Mapping winter-wheat biomass and grain yield based on a crop model and UAV remote sensing

References

• Aase, J. K., and F. H. Siddoway. 1981. “Spring Wheat Yield Estimates from Spectral Reflectance Measurements.” IEEE Transactions on Geoscience and Remote Sensing GE-19: 78–84. doi:10.1109/TGRS.1981.350356.
   Web of Science ®Google Scholar
• Atzberger, C. 2004. “Object-based Retrieval of Biophysical Canopy Variables Using Artificial Neural Nets and Radiative Transfer Models.” Remote Sensing of Environment 93: 53–67. doi:10.1016/j.rse.2004.06.016.
   Web of Science ®Google Scholar
• Atzberger, C., R. Darvishzadeh, M. Immitzer, M. Schlerf, A. Skidmore, and G. le Maire. 2015. “Comparative Analysis of Different Retrieval Methods for Mapping Grassland Leaf Area Index Using Airborne Imaging Spectroscopy.” International Journal of Applied Earth Observation and Geoinformation 43: 19–31. doi:10.1016/j.jag.2015.01.009.
   Web of Science ®Google Scholar
• Bareth, G., J. Bendig, N. Tilly, D. Hoffmeister, H. Aasen, and A. Bolten. 2016. “A Comparison of UAV- and TLS-derived Plant Height for Crop Monitoring: Using Polygon Grids for the Analysis of Crop Surface Models (Csms).” Photogramm. - Fernerkundung - Geoinf. 2016: 85–94. doi:10.1127/pfg/2016/0289.
   Google Scholar
• Battude, M., A. Al Bitar, D. Morin, J. Cros, M. Huc, C. Marais Sicre, V. Le Dantec, and V. Demarez. 2016. “Estimating Maize Biomass and Yield over Large Areas Using High Spatial and Temporal Resolution Sentinel-2 like Remote Sensing Data.” Remote Sensing of Environment 184: 668–681. doi:10.1016/j.rse.2016.07.030.
   Web of Science ®Google Scholar
• Boogaard, H. L., C. A. Diepen, R. P. Van, Rötter, J. C. M. A. Cabrera, and H. H. van Laar, 1998. “WOFOST 7.1. User Guide for the WOFOST 7.1 Crop Growth Simulation Model and WOFOST Control Center 5.1..” Winand Staring Centre.
   Google Scholar
• Bose, P., N. K. Kasabov, L. Bruzzone, and R. N. Hartono. 2016. “Spiking Neural Networks for Crop Yield Estimation Based on Spatiotemporal Analysis of Image Time Series.” IEEE Transactions on Geoscience and Remote Sensing 54: 6563–6573. doi:10.1109/TGRS.2016.2586602.
   Web of Science ®Google Scholar
• Breiman, L. 2001. “Random Forests.” Machine Learning 45: 5–32. doi:10.1023/A:1010933404324.
   Web of Science ®Google Scholar
• Burger, P., F. Bussiere, Y. M. Cabidoche, P. Cellier, P. Debaeke, J. P. Gaudillere, C. Henault, et al. 2003. “An Overview of the Crop Model STICS.” European Journal of Agronomy 18. doi:10.1016/S1161-0301(02)00110-7.
   Web of Science ®Google Scholar
• Campos, I., C. M. U. Neale, T. J. Arkebauer, A. E. Suyker, and I. Z. Gonçalves. 2018. “Water Productivity and Crop Yield: A Simplified Remote Sensing Driven Operational Approach.” Agricultural and Forest Meteorology 249: 501–511. doi:10.1016/j.agrformet.2017.07.018.
   Web of Science ®Google Scholar
• Casa, A., G. Ovando, L. Bressanini, J. Martínez, G. Díaz, and C. Miranda. 2018. “Soybean Crop Coverage Estimation from NDVI Images with Different Spatial Resolution to Evaluate Yield Variability in a Plot.” ISPRS Journal of Photogrammetry and Remote Sensing 146: 531–547. doi:10.1016/j.isprsjprs.2018.10.018.
