代表模型：
1）SPART
2）SCOPE 2.0，mSCOPE
论文：
1. Yang, P. *, (2022), Exploring the interrelated effects of soil background, canopy structure and sun-observer geometry on canopy photochemical reflectance index. Remote Sensing of Environment, 279, 113133. https://doi.org/10.1016/j.rse.2022.113133
2. Yang, P., Prikaziuk, E., Verhoef, W., & van Der Tol, C.* (2021). SCOPE 2.0: A model to simulate vegetated land surface fluxes and satellite signals. Geoscientific Model Development, 14(7), 4697-4712. https://doi.org/10.5194/gmd-14-4697-2021
3. Yang, P.*, Van der Tol, C., Campbell, P. K., & Middleton, E. M. (2021). Unravelling the physical and physiological basis for the solar-induced chlorophyll fluorescence and photosynthesis relationship. Biogeosciences, 1-32.https://doi.org/10.5194/bg-18-441-2021
4. Yang, P.*, Verhoef, W., Prikaziuk, E., & van der Tol, C. (2021). Improved retrieval of land surface biophysical variables from time series of Sentinel-3 OLCI TOA spectral observations by considering the temporal autocorrelation of surface and atmospheric properties. Remote Sensing of Environment, 256, 112328.https://doi.org/10.1016/j.rse.2021.112328
5. Yang, P.*, van der Tol, C., Tiangang Yin., Verhoef, W. (2020). The SPART model: a soil-plant-atmosphere radiative transfer model for satellite measurements in the solar spectrum. Remote Sensing of Environment, 247, 11187.https://doi.org/10.1016/j.rse.2020.111870
6. Yang, P.*, van der Tol, C., Campbell, P. and Middleton, E., (2020). Fluorescence Correction Vegetation Index (FCVI): A physically based reflectance index to separate physiological and non-physiological information in far-red sun-induced chlorophyll fluorescence. Remote Sensing of Environment, 240, 111676.https://doi.org/10.1016/j.rse.2020.111676
7. Yang, P.*, Verhoef, W., van der Tol, C., (2020). Unified four-stream radiative transfer theory in the optical-thermal domain with consideration of fluorescence for multi-layer vegetation canopies. Remote Sensing.https://doi.org/10.3390/rs12233914
8. Yang, P.*, van der Tol, C., Verhoef, W., Damm, ... & Rascher, U., 2019. Using reflectance to explain vegetation biochemical and structural effects on sun-induced chlorophyll fluorescence, Remote Sensing of Environment, 231.https://doi.org/10.1016/j.rse.2018.11.039
9. Yang, P.*, van der Tol, C., 2018. Linking canopy scattering of far-red sun-induced chlorophyll fluorescence with reflectance. Remote Sensing of Environment, 209, 456 – 467.https://doi.org/10.1016/j.rse.2018.02.029
10. Yang, P.*, Verhoef, W., van der Tol, C., 2017. The mSCOPE model: A simple adaptation to the SCOPE model to describe reflectance, fluorescence and photosynthesis of vertically heterogeneous canopies. Remote Sensing of Environment, 201, 1 - 11.https://doi.org/10.1016/j.rse.2017.08.029
11. Yang, P.*, Van der Tol, C., Rascher, U., Damm, A., Schickling, A., & Verhoef, W. (2016, December). Detecting Crop Functional Response to a Heat Wave using Airborne Reflectance and Sun-induced Chlorophyll Fluorescence Measurements. In AGU Fall Meeting Abstracts (Vol. 2016, pp. B51B-0390).https://optimise.dcs.aber.ac.uk/wp-content/uploads/Session7_Peiqi-Yang.pdf
12. Yang, P.*, van der Tol, C. (2018), A spectral invariant approach to modelling radiative transfer of sun-induced chlorophyll fluorescence. IEEE Geoscience and Remote Sensing Symposium (IGARSS).https://doi.org/10.1109/IGARSS.2018.8517742
