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代表性论文列表 (*表示通讯作者):
1. Tian, L., Xue, B., Wang, Z., Li, D., Yao, X., Cao, Q., Zhu, Y., Cao, W., &
Cheng, T.* (2021). Spectroscopic detection of rice leaf blast infection from
asymptomatic to mild stages with integrated machine learning and feature
selection. Remote Sensing of Environment, 257, 112350.
2. Yan, Y., Zhang, X., Li, D., Zheng, H., Yao, X., Zhu, Y., Cao, W., & Cheng, T*.
(2021). Laboratory shortwave infrared reflectance spectroscopy for estimating
grain protein content in rice and wheat. International Journal of Remote
Sensing, 42, 4467-4492.
3. Cheng, T., Ji, X., Yang, G., Zheng, H., Ma, J., Yao, X., Zhu, Y., & Cao, W.*
(2020). DESTIN: A new method for delineating the boundaries of crop fields
by fusing spatial and temporal information from WorldView and Planet
satellite imagery. Computers and Electronics in Agriculture, 178, 105787.
4. Li, D., Chen, J.M., Zhang, X., Yan, Y., Zhu, J., Zheng, H., Zhou, K., Yao, X.,
Tian, Y., Zhu, Y., Cheng, T.*, & Cao, W.* (2020). Improved estimation of leaf
chlorophyll content of row crops from canopy reflectance spectra through
minimizing canopy structural effects and optimizing off-noon observation time.
Remote Sensing of Environment, 248, 111985.
5. Li, P., Zhang, X., Wang, W., Zheng, H., Yao, X., Tian, Y., Zhu, Y., Cao, W.,
Chen, Q., & Cheng, T.* (2020). Estimating aboveground and organ biomass
of plant canopies across the entire season of rice growth with terrestrial laser
scanning. International Journal of Applied Earth Observation and
Geoinformation, 91, 102132.
6. Jiang, J., Zhang, Q., Yao, X., Tian, Y., Zhu, Y., Cao, W., & Cheng, T.* (2020).
HISTIF: A new spatiotemporal image fusion method for high-resolution
monitoring of crops at the subfield level. IEEE Journal of Selected Topics in
Applied Earth Observations and Remote Sensing, 13, 4607-4626.
7. Alebele, Y., Zhang, X., Wang, W., Yang, G., Yao, X., Zheng, H., Zhu, Y., Cao,
W., & Cheng, T.* (2020). Estimation of canopy biomass components in paddy
rice from combined optical and SAR data using multi-target Gaussian
regressor stacking. Remote Sensing, 12, 2564.
8. Li, D., Tian, L., Wan, Z., Jia, M., Yao, X., Tian, Y., Zhu, Y., Cao, W.*, &
Cheng, T.* (2019). Assessment of unified models for estimating leaf
chlorophyll content across directional-hemispherical reflectance and
bidirectional reflectance spectra. Remote Sensing of Environment, 111240.
9. Lu, N., Zhou, J., Han, Z., Li, D., Cao, Q., Yao, X., Tian, Y., Zhu, Y., Cao, W.,
& Cheng, T.* (2019). Improved estimation of aboveground biomass in wheat
from RGB imagery and point cloud data acquired with a low-cost unmanned
aerial vehicle system. Plant Methods, 15:17.
10. 姬旭升，李旭，万泽福，姚霞，朱艳，程涛*. (2019). 基于高空间分辨率
卫星影像的新疆阿拉尔市棉花与枣树分类. 中国农业科学, 52, 997-1008.
11. Li, D., Cheng, T.*, Jia, M., Zhou, K., Lu, N., Yao, X., Tian, Y., Zhu, Y., &
Cao, W. (2018). PROCWT: Coupling PROSPECT with continuous wavelet
transform to improve the retrieval of foliar chemistry from leaf bidirectional
reflectance spectra. Remote Sensing of Environment, 206, 1-14.
12. Li, D., Wang, X., Zheng, H., Zhou, K., Yao, X., Tian, Y., Zhu, Y., Cao, W., &
Cheng, T.* (2018). Estimation of area- and mass-based leaf nitrogen contents
of wheat and rice crops from water-removed spectra using continuous wavelet
analysis. Plant Methods, 14, 76.