   Web of Science ®Google Scholar
• Chaparro, D., M. Piles, M. Vall-llossera, A. Camps, A. G. Konings, and D. Entekhabi. 2018. “L-band Vegetation Optical Depth Seasonal Metrics for Crop Yield Assessment.” Remote Sensing of Environment 212: 249–259. doi:10.1016/j.rse.2018.04.049.
   Web of Science ®Google Scholar
• Curnel, Y., A. J. W. de Wit, G. Duveiller, and P. Defourny. 2011. “Potential Performances of Remotely Sensed LAI Assimilation in WOFOST Model Based on an OSS Experiment.” Agricultural and Forest Meteorology 151: 1843–1855. doi:10.1016/j.agrformet.2011.08.002.
   Web of Science ®Google Scholar
• Ding, Y., H. Zhang, K. Zhao, and X. Zheng. 2017. “Investigating the Accuracy of Vegetation Index-based Models for Estimating the Fractional Vegetation Cover and the Effects of Varying Soil Backgrounds Using in Situ Measurements and the PROSAIL Model.” International Journal of Remote Sensing 38: 4206–4223. doi:10.1080/01431161.2017.1312617.
   Web of Science ®Google Scholar
• Donald J, H. C. 1976. “The Biological Yield and Harvest Index of Cereals as Agronomic and Plant Breeding Criteria.” Advances in Agronomy 28: 361–405. doi:10.2135/cropsci2018.10.0645.
   Web of Science ®Google Scholar
• Doraiswamy, P. C., J. L. Hatfield, T. J. Jackson, B. Akhmedov, J. Prueger, and A. Stern. 2004. “Crop Condition and Yield Simulations Using Landsat and MODIS.” Remote Sensing of Environment 92: 548–559. doi:10.1016/j.rse.2004.05.017.
   Web of Science ®Google Scholar
• Fang, H., S. Liang, G. Hoogenboom, J. Teasdale, and M. Cavigelli. 2008. “Corn-yield Estimation through Assimilation of Remotely Sensed Data into the CSM-CERES-Maize Model.” International Journal of Remote Sensing 29: 3011–3032. doi:10.1080/01431160701408386.
   Web of Science ®Google Scholar
• Feret, J. B., C. François, G. P. Asner, A. A. Gitelson, R. E. Martin, L. P. R. Bidel, S. L. Ustin, G. le Maire, and S. Jacquemoud. 2008. “PROSPECT-4 and 5: Advances in the Leaf Optical Properties Model Separating Photosynthetic Pigments.” Remote Sensing of Environment 112: 3030–3043. doi:10.1016/j.rse.2008.02.012.
   Web of Science ®Google Scholar
• Fieuzal, R., C. Marais Sicre, and F. Baup. 2017. “Estimation of Corn Yield Using Multi-temporal Optical and Radar Satellite Data and Artificial Neural Networks.” International Journal of Applied Earth Observation and Geoinformation 57: 14–23. doi:10.1016/j.jag.2016.12.011.
   Web of Science ®Google Scholar
• Gitelson, A. A., Y. J. Kaufman, R. Stark, and D. Rundquist. 2002. “Novel Algorithms for Remote Estimation of Vegetation Fraction.” Remote Sensing of Environment 80: 76–87. doi:10.1016/S0034-4257(01)00289-9.
   Web of Science ®Google Scholar
• Gnyp, M. L., Y. Miao, F. Yuan, S. L. Ustin, K. Yu, Y. Yao, S. Huang, and G. Bareth. 2014. “Hyperspectral Canopy Sensing of Paddy Rice Aboveground Biomass at Different Growth Stages.” Field Crops Research 155: 42–55. doi:10.1016/j.fcr.2013.09.023.
