References

• Aggarwal, C.C. 2018. “An Introduction to Neural Networks.” In Neural Networks and Deep Learning, 1–52. Cham: Springer International Publishing.
   Google Scholar
• Ali, I., Cawkwell, F., Dwyer, E., and Green, S. 2017. “Modeling Managed Grassland Biomass Estimation by Using Multitemporal Remote Sensing Data-A Machine Learning Approach.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 10(No. 7): pp. 3254–3264. doi:10.1109/JSTARS.2016.2561618.
   Web of Science ®Google Scholar
• Asrar, G., Kanemasu, E.T., Jackson, R.D., and Pinter, P.J. 1985. “Estimation of Total Above-Ground Phytomass Production Using Remotely Sensed Data.” Remote Sensing of Environment, Vol. 17(No. 3): pp. 211–220. doi:10.1016/0034-4257(85)90095-1.
   Web of Science ®Google Scholar
• Bala, S.K., and Islam, A.S. 2009. “Correlation between Potato Yield and MODIS-Derived Vegetation Indices.” International Journal of Remote Sensing, Vol. 30(No. 10): pp. 2491–2507. doi:10.1080/01431160802552744.
   Web of Science ®Google Scholar
• Boote, K.J., Jones, J.W., and Pickering, N.B. 1996. “Potential Uses and Limitations of Crop Models (AJ).” Agronomy Journal, Vol. 88: pp. 704–716. doi:10.2134/agronj1996.00021962008800050005x.
   Web of Science ®Google Scholar
• Carlson, T.N., and Ripley, D.A. 1997. “On the Relation between NDVI, Fractional Vegetation Cover, and Leaf Area Index.” Remote Sensing of Environment, Vol. 62(No. 3): pp. 241–252. doi:10.1016/S0034-4257(97)00104-1.
   Web of Science ®Google Scholar
• Chang, L., Sun, P.S., and Liu, S.-R. 2016. “A Review of Plant Spectral Reflectance Response to Water Physiological Changes.” Chinese Journal of Plant Ecology, Vol. 40(No. 1): pp. 80–91. doi:10.17521/cjpe.2015.0267.
   Google Scholar
• Chen, X., Xu, X., Wang, Y., and Zhong, X. 2008. “Found on artificial neural network and genetic algorithm design the ASSEL roll profile.” Paper presented at Proceedings – International Conference on Computer Science and Software Engineering, Hubei, China, December 2008. doi:10.1109/CSSE.2008.1435.
   Google Scholar
• Cicek, H., Sunohara, M., Wilkes, G., McNairn, H., Pick, F., Topp, E., and Lapen, D.R. 2010. “Using Vegetation Indices from Satellite Remote Sensing to Assess Corn and Soybean Response to Controlled Tile Drainage.” Agricultural Water Management, Vol. 98(No. 2): pp. 261–270. doi:10.1016/j.agwat.2010.08.019.
   Web of Science ®Google Scholar
• Cristianini, N., and Shawe-Taylor, J. 2000. An Introduction to Support Vector Machines: And Other Kernel-Based Learning Methods. London: Cambridge University Press.
   Google Scholar
• Darvishzadeh, R., Wang, T., Skidmore, A., Vrieling, A., O’Connor, B., Gara, T., Ens, B., et al. 2019. “Analysis of Sentinel-2 and RapidEye for Retrieval of Leaf Area Index in a Saltmarsh Using a Radiative Transfer Model.” Remote Sensing, Vol. 11(No. 6): pp. 671. doi:10.3390/rs11060671.
   Web of Science ®Google Scholar
• Dash, J., Curran, P.J., Tallis, M.J., Llewellyn, G.M., Taylor, G., and Snoeij, P. 2010. “Validating the MERIS Terrestrial Chlorophyll Index (MTCI) with Ground Chlorophyll Content Data at MERIS Spatial Resolution.” International Journal of Remote Sensing, Vol. 31(No. 20): pp. 5513–5532. doi:10.1080/01431160903376340.
