spaceborne solar-induced fluorescence". Global Change Biology, 22(2).
Media: Stanford News; Youtube

[16] Bahn,M., Reichstein,M., Guan,K., Moreno,J.M., Williams,C. (2015) "Climate extremes and biogeochemical cycles in the terrestrial biosphere: impacts and feedbacks across scales". Biogeosciences, 12, 4827-4830.

[15] Guan,K., Sultan,B., Biasutti,M., and Lobell,D.B. (2015) "What aspects of future rainfall changes matter for crop yields in West Africa". Geophysical Research Letters, 42(19).

[14] Shukla,S., Safeeq,M., AghaKouchak,A., Guan,K., and Funk,C. (2015) "Temperature impacts on the Water Year 2014 Drought in California". Geophysical Research Letters, 42, 4384- 4393.
Media: UCSB Current; Phys.org; CIRC
[13] Guan,K.*, Pan,M., Li,H., Wolf,A., Wu,J., Medvigy,D., Caylor,K.K., Sheffield,J., Wood,E.F., Malhi,Y., Liang,M., Kimball,J. S., Saleska,S., Berry,J., Joiner,J., and Lyapustin,A.I. (2015) "Photosynthetic seasonality of global tropical forests constrained by hydroclimate", Nature Geoscience, 8, pages284-289.
Media: Water forms common thread in diverse rainforest ecosystems (Phys.org; Princeton University).
[12] Sultan,B.*, Guan,K.*, Kouressy,M., Biasutti,M., Piani,C., Hammer,G.L., Mclean,G., and Lobell,D.B. (2014) "Robust features of future climate change impacts on sorghum yields in West Africa". Environmental Research Letters, 9(10).
Media:  Climate change could cut West African sorghum yields by a fifth.

[11] Guan,K.*, Caylor,K.K., Good,S.P., Biasutti,M., Medvigy,D., Pan,M., Wood,E.F. and SATO,H. (2014) "Continental-scale impacts of intra-seasonal rainfall variability on simulated ecosystem responses in Africa". Biogeosciences, 11, 6939-6954.

[10] Reid,M.C, Guan,K., Wagner,F., and Mauzerall,D.L. (2014) "Global Methane Emission from Pit Latrines". Environmental Science and Technology, 48,8727-8734.
Media: Pit latrines: another source of greenhouse gas emissions.

[9] Guan,K.*, Wood,E.F., Caylor,K.K., Medvigy,D., Sheffield,J., Pan,M., Kimball,J., Xu,X and Jones,M.O. (2014) "Terrestrial hydrological control on vegetation phenology of African savannas and woodlands". Journal of Geophysical Research-Biogeosciences, 119(8), 8727-8734.

[8] Good,S.P., Soderberg,K., Guan,K., King,E.G., Scanlon,T., and Caylor,K.K. (2014) "δ2H Isotopic flux partitioning of evapotranspiration over a grass field following a water pulse and subsequent dry down". Water Resources Research, 50(2), 1410-1432.

[7] Sheffield,J., Wood,E.F., Chaney,N., Guan,K., Safri,S., Yuan,X., Olang,L., Amani,A., Ali,A., and Demuth,S. (2014) "A drought monitoring and forecarsting system for Sub-Sahara African water resources and food security". Bulletin of the American Meteorological Society, 95(6), 2014.
Media: UNESCO. African drought monitor;

[6] Yuan,X., Wood,E.F., Chaney,N.W., Sheffield,J., Kam,J., Liang,M., and Guan,K. (2014) "Probalistic Seasonal Forecasting of African Drought by Dynamical Models". Journal of Hydrometeorology, 14, 1706-1720.

[5] Guan,K.*, Medvigy,D., Wood,E.F. , Caylor,K.K. ,Li,S. and Jeong,S.J. (2014) "Deriving vegetation phenological time and trajectory information over Africa using SEVIRI daily LAI". IEEE transactions on Geoscience and Remote Sensing, 53(2),1113-1130.

[4] Guan,K.*, Wolf,A., Wood,E.F., Medvigy,D., Caylor,K.K. and Pan,M. (2013) "Seasonal coupling of canopy function and structure in African tropical forests and its environmental controls". Ecosphere, 4(3).