   Web of Science ®Google Scholar
• Hansen, J. W., and J. W. Jones. 2000. “Short Survey: Scaling-up Crop Models for Climate Variability.” Agricultural Systems 65: 43–72. doi:10.1016/S0308-521X(00)00025-1.
   Web of Science ®Google Scholar
• Haralick, R. M., K. Shanmugam, and I. Dinstein. 1973. “Textural Features for Image Classification.” IEEE Transactions on Systems Man and Cybernetics SMC3 610–621. doi:10.1109/TSMC.1973.4309314.
   Web of Science ®Google Scholar
• Heng, L. K., T. Hsiao, S. Evett, T. Howell, and P. Steduto. 2009. “Validating the FAO Aquacrop Model for Irrigated and Water Defi Cient Field Maize.” Agronomy Journal 101: 488–498. doi:10.2134/agronj2008.0029xs.
   Web of Science ®Google Scholar
• Heuvelink, E. 1999. “Evaluation of a Dynamic Simulation Model for Tomato Crop Growth and Development..” Annals of Botany 83: 413–422. doi:10.1006/anbo.1998.0832.
   Web of Science ®Google Scholar
• Holzman, M. E., R. Rivas, and M. C. Piccolo. 2014. “Estimating Soil Moisture and the Relationship with Crop Yield Using Surface Temperature and Vegetation Index.” International Journal of Applied Earth Observation and Geoinformation 28: 181–192. doi:10.1016/j.jag.2013.12.006.
   Web of Science ®Google Scholar
• Hsiao, T. C., L. Heng, P. Steduto, B. Rojas-Lara, D. Raes, and E. Fereres. 2009. “Aquacrop-The FAO Crop Model to Simulate Yield Response to Water: III.” **agronomy Journal 101: 448–459. doi:10.2134/agronj2008.0218s.
   Web of Science ®Google Scholar
• Huang, J., L. Tian, S. Liang, H. Ma, I. Becker-Reshef, Y. Huang, W. Su, X. Zhang, D. Zhu, and W. Wu. 2015. “Improving Winter Wheat Yield Estimation by Assimilation of the Leaf Area Index from Landsat TM and MODIS Data into the WOFOST Model.” Agricultural and Forest Meteorology 204: 106–121. doi:10.1016/j.agrformet.2015.02.001.
   Web of Science ®Google Scholar
• Jacquemoud, S. 1993. “Inversion of the PROSPECT + SAIL Canopy Reflectance Model from AVIRIS Equivalent Spectra: Theoretical Study.” Remote Sensing of Environment 44: 281–292. doi:10.1016/0034-4257(93)90022-P.
   Web of Science ®Google Scholar
• Jégo, G., E. Pattey, S. Morteza Mesbah, J. Liu, and I. Duchesne. 2015. “Impact of the Spatial Resolution of Climatic Data and Soil Physical Properties on Regional Corn Yield Predictions Using the STICS Crop Model.” International Journal of Applied Earth Observation and Geoinformation 41: 11–22. doi:10.1016/j.jag.2015.04.013.
   Web of Science ®Google Scholar
• Jena, B. 2017. “The Effect of Phytoplankton Pigment Composition and Packaging on the Retrieval of Chlorophyll-a Concentration from Satellite Observations in the Southern Ocean.” International Journal of Remote Sensing 38: 3763–3784. doi:10.1080/01431161.2017.1308034.
   Web of Science ®Google Scholar
• Jin, X., G. Yang, X. Xu, H. Yang, H. Feng, Z. Li, J. Shen, C. Zhao, and Y. Lan. 2015. “Combined Multi-temporal Optical and Radar Parameters for Estimating LAI and Biomass in Winter Wheat Using HJ and RADARSAR-2 Data.” Remote Sensing 7: 13251–13272. doi:10.3390/rs71013251.
   Web of Science ®Google Scholar
• Jin, X., G. Yang, Z. Li, X. Xu, J. Wang, and Y. Lan. 2018b. “Estimation of Water Productivity in Winter Wheat Using the AquaCrop Model with Field Hyperspectral Data.” Precision Agriculture 19: 1–17. doi:10.1007/s11119-016-9469-2.