   Web of Science ®Google Scholar
• Dong, T., Liu, J., Shang, J., Qian, B., Ma, B., Kovacs, J.M., Walters, D., Jiao, X., Geng, X., and Shi, Y. 2019. “Assessment of Red-Edge Vegetation Indices for Crop Leaf Area Index Estimation.” Remote Sensing of Environment, Vol. 222: pp. 133–143. doi:10.1016/j.rse.2018.12.032.
   Web of Science ®Google Scholar
• Duthoit, S., and Weiss, M. 2008. “Estimation of Leaf Area and Clumping Indexes of Crops with Hemispherical Photographs.” Agricultural and Forest Meteorology, Vol. 148: pp. 644–655. doi:10.1016/j.agrformet.2007.11.015.
   Web of Science ®Google Scholar
• Eckert, S. 2012. “Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data.” Remote Sensing, Vol. 4(No. 4): pp. 810–829. doi:10.3390/rs4040810.
   Web of Science ®Google Scholar
• Gao, S., Niu, Z., Huang, N., and Hou, X. 2013. “Estimating the Leaf Area Index, Height and Biomass of Maize Using HJ-1 and RADARSAT-2.” International Journal of Applied Earth Observation and Geoinformation, Vol. 24(No. 1): pp. 1–8. doi:10.1016/j.jag.2013.02.002.
   Google Scholar
• Gitelson, A.A., Viña, A., Arkebauer, T.J., Rundquist, D.C., Keydan, G., and Leavitt, B. 2003. “Remote Estimation of Leaf Area Index and Green Leaf Biomass in Maize Canopies.” Geophysical Research Letters, Vol. 30(No. 5): pp. n/a–52. doi:10.1029/2002GL016450.
   Web of Science ®Google Scholar
• Gitelson, A.A., Viña, A., Ciganda, V., Rundquist, D.C., and Arkebauer, T.J. 2005. “Remote Estimation of Canopy Chlorophyll Content in Crops.” Geophysical Research Letters, Vol. 32 (No. 8): pp. 1–4. doi:10.1029/2005GL022688.
   Web of Science ®Google Scholar
• Gitelson, A.A., Verma, S.B., Viña, A., Rundquist, D.C., Keydan, G., Leavitt, B., Arkebauer, T.J., Burba, G.G., and Suyker, A.E. 2003. “Novel Technique for Remote Estimation of CO 2 Flux in Maize.” Geophysical Research Letters, Vol. 30(No. 9): p. 1486. doi:10.1029/2002GL016543.
   Web of Science ®Google Scholar
• Gitelson, A.A., Kaufman, Y.J., and Merzlyak, M.N. 1996. “Use of a Green Channel in Remote Sensing of Global Vegetation from EOS-MODIS.” Remote Sensing of Environment, Vol. 58(No. 3): pp. 289–298. doi:10.1016/S0034-4257(96)00072-7.
   Web of Science ®Google Scholar
• Gitelson, A., and Merzlyak, M.N. 1994. “Spectral Reflectance Changes Associated with Autumn Senescence of Aesculus Hippocastanum L. and Acer Platanoides L. Leaves. Spectral Features and Relation to Chlorophyll Estimation.” Journal of Plant Physiology, Vol. 143(No. 3): pp. 286–292. doi:10.1016/S0176-1617(11)81633-0.
   Web of Science ®Google Scholar
• Gleason, C.J., and Im, J. 2012. “Forest Biomass Estimation from Airborne LiDAR Data Using Machine Learning Approaches.” Remote Sensing of Environment, Vol. 125: pp. 80–91. doi:10.1016/j.rse.2012.07.006.
   Web of Science ®Google Scholar
• Groten, S.M. 1993. “NDVI-Crop Monitoring and Early Yield Assessment of Burkina Faso.” International Journal of Remote Sensing, Vol. 14(No. 8): pp. 1495–1515. doi:10.1080/01431169308953983.