13. Yang, P., Liu, Z.*, (2013) Remote sensing of solar-induced chlorophyll fluorescence from an unmanned airship platform. IEEE Geoscience and Remote Sensing Symposium (IGARSS).https://doi.org/10.1109/IGARSS.2013.6723402
14. 杨沛琦,刘志刚*,倪卓娅,王冉,王庆山,2013. 基于低空成像高光谱系统探测植被日光诱导叶绿素荧光. 光谱学与光谱分析, 33(11), 3101-3105.http://doi.org/10.3964/j.issn.1000-0593(2013)11-3101-05
15. Zhang, R., Yang, P. *, Liu, S., Wang, C., and Liu, J. (2022). Evaluation of the Methods for Estimating Leaf Chlorophyll Content with SPAD Chlorophyll Meters. Remote Sensing 14, no. 20: 5144.https://doi.org/10.3390/rs14205144
16. van der Tol, C., Julitta, T., Yang, P., Sabater, N. Reiter, I., Tudoroiu, M., Schuettemeyer, D., Drusch, M. (2023). Retrieval of chlorophyll fluorescence from a large distance using oxygen absorption bands. Remote sensing of environment, 284, 113304.https://doi.org/10.1016/j.rse.2022.113304
17. Rastogi A, Antala M, Prikaziuk E, Yang P, van der Tol C, Juszczak R. (2022). Exploring the Potential of SCOPE Model for Detection of Leaf Area Index and Sun-Induced Fluorescence of Peatland Canopy. Remote Sensing.; 14(16):4010.https://doi.org/10.3390/rs14164010
18. Campbell, P., Middleton, E., Huemmrich, K., Ward, L., Julitta, T., Yang, P., ... & Kustas, W. (2021). Scaling photosynthetic function and CO2 dynamics from leaf to canopy level for maize–dataset combining diurnal and seasonal measurements of vegetation fluorescence, reflectance and vegetation indices with canopy gross ecosystem productivity. Data in Brief, 39, 107600.https://doi.org/10.1016/j.dib.2021.107600
19. Siegmann, B., Cendrero-Mateo, M. P., Cogliati, S., Damm, A., Gamon, J., Herrera, D., ... Yang, P. , & Rascher, U. (2021). Downscaling of far-red solar-induced chlorophyll fluorescence of different crops from canopy to leaf level using a diurnal data set acquired by the airborne imaging spectrometer HyPlant. Remote sensing of environment, 264, 112609.https://doi.org/10.1016/j.rse.2021.112609
20. Malenovský, Z., Regaieg, O., Yin, T., Lauret, N., Guilleux, J., Chavanon, E., ... Yang, P., & Gastellu-Etchegorry, J. P. (2021). Discrete anisotropic radiative transfer modelling of solar-induced chlorophyll fluorescence: Structural impacts in geometrically explicit vegetation canopies. Remote Sensing of Environment, 263, 112564.https://doi.org/10.1016/j.rse.2021.112564
21. Wang, Y., Zeng, Y., Yu, L., Yang, P., Van der Tol, C., Yu, Q., ... & Su, Z. (2021). Integrated modeling of canopy photosynthesis, fluorescence, and the transfer of energy, mass, and momentum in the soil–plant–atmosphere continuum (STEMMUS–SCOPE v1. 0.0). Geoscientific Model Development, 14(3), 1379-1407.https://doi.org/10.5194/gmd-14-1379-2021
22. Prikaziuk, E., Yang, P., & van der Tol, C. (2021). Google Earth Engine Sentinel-3 OLCI Level-1 Dataset Deviates from the Original Data: Causes and Consequences. Remote Sensing, 13(6), 1098.https://doi.org/10.3390/rs13061098
23. van der Tol, C., & Yang, P. (2020, December). From SIF to photosynthesis: Achievements, challenges and opportunities. In AGU Fall Meeting Abstracts (Vol. 2020, pp. B039-02).
24. van der Tol, C., Yang, P., Prikaziuk, E., & Verhoef, W. (2020, December). Energy budget and radiative transfer modelling in the soil, vegetation, atmosphere continuum. In AGU Fall Meeting 2020.
