Journal Articles

[17] Y. Guo, K. Mokany, S. R. Levick, J. Yang, S. Ferrier, and P. Moghadam (2024). Spatioformer: A geolocation-encoded Transformer architecture for continental-scale plant species richness prediction and mapping. Under Review.

[16] 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 (2024). Mapping the multidecadal trends of terrestrial plant nitrogen stable isotope ratios globally. Under Review.

[15] F. Zhao, W. Ma, J. Zhao, Y. Guo, M. Tariq, and J. Li (2024). Global retrieval 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

[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] 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.

[6] 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.

[5] 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.

[4] 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

[3] 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.

[2] 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.

[1] 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.

Conference Abstracts

[2] 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 (2023). Developing satellite-derived nitrogen stable isotope ratio grids to globally monitor terrestrial plant nitrogen availability for 1984-2022. The 25th International Congress on Modelling and Simulation.

[1] Y. Guo, K. Mokany, P. Moghadam, S. Ferrier, and S. R. Levick (2022). Mapping Plant Biodiversity in Australia from Landsat: A Deep Learning Approach. Advancing Earth Observation Forum 2022.

Conference Presentations

[9] Oral Presentation: Y. Guo, Quantitative assessment of DESIS hyperspectral data for plant biodiversity estimation in Australia, presented at the 2022 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 17-22 July 2022, Kuala Lumpur, Malaysia (Online).

[8] Video Presentation: Y. Guo, Plant biodiversity mapping with satellite imagery, presented at the 2022 Machine Learning and Artificial Intelligence Reimagining Science (MARS2022), 31 May-1 June 2022, Sydney, Australia.

[7] Video Presentation: Y. Guo, Self-supervised learning for biodiversity, presented at the 2021 Machine Learning and Artificial Intelligence Reimagining Science (MARS2021), 1-2nd June 2021, Online.

[6] Oral Presentation: Y. Guo, A drone-based sensing system to support satellite image analysis for rice farm mapping, presented at the 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 28 July–2 August 2019, Yokohama, Japan.

[5] Poster Presentation: Y. Guo, Mapping of rice varieties with Sentinel-2 data via deep CNN learning in spectral and time domains, presented at the 2018 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 10–13 December 2018, Canberra, Australia.

[4] Oral Presentation: Y. Guo, Sequential classifier training for rice mapping with multitemporal remote sensing imagery, presented at the 2nd International Symposium on Spatiotemporal Computing 2017, 7–9 August 2017, Cambridge, USA.

[3] Oral Presentation: Y. Guo, A domain-transfer support vector machine for multi-temporal remote sensing imagery classification, presented at the 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 23–28 July 2017, Fort Worth, USA.

[2] Poster Presentation: Y. Guo, Multi-kernel retrieval of land surface bidirectional reflectance distribution functions based on l1-norm optimization, presented at the 2016 IEEE International Geoscience and Remote Sensing Symposium, 10–15 July 2016, Beijing, China.

[1] Oral Presentation: Y. Guo, Early detection of crop injury from glyphosate by foliar biochemical parameter inversion through leaf reflectance measurement, presented at the Third International Conference on Agro-Geoinformatics, 11–14 August 2014, Beijing, China.

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. Zhang, 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