   Web of Science ®Google Scholar
• Haboudane, D., Miller, J.R., Pattey, E., Zarco-Tejada, P.J., and Strachan, I.B. 2004. “Hyperspectral Vegetation Indices and Novel Algorithms for Predicting Green LAI of Crop Canopies: Modeling and Validation in the Context of Precision Agriculture.” Remote Sensing of Environment, Vol. 90(No. 3): pp. 337–352. doi:10.1016/j.rse.2003.12.013.
   Web of Science ®Google Scholar
• Hassoun, M.H. 1995. Fundamentals of Artificial Neural Networks. Massachusetts: MIT Press.
   Google Scholar
• Horie, T., Yajima, M., and Nakagawa, H. 1992. “Yield Forecasting.” Agricultural Systems, Vol. 40(No. 1–3): pp. 211–236. doi:10.1016/0308-521X(92)90022-G.
   Web of Science ®Google Scholar
• Hosseini, M., McNairn, H., Mitchell, S., Dingle Robertson, L., Davidson, A., and Homayouni, S. 2019. “Synthetic Aperture Radar and Optical Satellite Data for Estimating the Biomass of Corn.” International Journal of Applied Earth Observation and Geoinformation, Vol. 83: pp. 101933. doi:10.1016/j.jag.2019.101933.
   Web of Science ®Google Scholar
• Huete, A., Didan, K., Miura, T., Rodriguez, E.P., Gao, X., and Ferreira, L.G. 2002. “Overview of the Radiometric and Biophysical Performance of the MODIS Vegetation Indices.” Remote Sensing of Environment, Vol. 83(No. 1–2): pp. 195–213. doi:10.1016/S0034-4257(02)00096-2.
   Web of Science ®Google Scholar
• Huete, A.R. 1988. “A Soil-Adjusted Vegetation Index (SAVI).” Remote Sensing of Environment, Vol. 25(No. 3): pp. 295–309. doi:10.1016/0034-4257(88)90106-X.
   Web of Science ®Google Scholar
• Huete, A.R., Liu, H.Q., Batchily, K., and van Leeuwen, W. 1997. “A Comparison of Vegetation Indices over a Global Set of TM Images for EOS-MODIS.” Remote Sensing of Environment, Vol. 59(No. 3): pp. 440–451. doi:10.1016/S0034-4257(96)00112-5.
   Web of Science ®Google Scholar
• Kouadio, L., Newlands, N.K., Davidson, A., Zhang, Y., and Chipanshi, A. 2014. “Assessing the Performance of MODIS NDVI and EVI for Seasonal Crop Yield Forecasting at the Ecodistrict Scale.” Remote Sensing, Vol. 6(No. 10): pp. 10193–10214. doi:10.3390/rs61010193.
   Web of Science ®Google Scholar
• Kross, A., McNairn, H., Lapen, D., Sunohara, M., and Champagne, C. 2015. “Assessment of RapidEye Vegetation Indices for Estimation of Leaf Area Index and Biomass in Corn and Soybean Crops.” International Journal of Applied Earth Observation and Geoinformation, Vol. 34(No. 1): pp. 235–248. doi:10.1016/j.jag.2014.08.002.
   Google Scholar
• Lourakis, M. I. a. 2005. “A Brief Description of the Levenberg-Marquardt Algorithm Implemened by Levmar.” Computer Science. https://www.semanticscholar.org/paper/A-Brief-Description-of-the-Levenberg-Marquardt-by-Lourakis/a92844ea0726e0ebb3fdf99b070d1e8e289eb97f.
   Google Scholar
• Javed, F., Chan, G.S.H., Savkin, A.V., Middleton, P.M., Malouf, P., Steel, E., Mackie, J., and Lovell, N.H. 2009. “RBF kernel based support vector regression to estimate the blood volume and heart rate responses during hemodialysis.” Paper presented at Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, Minneapolis, United States, September 2009. doi:10.1109/IEMBS.2009.5332739.