   Web of Science ®Google Scholar
• Jin, X., L. Kumar, Z. Li, H. Feng, X. Xu, G. Yang, and J. Wang. 2018a. “A Review of Data Assimilation of Remote Sensing and Crop Models.” European Journal of Agronomy 92: 141–152. doi:10.1016/j.eja.2017.11.002.
   Web of Science ®Google Scholar
• Jin, X., Z. Li, G. Yang, H. Yang, H. Feng, X. Xu, J. Wang, X. Li, and J. Luo. 2017. “Winter Wheat Yield Estimation Based on Multi-source Medium Resolution Optical and Radar Imaging Data and the AquaCrop Model Using the Particle Swarm Optimization Algorithm.” ISPRS Journal of Photogrammetry and Remote Sensing 126: 24–37. doi:10.1016/j.isprsjprs.2017.02.001.
   Web of Science ®Google Scholar
• Jin, X. L., K. R. Wang, C. H. Xiao, W. Y. Diao, F. Y. Wang, B. Chen, and S. K. Li. 2012. “Comparison of Two Methods for Estimation of Leaf Total Chlorophyll Content Using Remote Sensing in Wheat.” Field Crops Research 135: 24–29. doi:10.1016/j.fcr.2012.06.017.
   Web of Science ®Google Scholar
• Jin, Z., G. Azzari, C. You, S. Di Tommaso, S. Aston, M. Burke, and D. B. Lobell. 2019. “Smallholder Maize Area and Yield Mapping at National Scales with Google Earth Engine.” Remote Sensing of Environment 228: 115–128. doi:10.1016/j.rse.2019.04.016.
   Web of Science ®Google Scholar
• Kennedy, J., and R. Eberhart. 1995. “Particle Swarm Optimization.” In Proceedings of International Conference on Neural Networks (ICNN 95), edited by C. Sammut and G. I. Webb, 1942–1948. Boston, MA: Springer US. doi:10.1007/978-0-387-30164-8_630.
   Google Scholar
• Kogan, F., N. Kussul, T. Adamenko, S. Skakun, O. Kravchenko, O. Kryvobok, A. Shelestov, A. Kolotii, O. Kussul, and A. Lavrenyuk. 2013. “Winter Wheat Yield Forecasting in Ukraine Based on Earth Observation, Meteorologicaldata and Biophysical Models.” International Journal of Applied Earth Observation and Geoinformation 23: 192–203. doi:10.1016/j.jag.2013.01.002.
   Web of Science ®Google Scholar
• Li, Y., Q. Zhou, J. Zhou, G. Zhang, C. Chen, and J. Wang. 2014. “Assimilating Remote Sensing Information into a Coupled Hydrology-crop Growth Model to Estimate Regional Maize Yield in Arid Regions.” Ecological Modelling 291: 15–27. doi:10.1016/j.ecolmodel.2014.07.013.
   Web of Science ®Google Scholar
• Lobell, D. B. 2013. “The Use of Satellite Data for Crop Yield Gap Analysis.” Field Crops Research 143: 56–64. doi:10.1016/j.fcr.2012.08.008.
   Web of Science ®Google Scholar
• Lobell, D. B., G. P. Asner, J. I. Ortiz-Monasterio, and T. L. Benning. 2003. “Remote Sensing of Regional Crop Production in the Yaqui Valley, Mexico: Estimates and Uncertainties.” Agriculture, Ecosystems & Environment 94: 205–220. doi:10.1016/S0167-8809(02)00021-X.
   Web of Science ®Google Scholar
• Lorite, I. J., M. García-Vila, C. Santos, M. Ruiz-Ramos, and E. Fereres. 2013. “AquaData and AquaGIS: Two Computer Utilities for Temporal and Spatial Simulations of Water-limited Yield with AquaCrop.” Computers and Electronics in Agriculture 96: 227–237. doi:10.1016/j.compag.2013.05.010.