25. Bayat, B., van der Tol, C., Yang, P., Montzka, C., Vereecken, H., & Verhoef, W. (2020, May). Integrating soil moisture in SCOPE model for improving remote sensing of evapotranspiration and photosynthesis under water stress conditions. In EGU General Assembly Conference Abstracts (p. 5658).https://doi.org/10.5194/egusphere-egu2020-5658
26. Celesti, M., Biriukova, K., Campbell, P. K., Cesana, I., Cogliati, S., Damm, A., ... , Yang, P., & Colombo, R. (2020, May). Exploring continuous time series of vegetation hyperspectral reflectance and solar-induced fluorescence through radiative transfer model inversion. In EGU General Assembly Conference Abstracts (p. 14904).https://doi.org/10.5194/egusphere-egu2020-14904
27. Joiner, J., Yoshida, Y., Köehler, P., Campbell, P., Frankenberg, C., van der Tol, C., Yang, P.,... & Sun, Y. (2020). Systematic orbital geometry-dependent variations in satellite solar-induced fluorescence (SIF) retrievals. Remote sensing, 12(15), 2346.https://doi.org/10.3390/rs12152346
28. Tagliabue, G., Celesti, M., Biriukova, K., Campbell, P. K. E., Cesana, I., Cogliati, S., ... Yang, P., & Colombo, R. (2019, December). Exploring continuous time series of vegetation hyperspectral reflectance and solar-induced fluorescence through radiative transfer model inversion. In AGU Fall Meeting Abstracts (Vol. 2019, pp. B11Q-2277).https://doi.org/10.5194/egusphere-egu2020-14904
29. van der Tol, C., Vilfan, N., Dauwe, D., Cendrero-Mateo, M. P., & Yang, P. (2019). The scattering and re-absorption of red and near-infrared chlorophyll fluorescence in the models Fluspect and SCOPE. Remote sensing of environment, 232, 111292.https://doi.org/10.1016/j.rse.2019.111292
30. Bayat, B., van der Tol, C., Yang, P., & Verhoef, W. (2019). Extending the SCOPE model to combine optical reflectance and soil moisture observations for remote sensing of ecosystem functioning under water stress conditions. Remote sensing of environment, 221, 286-301.https://doi.org/10.1016/j.rse.2018.11.021
31. Martini, D., Pacheco-Labrador, J., Perez-Priego, O., Van der Tol, C., El-Madany, T. S., Julitta, T., Yang, P.,... & Migliavacca, M. (2019). Nitrogen and phosphorus effect on sun-induced fluorescence and gross primary productivity in mediterranean grassland. Remote sensing, 11(21), 2562.https://doi.org/10.3390/rs11212562
32. Celesti, M., van der Tol, C., Cogliati, S., Panigada, C., Yang, P., Pinto, F., ... & Rossini, M. (2018). Exploring the physiological information of Sun-induced chlorophyll fluorescence through radiative transfer model inversion. Remote sensing of environment, 215, 97-108.https://doi.org/10.1016/j.rse.2018.05.013
33. van der Tol, C., Vilfan, N., Yang, P., Bayat, B., & Verhoef, W. (2018, July). Modeling reflectance, fluorescence and photosynthesis: Development of the scope model. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 5968-5971). IEEE.https://doi.org/10.1109/IGARSS.2018.8517517
34. Vilfan, N., van der Tal, C., Yang, P., & Verhoef, W. (2018, July). Retrieving photosynthetic capacity parameter from leaf photochemical reflectance and chlorophyll fluorescence. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 5991-5994). IEEE.https://doi.org/10.1109/IGARSS.2018.8517912
35. Vilfan, N., Van der Tol, C., Yang, P., Wyber, R., Malenovský, Z., Robinson, S. A., & Verhoef, W. (2018). Extending Fluspect to simulate xanthophyll driven leaf reflectance dynamics. Remote sensing of environment, 211, 345-356.https://doi.org/10.1016/j.rse.2018.04.012
36. Ni, Z., Liu, Z., Li, Z. L., Nerry, F., Huo, H., Sun, R., Yang, P., & Zhang, W. (2016). Investigation of atmospheric effects on retrieval of sun-induced fluorescence using hyperspectral imagery. Sensors, 16(4), 480.https://doi.org/10.3390/s16040480
37. 王冉,刘志刚,冯海宽,杨沛琦,王庆山,倪卓娅, (2013). 基于近地面高光谱影像的冬小麦日光诱导叶绿素荧光提取与分析.光谱学与光谱分析, 33(9), 2451-2454.http://doi.org/10.3964/j.issn.1000-0593(2013)09-2451-04
38. 王冉, 刘志刚, 杨沛琦, (2012). 植物日光诱导叶绿素荧光遥感原理及研究进展. 地球科学进展. 27(11).https://doi.org/10.11867/j.issn.1001-8166.2012.11.1221
39. 专利-刘志刚, 陈绩, 杨沛琦, 王庆山, 张葳葳, & 倪卓娅等. (2014). 一种叶片主被动叶绿素荧光长时间序列协同观测系统.