   Google Scholar
• Jordan, C.F. 1969. “Derivation of Leaf-Area Index from Quality of Light on the Forest Floor.” Ecology, Vol. 50(No. 4): pp. 663–666. doi:10.2307/1936256.
   Web of Science ®Google Scholar
• Kottek, M., Grieser, J., Beck, C., Rudolf, B., and Rubel, F. 2006. “World Map of the Köppen-Geiger Climate Classification Updated.” Meteorologische Zeitschrift, Vol. 15(No. 3): pp. 259–263. doi:10.1127/0941-2948/2006/0130.
   Web of Science ®Google Scholar
• Li, J., Cheng, J.-H., Shi, J.-Y., and Huang, F. 2012. “Brief Introduction of Back Propagation (BP) Neural Description of BP Algorithm in Mathematics.” Advances in Computer Science and Information Engineering, Vol. 2: pp. 553–558. doi:10.1007/978-3-642-30223-7_87.
   Google Scholar
• Liu, C., Yin, S.Q., Zhang, M., Zeng, Y., and Liu, J.Y. 2014. “An Improved Grid Search Algorithm for Parameters Optimization on SVM.” Applied Mechanics and Materials, Vol. 644–650(No. 2): pp. 2216–2219. doi:10.4028/www.scientific.net/AMM.644-650.2216.
   Google Scholar
• Magney, T.S., Eitel, J.U.H., and Vierling, L.A. 2017. “Mapping Wheat Nitrogen Uptake from RapidEye Vegetation Indices.” Precision Agriculture, Vol. 18(No. 4): pp. 429–451. doi:10.1007/s11119-016-9463-8.
   Web of Science ®Google Scholar
• Marquardt, D. 1963. “An Algorithm for Least-Squares Estimation of Nonlinear Parameters.” SIAM Journal on Applied Mathematics, Vol. 11(No. 2): pp. 431–441. doi:10.1137/0111030.
   Web of Science ®Google Scholar
• McNairn, H., Jackson, T.J., Wiseman, G., Belair, S., Berg, A., Bullock, P., Colliander, A., et al. 2015. “The Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12): Prelaunch Calibration and Validation of the SMAP Soil Moisture Algorithms.” IEEE Transactions on Geoscience and Remote Sensing, Vol. 53(No. 5): pp. 2784–2801. doi:10.1109/TGRS.2014.2364913.
   Web of Science ®Google Scholar
• Mkhabela, M.S., Bullock, P., Raj, S., Wang, S., and Yang, Y. 2011. “Crop Yield Forecasting on the Canadian Prairies Using MODIS NDVI Data.” Agricultural and Forest Meteorology, Vol. 151(No. 3): pp. 385–393. doi:10.1016/j.agrformet.2010.11.012.
   Web of Science ®Google Scholar
• Nguy-Robertson, A.L., Peng, Y., Gitelson, A.A., Arkebauer, T.J., Pimstein, A., Herrmann, I., Karnieli, A., Rundquist, D.C., and Bonfil, D.J. 2014. “Estimating Green LAI in Four Crops: Potential of Determining Optimal Spectral Bands for a Universal Algorithm.” Agricultural and Forest Meteorology, Vol. 192–193: pp. 140–148. doi:10.1016/j.agrformet.2014.03.004.
   Web of Science ®Google Scholar
• Qi, J., Chehbouni, A., Huete, A.R., Kerr, Y.H., and Sorooshian, S. 1994. “A Modified Soil Adjusted Vegetation Index.” Remote Sensing of Environment, Vol. 48(No. 2): pp. 119–126. doi:10.1016/0034-4257(94)90134-1.