13. Li, D., Cheng, T.*, Zhou, K., Zheng, H., Yao, X., Tian, Y., Zhu, Y., & Cao, W.
(2017). WREP: A wavelet-based technique for extracting the red edge position
from reflectance spectra for estimating leaf and canopy chlorophyll contents of
cereal crops. ISPRS Journal of Photogrammetry and Remote Sensing, 129,
103-117.
14. Xu, X., Ji, X., Jiang, J., Yao, X., Tian, Y., Zhu, Y., Cao, W., Cao, Q., Yang, H.,
Shi, Z., & Cheng, T.* (2018). Evaluation of one-class support vector
classification for mapping the paddy rice planting area in Jiangsu Province of
China from Landsat 8 OLI imagery. Remote Sensing, 10, 546.
15. Jiang, J., Ji, X., Yao, X., Tian, Y., Zhu, Y., Cao, W., & Cheng, T.* (2018).
Evaluation of three techniques for correcting the spatial scaling bias of leaf
area index. Remote Sensing, 10, 221.
16. Cheng, T., Song, R., Li, D., Zhou, K., Zheng, H., Yao, X., Tian, Y., Cao, W.,
& Zhu, Y. (2017). Spectroscopic estimation of biomass in canopy components
of paddy rice using dry matter and chlorophyll indices. Remote Sensing, 9,
319.
17. Zhou, K., Deng, X., Yao, X., Tian, Y., Cao, W., Zhu, Y.*, Ustin, S.L., &
Cheng, T.* (2017). Assessing the spectral properties of sunlit and shaded
components in rice canopies with near-ground imaging spectroscopy
data. Sensors, 17, 578.
18. Cheng, T., Yang, Z., Inoue, Y., Zhu, Y., & Cao, W. (2016). Preface: recent
advances in remote sensing for crop growth monitoring. Remote Sensing, 8,
116.
19. Cheng, T., Riaño, D. & Ustin, S. L. (2014). Detecting diurnal and seasonal
variation in canopy water content of nut tree orchards from airborne imaging
spectroscopy data using continuous wavelet analysis. Remote Sensing of
Environment, 143, 39-53.
20. Cheng, T., Rivard, B., Sánchez-Azofeifa, G. A., Féret, J. B., Jacquemoud, S.
& Ustin, S. L. (2014). Deriving leaf mass per area (LMA) from foliar
reflectance across a variety of plant species using continuous wavelet analysis.
ISPRS Journal of Photogrammetry and Remote Sensing, 87, 28-38.
21. Cheng, T., Riaño, D., Koltunov, A., Whiting, M. L., Ustin, S. L. & Rodriguez,
J. Detection of diurnal variation in orchard canopy water content using
MODIS/ASTER airborne simulator (MASTER) data. (2013). Remote Sensing
of Environment, 132, 1-12.
22. Cheng, T., Rivard, B., Sánchez-Azofeifa, G. A., Féret, J. B., Jacquemoud, S.
& Ustin, S. L. (2012). Predicting leaf gravimetric water content from foliar
reflectance across a range of plant species using continuous wavelet analysis.
Journal of Plant Physiology, 169, 1134-1142.
23. Cheng, T., Rivard, B., & Sánchez-Azofeifa, G. A. (2011). Spectroscopic
determination of leaf water content using continuous wavelet analysis. Remote
Sensing of Environment, 115, 659-670.
24. Cheng, T., Rivard, B., Sánchez-Azofeifa, G. A., Feng, J. & Calvo-Polanco, M.
(2010). Continuous wavelet analysis for the detection of green attack damage
due to mountain pine beetle infestation. Remote Sensing of Environment, 114,
899-910.
合编著作
1. 曹卫星，程涛，朱艳，姚霞，等. 2020. 作物生长光谱监测. 北京: 科学出
版社.
2. Cheng, T., Zhu, Y., Li, D., Yao, X, & Zhou, K. (2018). Hyperspectral remote
sensing of leaf nitrogen concentration in cereal crops. In P. S. Thenkabail, J.
Lyon, & A. Huete (Eds.), Hyperspectral Remote Sensing of Vegetation,
Second Edition, Four Volume Set, Volume 2. Boca Raton, FL: CRC Press.
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