About me
Hi, my name is Yiqing Guo (Yiqing is pronounced like /Yee-Ching/). Currently, I am a Research Scientist at CSIRO, Australia. My research focuses on developing and applying AI methods for remote sensing data interpretation and environmental monitoring. Please see my Google Scholar and CV.
I received my PhD degree from the University of New South Wales, Canberra Campus, in 2019. After one and a half years of industry experience, I joined the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in 2020, where I am now a Research Scientist with CSIRO Data61.
I have authored/co-authored more than 20 peer-reviewed publications. My research outcomes have been published in top journals such as Remote Sens. Environ., ISPRS J. Photogramm. Remote Sens., IEEE Trans. Image Process., IEEE Trans. Geosci. Remote Sens., and IEEE Geosci. Remote Sens. Magazine.
Contact me at yiqing.guo.buaa@gmail.com
Journal Articles
[21] J. Yang, H. Zhang, Y. Guo, R. J. Donohue, T. R. McVicar, S. Ferrier, W. Müller, X. Lü, Y. Fang, X. Wang, P. B. Reich, X. Han, and K. Mokany (2025). Globally mapping the nitrogen stable isotope ratios of terrestrial vegetation from 1984 to 2022. Earth’s Future.
[20] J. Yang, Y. Guo, C. J. Owers, K. Giljohann, R. Valavi, R. Donohue, K. J. Williams, S. Ferrier, and K. Mokany (2025). A framework for dynamic assessments of terrestrial ecosystem condition. Global Ecology and Biogeography, 34(10), e70132.
[19] C. Luo, W. Xiang, K. Han, L. Yu, Y. Guo, S. L. K. Unnithan, X. Qi, and Cherukuru, N. (2025). HyperEst: Context-aware self-supervised pretraining for hyperspectral and multispectral water quality estimation. International Journal of Applied Earth Observation and Geoinformation, 143, 104761.
[18] S. K. Unnithan, N. Cherukuru, T. Ingleton, E. Lehmann, M. Paget, Y. Guo, N. Drayson, and G. Kerrisk (2025). Mapping total suspended solids (TSS) and dissolved organic carbon (DOC) in complex coastal waters using deep learning enhanced remote sensing. Ecological Informatics, 90, 103276.
[17] Y. Guo, N. Cherukuru, E. Lehmann, X. Qi, M. J. Doubell, S. L. Kesav Unnithan, and M. Feng (2025). Decadal analysis of sea surface temperature patterns, climatology, and anomalies in temperate coastal waters with Landsat-8 TIRS observations. GIScience & Remote Sensing, 62(1), 2518623.
[16] Y. Guo, K. Mokany, S. R. Levick, J. Yang, and P. Moghadam (2025). Spatioformer: A geo-encoded transformer for large-scale plant species richness prediction. IEEE Transactions on Geoscience and Remote Sensing, 63, 4403216.
[15] F. Zhao, W. Ma, J. Zhao, Y. Guo, M. Tariq, and J. Li (2024). Global reconstruction of the spectrum of terrestrial chlorophyll fluorescence: First Results With TROPOMI. Remote Sensing of Environment, 300, 113903.
[14] Y. Guo, K. Mokany, C. Ong, P. Moghadam, S. Ferrier, and S. R. Levick (2023). Plant species richness prediction from DESIS hyperspectral data: A comparison study on feature extraction procedures and regression models. ISPRS Journal of Photogrammetry and Remote Sensing, 196, 120-133.
[13] Y. Guo, J. Zhang, A. Farooq, X. Chen, and X. Jia (2020). Activities of the IEEE GRSS University of New South Wales Canberra Student Chapter, Australia [Column Article]. IEEE Geoscience and Remote Sensing Magazine, 8(3), 102-103.
[12] Y. Guo, X. Jia, D. Paull, and J. A. Benediktsson (2019). Nomination-favoured opinion pool for optical-SAR-synergistic rice mapping in face of weakened flooding signals. ISPRS Journal of Photogrammetry and Remote Sensing, 155, 187–205.
[11] F. Zhao, R. Li, W. Verhoef, S. Cogliati, X. Liu, Y. Huang, Y. Guo, and J. Huang (2018). Reconstruction of the full spectrum of solar-induced chlorophyll fluorescence: Intercomparison study for a novel method. Remote Sensing of Environment, 219, 233–246.
[10] Y. Guo, X. Jia, and D. Paull (2018). Effective sequential classifier training for SVM-based multitemporal remote sensing image classification. IEEE Transactions on Image Processing, 27(6), 3036–3048.
[9] Y. Guo, X. Jia, and D. Paull (2017). Superpixel-based adaptive kernel selection for angular effect normalization of remote sensing images with kernel learning. IEEE Transactions on Geoscience and Remote Sensing, 55(8), 4262–4271.