   Web of Science ®Google Scholar
• Qian, B., De Jong, R., Warren, R., Chipanshi, A., and Hill, H. 2009. “Statistical Spring Wheat Yield Forecasting for the Canadian Prairie Provinces.” Agricultural and Forest Meteorology, Vol. 149(No. 6–7): pp. 1022–1031. doi:10.1016/j.agrformet.2008.12.006.
   Web of Science ®Google Scholar
• Ramoelo, A., Skidmore, A.K., Cho, M.A., Schlerf, M., Mathieu, R., and Heitkönig, I.M.A. 2012. “Regional Estimation of Savanna Grass Nitrogen Using the Red-Edge Band of the Spaceborne Rapideye Sensor.” International Journal of Applied Earth Observation and Geoinformation, Vol. 19(No. 1): pp. 151–162. doi:10.1016/j.jag.2012.05.009.
   Google Scholar
• Rouse, J. W. 1974. Monitoring the Vernal Advancement and Retrogradation (Greenwave Effect) of Natural Vegetation. Texas: Texas A&M University; Remote Sensing Center.
   Google Scholar
• Shang, J., McNairn, H., Schulthess, U., Fernandes, R., and Storie, J. 2012. “Estimation of Crop Ground Cover and Leaf Area Index (LAI) of Wheat Using RapidEye Satellite Data: Prelimary Study.” Paper presented at 2012 First International Conference on Agro-Geoinformatics (Agro-Geoinformatics), Shanghai, China, August 2012. doi:10.1109/Agro-Geoinformatics.2012.6311624.
   Google Scholar
• Veloso, A., Mermoz, S., Bouvet, A., Le Toan, T., Planells, M., Dejoux, J.F., and Ceschia, E. 2017. “Understanding the Temporal Behavior of Crops Using Sentinel-1 and Sentinel-2-like Data for Agricultural Applications.” Remote Sensing of Environment, Vol. 199: pp. 415–426. doi:10.1016/j.rse.2017.07.015.
   Web of Science ®Google Scholar
• Wang, L., Zhou, X., Zhu, X., Dong, Z., and Guo, W. 2016. “Estimation of Biomass in Wheat Using Random Forest Regression Algorithm and Remote Sensing Data.” The Crop Journal, Vol. 4(No. 3): pp. 212–219. doi:10.1016/j.cj.2016.01.008.
   Google Scholar
• Willmott, C.J., and Matsuura, K. 2005. “Advantages of the Mean Absolute Error (MAE) over the Root Mean Square Error (RMSE) in Assessing Average Model Performance.” Climate Research, Vol. 30(No. 1): pp. 79–82. PP. doi:10.3354/cr030079.
   Web of Science ®Google Scholar
• Wiseman, G., McNairn, H., Homayouni, S., and Shang, J. 2014. “RADARSAT-2 Polarimetric SAR Response to Crop Biomass for Agricultural Production Monitoring.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 7(No. 11): pp. 4461–4471. doi:10.1109/JSTARS.2014.2322311.
   Web of Science ®Google Scholar
• Xue, J., and Su, B. 2017. “Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications.” Journal of Sensors, Vol. 2017: pp. 1–17. doi:10.1155/2017/1353691.
   Web of Science ®Google Scholar
• Zhang, C., and Kovacs, J.M. 2012. “The Application of Small Unmanned Aerial Systems for Precision Agriculture: A Review.” Precision Agriculture, Vol. 13(No. 6): pp. 693–712. doi:10.1007/s11119-012-9274-5.
   Web of Science ®Google Scholar
• Zillmann, E., Schonert, M., and Weichelt, H. 2015. “Monitoring the Variability of Crop Growth Dynamics in Cereals Using High-Resolution RapidEye Imagery.” Paper presented at 2015 4th International Conference on Agro-Geoinformatics, Agro-Geoinformatics, Istanbul, Turkey, July 2015. doi:10.1109/Agro-Geoinformatics.2015.7248153.
   Google Scholar