1,284
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Leaf area index estimation from the time-series SAR data using the AIEM-MWCM model

, &
Pages 4385-4403 | Received 10 Jul 2023, Accepted 12 Oct 2023, Published online: 23 Oct 2023

References

  • Amin, E., V. Jochem, J. P. Rivera-Caicedo, L. Pipia, A. Ruiz-Verdú, and J. Moreno. 2021. “Prototyping Sentinel-2 Green LAI and Brown LAI Products for Cropland Monitoring.” Remote Sensing of Environment 255: 112168. https://doi.org/10.1016/j.rse.2020.112168.
  • Anderson, M. C., C. M. U. Neale, F. Li, J. M. Norman, W. P. Kustas, H. Jayanthi, and J. Chavez. 2004. “Upscaling Ground Observations of Vegetation Water Content, Canopy Height, and Leaf Area Index During SMEX02 Using Aircraft and Landsat Imagery.” Remote Sensing of Environment 92 (4): 447–464. https://doi.org/10.1016/j.rse.2004.03.019.
  • Attema, E. P. W., and F. T. Ulaby. 1978. “Vegetation Modeled as a Water Cloud.” Radio Science 13: 357–364. https://doi.org/10.1029/rs013i002p00357.
  • Dubois, P. C., V. Z. Jakobl, and T. Engman. 1995. “Measuring Soil Moisture with Imaging Radars.” IEEE Transactions on Geoscience and Remote Sensing 33 (4): 915–926. https://doi.org/10.1109/36.406677.
  • Emilie, B., W. François, C. François, B. Patrick, and D. Pierre. 2015. “Maize Leaf Area Index Retrieval from Synthetic Quad pol SAR Time Series Using the Water Cloud Model.” Remote Sensing 7: 16204–16225. https://doi.org/10.3390/rs71215818.
  • Gao, S., Z. Niu, and C. Y. Wu. 2010. “Multi-polarization EnvisatASAR Images as a Function of Leaf Area Index (LAI) of White Poplar and Desert Date Plantations.” International Journal of Remote Sensing 31 (4): 1095–1102. https://doi.org/10.1080/01431160903283827.
  • Giovanni , C., E. G. Mireille, S. Giuseppe, and V. Luisa. 2017. “Multitemporal SAR Image Despeckling Based on Block-Matching and Collaborative Filtering.” IEEE Transactions on Geoscience and Remote Sensing 55 (10): 5467–5480. https://doi.org/10.1109/TGRS.2017.2707806.
  • Inge, J., F. Stefan, N. Kris, M. Bart, C. Pol, W. Marie, and B. Frédéric. 2004. “Review of Methods for in Situ Leaf Area Index Determination: Part I. Theories, Sensors and Hemispherical Photography.” Agricultural & Forest Meteorology 121 (1–2): 19–35. https://doi.org/10.1016/j.agrformet.2003.08.027.
  • Jafari, M., and A. Keshavarz. 2021. “Improving CERES-Wheat Yield Forecasts by Assimilating Dynamic Landsat-Based Leaf Area Index: A Case Study in Iran.” Journal of the Indian Society of Remote Sensing, 1–14. https://doi.org/10.1007/s12524-021-01359-w.
  • Jarlan, L., G. Balsamo, S. Lafont, A. Beljaars, J. C. Calvet, and E. Mougin. 2008. “Analysis of Leaf Area Index in the ECMWF Land Surface Model and Impact on Latent Heat and Carbon Fluxes: Application to West Africa.” Journal of Geophysical Research: Atmospheres 113 (24): 1–22. https://doi.org/10.1029/2007JD009370.
  • Kurosu, T., M. Fujita, and K. Chibae. 1995. “Monitoring of Rice Crop Growth from Space Using the ERS-1 C-Band SAR.” IEEE Transactions on Geoscience and Remote Sensing 33 (4): 1092–1096. https://doi.org/10.1109/36.406698.
  • Li, X. J., H.Q Du, G. M. Zhou, F. J. Mao, M. Zhang, N. Han, W. L. Fan, et al. 2021. “Phenology Estimation of Subtropical Bamboo Forests Based on Assimilated MODIS LAI Time Series Data.” ISPRS Journal of Photogrammetry and Remote Sensing 173: 262–277. https://doi.org/10.1016/j.isprsjprs.2021.01.018.
  • Mandal, D., M. Hosseini, H. McNairn, V. Kumar, A. Bhattacharya, Y. S. Rao, S. Mitchell, L. D. Robertson, A. Davidson, and K. Dabrowska-Zielinska. 2019. “An Investigation of Inversion Methodologies to Retrieve the Leaf Area Index of Corn from C-Band SAR Data.” International Journal of Applied Earth Observation and Geoinformation 82: 101893. https://doi.org/10.1016/j.jag.2019.06.003.