[8] F. Zhao, X. Dai, W. Verhoef, Y. Guo, C. van der Tol, Y. Li, and Y. Huang (2016). FluorWPS: A Monte Carlo ray-tracing model to compute sun-induced chlorophyll fluorescence of three-dimensional canopy. Remote Sensing of Environment, 187, 385–399.
[7] F. Zhao, Y. Li, X. Dai, W. Verhoef, Y. Guo, H. Shang, X. Gu, Y. Huang, T. Yu, and J. Huang (2015). Simulated impact of sensor field of view and distance on field measurements of bidirectional reflectance factors for row crops. Remote Sensing of Environment, 156, 129–142.
[6] F. Zhao, Y. Guo, Y. Huang, W. Verhoef, C. van der Tol, B. Dai, L. Liu, H. Zhao, and G. Liu (2015). Quantitative estimation of fluorescence parameters for crop leaves with Bayesian inversion. Remote Sensing, 7(10), 14179–14199.
[5] F. Zhao, Y. Guo, Y. Huang, K. N. Reddy, Y. Zhao, and W. T. Molin (2015). Detection of the onset of glyphosate-induced soybean plant injury through chlorophyll fluorescence signal extraction and measurement. Journal of Applied Remote Sensing, 9(1), 097098.
[4] F. Zhao, Y. Guo, Y. Huang, K. N. Reddy, M. A. Lee, R. S. Fletcher, and S. J. Thomson (2014). Early detection of crop injury from herbicide glyphosate by leaf biochemical parameter inversion. International Journal of Applied Earth Observation and Geoinformation, 31, 78–85.
[3] F. Zhao, Y. Guo, W. Verhoef, X. Gu, L. Liu, and G. Yang (2014). A method to reconstruct solar-induced canopy fluorescence spectrum from hyperspectral measurements. Remote Sensing, 6(10), 10171–10192.
[2] F. Zhao, Y. Huang, Y. Guo, K. N. Reddy, M. A. Lee, Reginald S. Fletcher, and Steven J. Thomson (2014). Early detection of crop injury from glyphosate on soybean and cotton using plant leaf hyperspectral data. Remote Sensing, 6(2), 1538–1563.
[1] F. Zhao, X. Gu, T. Yu, W. Verhoef, Y. Guo, Y. Du, H. Shang, and H. Zhao (2013). Bidirectional reflectance effects over flat land surface from the charge-coupled device data sets of the HJ-1A and HJ-1B satellites. Journal of Applied Remote Sensing, 7(1), 073466.
Conference Papers
[11] Y. Guo, N. Cherukuru, E. Lehmann, S. L. Unnithan, G. Kerrisk, T. Malthus, and F. Islam (2025). Hyperspectral in situ remote sensing of water surface nitrate in the Fitzroy River estuary, Queensland, Australia, using deep learning. In Proceedings of the 2025 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
[10] Y. Guo, K. Mokany, C. Ong, P. Moghadam, S. Ferrier, and S. R. Levick (2022). Quantitative assessment of DESIS hyperspectral data for plant biodiversity estimation in Australia. In Proceedings of the 2022 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 1744-1747.
[9] Y. Guo, X. Jia, D. Paull, J. Zhang, A. Farooq, X. Chen, and M. N. Islam (2019). A drone-based sensing system to support satellite image analysis for rice farm mapping. In Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 9376–9379.
[8] Y. Guo, X. Jia, and D. Paull (2018). Mapping of rice varieties with Sentinel-2 data via deep CNN learning in spectral and time domains. In Proceedings of the 2018 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 794–800.
[7] E. Madigan, Y. Guo, M. Pickering, A. Held, and X. Jia (2018). Quantitative monitoring of complete rice growing seasons using Sentinel 2 time series images. In Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 7699–7702.
[6] Y. Guo, X. Jia, and D. Paull (2017). Sequential classifier training for rice mapping with multitemporal remote sensing imagery. In ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences, 4, 161–165.
[5] Y. Guo, X. Jia, and D. Paull (2017). A domain-transfer support vector machine for multi-temporal remote sensing imagery classification. In Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2215–2218.
[4] Y. Guo, X. Jia, and D. Paull (2016). Multi-kernel retrieval of land surface bidirectional reflectance distribution functions based on l1-norm optimization. In Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 1358–1361.
[3] Y. Guo, F. Zhao, Y. Huang, K. N. Reddy, Y. Zhao, and L. Dong (2014). Detection of the onset of crop stress induced by glyphosate using chlorophyll fluorescence measurements. In Proceedings of the Third International Conference on Agro-Geoinformatics, 560–564. Best Student Paper Award
[2] P. Zhang, F. Zhao, Y. Guo, Y. Zhao, L. Dong, and H. Zhao (2014). Sensitivity analysis of the row model’s input parameters. In Proceedings of the Third International Conference on Agro-Geoinformatics, 220–224.