   Web of Science ®Google Scholar
• Luo, B., C. Yang, J. Chanussot, and L. Zhang. 2013. “Crop Yield Estimation Based on Unsupervised Linear Unmixing of Multidate Hyperspectral Imagery.” IEEE Transactions on Geoscience and Remote Sensing 51: 162–173. doi:10.1109/TGRS.2012.2198826.
   Web of Science ®Google Scholar
• Machwitz, M., L. Giustarini, C. Bossung, D. Frantz, M. Schlerf, H. Lilienthal, L. Wandera, P. Matgen, L. Hoffmann, and T. Udelhoven. 2014. “Enhanced Biomass Prediction by Assimilating Satellite Data into a Crop Growth Model.” Environmental Modelling and Software 62: 437–453. doi:10.1016/j.envsoft.2014.08.010.
   Web of Science ®Google Scholar
• Meroni, M., D. Fasbender, R. Balaghi, M. Dali, M. Haffani, I. Haythem, J. Hooker, et al. 2016. “Evaluating NDVI Data Continuity between SPOT-VEGETATION and PROBA-V Missions for Operational Yield Forecasting in North African Countries.” IEEE Transactions on Geoscience and Remote Sensing 54: 795–804. doi:10.1109/TGRS.2015.2466438.
   Web of Science ®Google Scholar
• Meyer, G. E., and J. C. Neto. 2008. “Verification of Color Vegetation Indices for Automated Crop Imaging Applications.” Computers and Electronics in Agriculture 63: 282–293. doi:10.1016/j.compag.2008.03.009.
   Web of Science ®Google Scholar
• Mo, X., S. Liu, Z. Lin, Y. Xu, Y. Xiang, and T. R. McVicar. 2005. “Prediction of Crop Yield, Water Consumption and Water Use Efficiency with a SVAT-crop Growth Model Using Remotely Sensed Data on the North China Plain.” Ecological Modelling 183: 301–322. doi:10.1016/j.ecolmodel.2004.07.032.
   Web of Science ®Google Scholar
• Mutanga, O., E. Adam, and M. A. Cho. 2012. “High Density Biomass Estimation for Wetland Vegetation Using Worldview-2 Imagery and Random Forest Regression Algorithm.” International Journal of Applied Earth Observation and Geoinformation 18: 399–406. doi:10.1016/j.jag.2012.03.012.
   Web of Science ®Google Scholar
• Ovando, G., S. Sayago, and M. Bocco. 2018. “Evaluating Accuracy of DSSAT Model for Soybean Yield Estimation Using Satellite Weather Data.” ISPRS Journal of Photogrammetry and Remote Sensing 138: 208–217. doi:10.1016/j.isprsjprs.2018.02.015.
   Web of Science ®Google Scholar
• Pu, L., S. Zhang, J. Yang, L. Chang, and S. Bai. 2019. “Spatio-temporal Dynamics of Maize Potential Yield and Yield Gaps in Northeast China from 1990 to 2015.” International Journal of Environmental Research and Public Health 16: 1211. doi:10.3390/ijerph16071211.
   Web of Science ®Google Scholar
• Ren, J., Z. Chen, Q. Zhou, and H. Tang. 2008. “Regional Yield Estimation for Winter Wheat with MODIS-NDVI Data in Shandong, China.” International Journal of Applied Earth Observation and Geoinformation 10: 403–413. doi:10.1016/j.jag.2007.11.003.
   Web of Science ®Google Scholar
• Rouse, J. W., R. H. Hass, J. A. Schell, and D. W. Deering. 1973. “Monitoring Vegetation Systems in the Great Plains with ERTS.” Third Earth Resources Technology Satellite-1 Symposium 1: 309–317. doi:org/citeulike-article-id:12009708.