[3] Guan,K.*, Wood,E.F. and Caylor,K.K. (2012) "Multi-sensor derivation of regional vegetation fractional cover in Africa". Remote Sensing of Environment, 124, 653-665.

[2] Guan,K., Thompson,S.E.*, Harman,C.J., Basu,N.B., Rao,S.P., Sivapalan,M., Kalita,P.K. and Packman,A.I. (2011) "Spatio-temporal scaling of hydrological and agro-chemical export dynamics in a tile-drained Midwestern watershed". Water Resource Research, 47, W00J02.
Media: "Agricultural chemical export dynamics in a watershed". EOS, 92(25), 21 June 2011.

[1] Li,X., Zhao,S., Ke,C. and Guan,K. (2007) "The Study of Methods of Quantitative Evaluation on Remotely Sensed Image Fusion (in Chinese)". Remote Sensing Technology and Application, 22(3).

Other Publications:
[8] Jing, B., Zhang, S., Zhu, Y., Peng, B., Guan, K., Margenot, A. and Tong, H., 2022. "Retrieval Based Time Series Forecasting". arXiv preprint arXiv:2209.13525.

[7] Gustafson. D., et al. (including Guan,K.) (2020) "Integrated Approach to Climate Adaptation and Mitigation: Processed Potato and Tomato". arxiv.org.

[6] Xu,K., Guan,K.*, Peng,J, Luo,Y., and Wang,S.(2019) "DeepMask: an algorithm for cloud and cloud shadow detection in optical satellite remote sensing images using deep residual network". Research Square.

[5] Edwards,A, et al. (including Guan,K. and Li,Y.) (2018) "Sustainable and Equitable Increases in Fruit and Vegetable Productivity and Consumption are Needed to Achieve Global Nutrition Security". Position Paper resulting from a workshop organized by the Aspen Global Change Institute and hosted at the Keystone Policy Center, July 30-August 3, 2018. 

[4] Gamon,J., Hmimina,G., Miao,G., Guan,K. et al.(2018) "Imaging Spectrometry and Fluorometry in Support of Flex: What Can We Learn from Multi-Scale Experiments?". IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.

[3] Guan,K., Hien,N.T., Zhan,L., and Rao,L.N.(2018) "Measuring rice yield from space: the case of Thai Binh Province, Viet Nam". ADB Economics Working Paper Series.

[2] Guan,K. (2013) "PhD dissertation: Hydrological variability on vegetation seasonality, productivity and composition in tropical ecosystems of Africa". Princeton University.

[1] Soderberg,K., Good,S.P., Guan,K. and King,E.G. (2011) "Ecohydrology: also know as growing grass". Mpala Memos, April 2011 issue, Mpala Research Centre and Wildlife Foundation, Laikipia, Kenya.    

Professional Memberships:
American Geophysical Union (AGU) (2009-present)
European Geophysical Union (EGU) (2014-present)
American Meteorological Society (AMS) (2012-present)
Ecological Society of America (ESA) (2015-present)

Academic Services:
Manuscript reviewer: Science; Proceedings of National Academy of Science; Nature Geoscience; Global Change Biology; Remote Sensing of Environment; Journal of Geophysical Research-Biogeosciences; Global Ecology and Biogeography; Journal of Biogeography; Agricultural and Forest Meteorology; Biogeoscience; Water Resources Research; Journal of Hydrology; Hydrology and Earth System Sciences; New Phytologist; PLOS one; Journal of Arid Environments; Land; Journal of Hydrometeorology; International Journal of Biometeorology; Advances in Space Research; Geoinformatics & Geostatistics; Remote Sensing; IEEE Geoscience and Remote Sensing Letters; Journal of Selected Topics in Applied Earth Observations and Remote Sensing; Environmental Research Letters; International Journal of Climatology; Global Biochemcial Cycles.

Proposal reviewer: NASA, NSF, USDA, DOE.

Editor: [1] Guest editor for Special Issue: "Climate extremes and biogeochemical cycles in the terrestrial biosphere: impacts and feedbacks across scale" in Biogeosciences.
[2] Guest editor for Special Issue: "Ecophysiological Remote Sensing" in Remote Sensing.
[3] Guest editor for Special Issue: "Advances in remote sensing and modeling towards sustainable agriculture in a changing climate" in Frontiers in Big Data.
[4] Selected special editor for Proceedings of National Academy of Science (PNAS).

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