A Time-Series Approach to Estimate Soil Moisture Using Polarimetric Radar Data

By Yunjin Kim, J. V. Zyl. IEEE Transactions on Geoscience and Remote Sensing, 2009

346 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Atmospheric Science, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/89a871cc81fe9485b8480b2a33a6d11b3a254165

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Dara Entekhabi
2. Eni G. Njoku
3. K. Papathanassiou
4. Narendra Narayan Das
5. Shane R. Cloude

In Atmospheric Science

1. Aliihsan Sekertekin
2. Dara Entekhabi
3. Eni G. Njoku
4. Narendra Narayan Das
5. Shane R. Cloude
6. Hoshin V. Gupta

In Environmental Engineering

1. Aliihsan Sekertekin
2. Dara Entekhabi
3. Eni G. Njoku
4. K. Papathanassiou
5. Narendra Narayan Das
6. Shane R. Cloude
7. Hoshin V. Gupta

Citations in the corpus

• Radar Remote Sensing of Agricultural Canopies: A Review (2017, methodology): “IEEE, 1998, pp.1244 2366–2368.1245 [68] H. McNairn, J. Boisvert, D. Major, G. Gwyn, R. Brown, and A. Smith, “Identification of agricultural tillage practices1246 from c-band radar backscatter,” Canadian Journal of Remote Sensing, vol. 22, pp. 154–163, 1996.1247 [69] H. McNairn, C. Duguay, J. Boisver”
• An Algorithm for Merging SMAP Radiometer and Radar Data for High-Resolution Soil-Moisture Retrieval (2011, methodology): “The feasibility of using time-series data to compute the regression slope has been demonstrated in [7]–[9].”
• Sensitivity Analysis of Multi-Temporal Sentinel-1 SAR Parameters to Crop Height and Canopy Coverage (2019, background): “of growth cycle and it is affected by vegetation water content and sensitive to the biomass [39].”