   Google Scholar
• Sakamoto, T., A. A. Gitelson, and T. J. Arkebauer. 2014. “Near Real-time Prediction of U.S. Corn Yields Based on Time-series MODIS Data.” Remote Sensing of Environment 147: 219–231. doi:10.1016/j.rse.2014.03.008.
   Web of Science ®Google Scholar
• Santi, E., S. Paloscia, S. Pettinato, G. Fontanelli, M. Mura, C. Zolli, F. Maselli, M. Chiesi, L. Bottai, and G. Chirici. 2017. “The Potential of Multifrequency SAR Images for Estimating Forest Biomass in Mediterranean Areas.” Remote Sensing of Environment 200: 63–73. doi:10.1016/j.rse.2017.07.038.
   Web of Science ®Google Scholar
• Setiyono, T., A. Nelson, and F. Holecz. 2014. “Remote Sensing Based Crop Yield Monitoring and Forecasting.” Expert Meeting on Crop Monitoring for Improved Food Security,Vientiane, Laos, pp. 1-12.
   Google Scholar
• Sousa, D., and C. Small. 2017. “Global Cross-calibration of Landsat Spectral Mixture Models.” Remote Sensing of Environment 192: 139–149. doi:10.1016/j.rse.2017.01.033.
   Web of Science ®Google Scholar
• Steduto, P., T. C. Hsiao, D. Raes, and E. Fereres. 2009. “Aquacrop-the FAO Crop Model to Simulate Yield Response to Water: I.” Agronomy Journal** 101: 426–437. doi:10.2134/agronj2008.0139s.
   Web of Science ®Google Scholar
• Tilly, N., D. Hoffmeister, Q. Cao, V. Lenz-Wiedemann, Y. Miao, and G. Bareth. 2015. “Transferability of Models for Estimating Paddy Rice Biomass from Spatial Plant Height Data.” Agriculture 5: 538–560. doi:10.3390/agriculture5030538.
   Google Scholar
• Verhoef, W. 1985. “Earth Observation Modeling Based on Layer Scattering Matrices.” Remote Sensing of Environment 17: 165–178. doi:10.1016/0034-4257(85)90072-0.
   Web of Science ®Google Scholar
• Verrelst, J., E. Romijn, and L. Kooistra. 2012. “Mapping Vegetation Density in a Heterogeneous River Floodplain Ecosystem Using Pointable CHRIS/PROBA Data.” Remote Sensing 4: 2866–2889. doi:10.3390/rs4092866.
   Web of Science ®Google Scholar
• Verrelst, J., J. P. Rivera, F. Veroustraete, J. Muñoz-Marí, J. G. P. W. Clevers, G. Camps-Valls, and J. Moreno. 2015. “Experimental Sentinel-2 LAI Estimation Using Parametric, Non-parametric and Physical Retrieval Methods - A Comparison.” ISPRS Journal of Photogrammetry and Remote Sensing 108: 260–272. doi:10.1016/j.isprsjprs.2015.04.013.
   Web of Science ®Google Scholar
• Verrelst, J., N. Sabater, J. P. Rivera, J. Muñoz-Marí, J. Vicent, G. Camps-Valls, and J. Moreno. 2016. “Emulation of Leaf, Canopy and Atmosphere Radiative Transfer Models for Fast Global Sensitivity Analysis.” Remote Sensing 8: 1–27. doi:10.3390/rs8080673.
   Web of Science ®Google Scholar
• Wang, Y., X. Xu, L. Huang, G. Yang, L. Fan, P. Wei, and G. Chen. 2019. “An Improved CASA Model for Estimating Winter Wheat Yield from Remote Sensing Images.” Remote Sensing 11. doi:10.3390/rs11091088.
   Web of Science ®Google Scholar
• Wu, L., X. Liu, P. Wang, B. Zhou, M. Liu, and X. Li. 2013. “The Assimilation of Spectral Sensing and the WOFOST Model for the Dynamic Simulation of Cadmium Accumulation in Rice Tissues.” International Journal of Applied Earth Observation and Geoinformation 25: 66–75. doi:10.1016/j.jag.2013.04.002.
