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

Author:

Singh Shubham Kumar,Prasad Rajendra,Srivastava Prashant K.,Yadav Suraj A.,Yadav Vijay P.,Sharma Jyoti

Funder

Department of Science and Technology, Ministry of Science and Technology, India

European Space Agency

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Differentiable modeling for soil moisture retrieval by unifying deep neural networks and water cloud model;Remote Sensing of Environment;2024-09

2. Computational methods to retrieve soil moisture using remote sensing data: A review;2024 IEEE 7th International Conference on Advanced Technologies, Signal and Image Processing (ATSIP);2024-07-11

3. Model Construction and Evaluation of Flood Area Estimation Based on SAR and GPS Data;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

4. A MWCMLAI-Net method for LAI inversion in maize and rice using GF-3 and Lutan radar data;International Journal of Digital Earth;2024-04-11

5. Surface soil moisture retrieval based on transfer learning using SAR data on a local scale;International Journal of Remote Sensing;2024-03-21

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