  • Mansaray, L. R., D. Zhang, Z. Zhou, and J. Huang. 2017. “Evaluating the Potential of Temporal Sentinel-1A Data for Paddy Rice Discrimination at Local Scales.” Remote Sensing Letters 8: 967–976. https://doi.org/10.1080/2150704X.2017.1331472.
  • Mehdi, H., M. N. Heather, M. Amine, and P. Anna. 2015. “Estimation of Leaf Area Index (LAI) in Corn and Soybeans Using Multi-Polarization C-and L-Band Radar Data.” Remote Sensing of Environment 170: 77–89. https://doi.org/10.1016/j.rse.2015.09.002.
  • Pauline , D., C. Thomas, H. M. Laurence, and C. Samuel. 2014. “Combined use of Multi-Temporal Optical and Radar Satellite Images for Grassland Monitoring.” Remote Sensing 6 (7): 6163–6182. https://doi.org/10.3390/rs6076163.
  • Ren, Z. B., Y. X. Du, X. Y. He, R. L. Pu, H. F. Zheng, and H. D. Hu. 2018. “Spatiotemporal Pattern of Urban Forest Leaf Area Index in Response to Rapid Urbanization and Urban Greening.” Journal of Forestry Research 29 (03): 785–796. https://doi.org/10.1007/s11676-017-0480-x.
  • Shubham, K. S., P. Rajendra, K. S. Prashant, A. Y. Suraj, P. Y. Vijay, and S. Jyoti. 2022. “Incorporation of First-Order Backscattered Power in Water Cloud Model for Improving the Leaf Area Index and Soil Moisture Retrieval Using Dual-Polarized Sentinel-1 SAR Data.” Remote Sensing of Environment, https://doi.org/10.1016/J.RSE.2023.113756.
  • Sonia, A., N. Andrew, de B. Kees, S. Andrew, L. Alice, M. Aileen, and J. P. Q. Eduardo. 2019. “Relating X-Band SAR Backscattering to Leaf Area Index of Rice in Different Phenological Phases.” Remote Sensing 11 (12): 1462. https://doi.org/10.3390/rs11121462.
  • Tao, L., J. Li, J. Jiang, and X. Chen. 2016. “Leaf Area Index Inversion of Winter Wheat Using Modified Water-Cloud Model.” IEEE Geoscience & Remote Sensing Letters 13 (6): 816–820. https://doi.org/10.1109/LGRS.2016.2546945.
  • Toan, T. L., H. Laur, E. Mougin, and A. Lopes. 1989. “Multitemporal and Dual-Polarization Observations of Agricultural Vegetation Covers by X-Band SAR Images.” IEEE Transactions on Geoscience and Remote Sensing 27: 709–718. https://doi.org/10.1109/TGRS.1989.1398243.
  • Verma, B., R. Prasad, P. K. Srivastava, S. A. Yadav, P. Singh, and R. K. Singh. 2022. “Investigation of Optimal Vegetation Indices for Retrieval of Leaf Chlorophyll and Leaf Area Index Using Enhanced Learning Algorithms.” Computers and Electronics in Agriculture 192: 106581. https://doi.org/10.1016/j.compag.2021.106581.
  • Wang, Y. B., Y. H. Wang, Z. H. Li, P. T. Yu, and X. S. Han. 2020. “Interannual Variation of Transpiration and its Modeling of a Larch Plantation in Semiarid Northwest China.” Forests 11 (12): 1303. https://doi.org/10.3390/f11121303.
  • Wu, T. D., K. S. Chen, J. C. Shi, and A. K. Fung. 2001. “A Transitio Model for the Reflection Coefficient in Surface Scattering.” IEEE Transactions on Geoscience and Remote Sensing 39 (9): 2040–2050. https://doi.org/10.1109/36.951094.
  • Yadav, V. P., R. Prasad, and R. Bala. 2021. “Leaf Area Index Estimation of Wheat Crop Using Modified Water Cloud Model from the Time-Series SAR and Optical Satellite Data.” Geocarto International 36: 791–802. https://doi.org/10.1080/10106049.2019.1624984.
  • Yan, G. J., R. H. Hu, J. H. Luo, M. Weiss, H. L. Jing, X. H. Mu, D. H. Xie, and W. M. Zhang. 2019. “Review of Indirect Optical Measurements of Leaf Area Index: Recent Advances, Challenges, and Perspectives.” Agricultural and Forest Meteorology 265 (15): 390–411. https://doi.org/10.1016/j.agrformet.2018.11.033.
  • Yang, Z., K. Li, Y. Shao, B. Brisco, and L. Liu. 2016. “Estimation of Paddy Rice Variables with a Modified Water Cloud Model and Improved Polarimetric Decomposition Using Multi-Temporal RADARSAT-2 Images.” Remote Sensing 8 (10): 878. https://doi.org/10.3390/rs8100878.
  • Zhang, L. L., Q. Y. Meng, S. Yao, Q. Wang, J. Y. Zeng, S. H. Zhao, and J. W. Ma. 2018. “Soil Moisture Retrieval from the Chinese GF-3 Satellite and Optical Data Over Agricultural Fields.” Sensors 18 (8): 2675. https://doi.org/10.3390/s18082675.