   Web of Science ®Google Scholar
• Xing, H., X. Xu, Z. Li, Y. Chen, H. Feng, G. Yang, and Z. Chen. 2017. “Global Sensitivity Analysis of the AquaCrop Model for Winter Wheat under Different Water Treatments Based on the Extended Fourier Amplitude Sensitivity Test.” Journal of Integrative Agriculture 16: 2444–2458. doi:10.1016/S2095-3119(16)61626-X.
   Web of Science ®Google Scholar
• Yang, L., K. Jia, S. Liang, M. Liu, X. Wei, Y. Yao, X. Zhang, and D. Liu. 2018. “Spatio-temporal Analysis and Uncertainty of Fractional Vegetation Cover Change over Northern China during 2001-2012 Based on Multiple Vegetation Data Sets.” Remote Sensing 10:1–15. doi:10.3390/rs10040549.
   Web of Science ®Google Scholar
• Yousfi, S., A. Gracia-Romero, N. Kellas, M. Kaddour, A. Chadouli, M. Karrou, J. L. Araus, and M. D. Serret. 2019. “Combined Use of Low-Cost Remote Sensing Techniques and δ13C to Assess Bread Wheat Grain Yield under Different Water and Nitrogen Conditions.” Agronomy 9: 285. doi:10.3390/agronomy9060285.
   Web of Science ®Google Scholar
• Yu, G., W. Yang, B. Matsushita, R. Li, Y. Oyama, and T. Fukushima. 2014. “Remote Estimation of Chlorophyll-a in Inland Waters by a NIR-red-based Algorithm: Validation in Asian Lakes.” Remote Sensing 6: 3492–3510. doi:10.3390/rs6043492.
   Web of Science ®Google Scholar
• Yue, J., G. Yang, C. Li, Z. Li, Y. Wang, H. Feng, and B. Xu. 2017. “Estimation of Winter Wheat Above-ground Biomass Using Unmanned Aerial Vehicle-based Snapshot Hyperspectral Sensor and Crop Height Improved Models.” Remote Sensing 9: 1–19. doi:10.3390/rs9070708.
   Web of Science ®Google Scholar
• Yue, J., G. Yang, Q. Tian, H. Feng, K. Xu, and C. Zhou. 2019. “Estimate of Winter-wheat Above-ground Biomass Based on UAV Ultrahigh-ground-resolution Image Textures and Vegetation Indices.” ISPRS Journal of Photogrammetry and Remote Sensing 150: 226–244. doi:10.1016/j.isprsjprs.2019.02.022.
   Web of Science ®Google Scholar
• Yue, J., H. Feng, G. Yang, and Z. Li. 2018b. “A Comparison of Regression Techniques for Estimation of Above-ground Winter Wheat Biomass Using Near-surface Spectroscopy.” Remote Sensing 10: 66. doi:10.3390/rs10010066.
   Web of Science ®Google Scholar
• Yue, J., H. Feng, X. Jin, H. Yuan, Z. Li, C. Zhou, G. Yang, and Q. Tian. 2018a. “A Comparison of Crop Parameters Estimation Using Images from UAV-Mounted Snapshot Hyperspectral Sensor and High-Definition Digital Camera.” Remote Sensing 10: 1138. doi:10.3390/rs10071138.
   Web of Science ®Google Scholar
• Zhang, Y., B. Yang, X. Liu, and C. Wang. 2017. “Estimation of Rice Grain Yield from Dual-polarization Radarsat-2 SAR Data by Integrating a Rice Canopy Scattering Model and a Genetic Algorithm.” International Journal of Applied Earth Observation and Geoinformation 57: 75–85. doi:10.1016/j.jag.2016.12.014.
   Web of Science ®Google Scholar