[1] Y. Guo, F. Zhao, Y. Huang, M. A. Lee, K. N. Reddy, R. S. Fletcher, S. J. Thomson, and J. Huang (2013). Early detection of crop injury from glyphosate by foliar biochemical parameter inversion through leaf reflectance measurement. In Proceedings of the Second International Conference on Agro-Geoinformatics, 116–120.
Technical Reports
[1] Lau, Ian; Ong, Cindy; Caccetta, Mike; Guo, Yiqing. A 10-Year Analysis of Landsat 8 Continental Imagery to Identify Candidate Sites for Optical Vicarious Calibration and Validation in Australia. Australia: CSIRO; 2023. csiro:EP2023-5606. https://doi.org/10.25919/dxg8-8w19
Open Source Codes
[4] Y. Guo, K. Mokany, S. R. Levick, J. Yang, and P. Moghadam (2025). Spatioformer. https://github.com/csiro-robotics/Spatioformer
[3] Yang, Jinyan; Zhang, Haiyang; Guo, Yiqing; Donohue, Randall; McVicar, Tim; Ferrier, Simon; Muller, Warren; Lv, Xiaotao; Fang, Yunting; Wang, Xiaoguang; Reich, Peter; Han, Xingguo; & Mokany, Karel (2024): A framework to estimate nitrogen stable isotope ratio from satellite spectra. CSIRO. v1. Software. https://doi.org/10.25919/6ahe-e170
[2] Yang, Jinyan; Guo, Yiqing; Owers, Chris; Giljohann, Kate; Valavi, Roozbeh; Donohue, Randall; Williams, Kristen; Ferrier, Simon; & Mokany, Karel (2024): FACTE: A framework for dynamic assessments of terrestrial ecosystem condition. CSIRO. v1. Software. https://doi.org/10.25919/e6gt-hd02
[1] Yiqing Guo, Xiuping Jia, David Paull (2018) TASVM: A domain-transfer support vector machine for classifier-level domain adaptation [Source Code]. https://doi.org/10.24433/CO.9d860e02-91b0-4a6a-850d-d4f52754ca33
Published Datasets
[4] Guo, Yiqing; Mokany, Karel; Levick, Shaun; Yang, Jinyan; & Moghadam, Peyman (2024): AusRichness: A machine learning ready dataset for plant species richness prediction in Australia. v1. CSIRO. Data Collection. https://doi.org/10.25919/7d5h-yp05
[3] Yang, Jinyan; Guo, Yiqing; Owers, Chris; Giljohann, Kate; Valavi, Roozbeh; Donohue, Randall; Williams, Kristen; Ferrier, Simon; & Mokany, Karel (2024): Annual terrestrial ecosystem condition score map for Australia derived using the FACTE framework: 100m, 2013-2022. v1. CSIRO. Data Collection. https://doi.org/10.25919/k5cv-ss32
[2] Yang, Jinyan; Zhang, Haiyang; Guo, Yiqing; Donohue, Randall; McVicar, Tim; Ferrier, Simon; Muller, Warren; Lv, Xiaotao; Fang, Yunting; Wang, Xiaoguang; Reich, Peter; Han, Xingguo; & Mokany, Karel (2024): Global terrestrial plant nitrogen stable isotope ratio samples: 30m centroid of each 0.1 degree grid cell from 1984 to 2022. v1. CSIRO. Data Collection. https://doi.org/10.25919/7069-6855
[1] Lau, Ian; Ong, Cindy; Guo, Yiqing; Caccetta, Mike; Squire, Geoffrey; & Woodcock, Robert (2023): Landsat 8 Continental Analysis of Australia. v1. CSIRO. Data Collection. https://doi.org/10.25919/25p4-5r08
Theses
[2] Y. Guo (2019). Quantitative rice mapping with remote sensing image time series. PhD Thesis. The University of New South Wales.
[1] Y. Guo (2015). Early detection of crop stress with hyperspectral remote sensing data. Master’s Thesis. Beihang University [In Chinese]. Excellent Thesis Award
Granted Patents
[2] F. Zhao and Y. Guo (2014). A method for spectral feature extraction from hyperspectral reflectance data based on global sensitivity analysis. Patent Grant No.: CN103714341A
[1] F. Zhao, Y. Guo, P. Zhang, Y. Zhao, and H. Zhao (2014). A method for retrieval of field component temperature based on global optimization algorithm. Patent Grant No.: CN103823994A