论文：
Han D., Liu J.*, Zhang R., et al. Evaluation of the SAIL Radiative Transfer Model for Simulating Canopy Reflectance of Row Crop Canopies. Remote Sensing. 2023; 15(23):5433. https://doi.org/10.3390/rs15235433
Wang J., Liu J.*, Li L. Detecting Photovoltaic Installations in Diverse Landscapes Using Open Multi-Source Remote Sensing Data. Remote Sensing. 2022; 14(24):6296. https://doi.org/10.3390/rs14246296
雷秋佳，刘婧*，曹新运．利用机载LiDAR数据的开放DEM产品精度评估. 武汉大学学报(信息科学版). https://doi.org/10.13203/j.whugis20220421
Liu, J.*, Li, L., Akerblom, M., Wang, T., Skidmore, A., Zhu, X., & Heurich, M. 2021. Comparative Evaluation of Algorithms for Leaf Area Index Estimation from Digital Hemispherical Photography through Virtual Forests. Remote Sensing, 2021, 13(16), 3325 https://doi.org/10.3390/rs13163325
Liu, J.*, Wang, T., Skidmore, A.K., Jones, S., Heurich, M., Beudert, B., Premier, J., 2019. Comparison of terrestrial LiDAR and digital hemispherical photography for estimating leaf angle distribution in European broadleaf beech forests, ISPRS Journal of Photogrammetry and Remote Sensing, 2019, 158: 76-89. https://doi.org/10.1016/j.isprsjprs.2019.09.015
Liu, J.*, Skidmore, A.K., Wang, T., Zhu, X., Premier, J., Heurich, M., Beudert, B., Jones, S., 2019. Variation of leaf angle distribution quantified by terrestrial LiDAR in natural European beech forest. ISPRS Journal of Photogrammetry and Remote Sensing, 148, 208-220. (入选期刊Featured Article) https://doi.org/10.1016/j.isprsjprs.2019.01.005
Liu, J.*, Skidmore, A.K., Jones, S., Wang, T., Heurich, M., Zhu, X., Shi, Y., 2018. Large off-nadir scan angle of airborne LiDAR can severely affect the estimates of forest structure metrics. ISPRS Journal of Photogrammetry and Remote Sensing, 136, 13-25. (入选期刊Featured Article) https://doi.org/10.1016/j.isprsjprs.2017.12.004
Liu, J.*, Skidmore, A.K., Heurich, M., Wang, T.*, 2017. Significant effect of topographic normalization of airborne LiDAR data on the retrieval of plant area index profile in mountainous forests. ISPRS Journal of Photogrammetry and Remote Sensing, 132, 77-87. (入选期刊Featured Article) https://doi.org/10.1016/j.isprsjprs.2017.08.005
Liu, J., Li, P.*, Wang, X., 2015.A new segmentation method for very high resolution imagery using spectral and morphological information. ISPRS Journal of Photogrammetry and Remote Sensing, 101, 145-162. https://doi.org/10.1016/j.isprsjprs.2014.11.009
Zhu, X.*, Liu, J., Skidmore, A.K., Premier, J., Heurich, M., 2020. A voxel matching method for effective leaf area index estimation in temperate deciduous forests from leaf-on and leaf-off airborne LiDAR data. Remote Sensing of Environment, 240, 111696. https://doi.org/10.1016/j.rse.2020.111696
Wang, D., Wan, B.*, Liu, J., Su, Y., Guo, Q., Qiu, P., Wu, X., 2020. Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots, UAV-LiDAR data and Sentinel-2 imagery. International Journal of Applied Earth Observation and Geoinformation, 85, 101986. https://doi.org/10.1016/j.jag.2019.101986
Zhu, X.*, Skidmore, A.K., Wang, T., Liu, J., Darvishzadeh, R., Shi, Y., Premier, J., Heurich, M., 2018. Improving leaf area index (LAI) estimation by correcting for clumping and woody effects using terrestrial laser scanning. Agricultural and Forest Meteorology, 263, 276-286. https://doi.org/10.1016/j.agrformet.2018.08.026
Zhu, X., Skidmore, A.K., Darvishzadeh., R., Niemann, K., Liu, J., Shi, Y., Wang, T., 2018. Foliar and woody materials discriminated using terrestrial LiDAR in a mixed natural forest. International Journal of Applied Earth Observation and Geoinformation, 64, 43-50. https://doi.org/10.1016/j.jag.2017.09.004
Zhu, X., Wang, T., Skidmore, A.K., Darvishzadeh., R., Niemann, K., Liu, J., 2017. Canopy leaf water content estimated using terrestrial LiDAR. Agricultural and Forest Meteorology, 232, 152-162. https://doi.org/10.1016/j.agrformet.2016.08.016
