Fusion of Multispectral and Microwave Sensor Data for Monitoring Land Surface Temperature in Agro Meteorological Studies

Authors

  • MAHESH PALAKURU School of Agricultural Sciences, Malla Reddy University, Hyderabad, Telangana, India
  • SURYA PRAKASH REDDY M School of Agricultural Sciences, Malla Reddy University, Hyderabad, Telangana, India
  • ASHWINI KUMAR RAK College of Agriculture, Sehore, Madhya Pradesh, India
  • SUNDAR BORKAR Bhaganthrao Mandloi College of Agriculture, Ramnagar, Khandwa-450001, Madhya Pradesh, India
  • JAWAHARLAL D Professor Jayashankar Telangana Agricultural University, Rajendranagar, Hyderabad, India
  • SAI KUMAR R Professor Jayashankar Telangana Agricultural University, Rajendranagar, Hyderabad, India
  • SUDHARSHANA C. College of Agriculture, Annamacharya University, Rajampeta, Andhra Pradesh, India
  • BABY Y Annamacharya Institute of Technology & Sciences, Venkatapuram, Renigunta, Tirupati, Chitoor District, Andhra Pradesh, India

DOI:

https://doi.org/10.54386/jam.v28i2.3276

References

Anderson, M. C., Allen, R. G., Morse, A., & Kustas, W. P. (2016). Agro-meteorological applications of fused land surface temperature data. Agricultural and Forest Meteorology, 216, 1–15. https://doi.org/10.1016/j.agrformet.2015.10.002

Dash, P., Lanza, L. G., & Fox, N. T. (2023). Emissivity correction in microwave–optical fusion for land surface temperature estimation. International Journal of Remote Sensing, 44(5), 1234–1256.

Du, C., Ren, H., Qin, Q., & Li, Z. L. (2020). Microwave land surface temperature estimation using Ku-band polarimetric observations. IEEE Transactions on Geoscience and Remote Sensing, 58(7), 4567–4578. https://doi.org/10.1109/TGRS.2019.2960123

Jiménez-Muñoz, J. C., Sobrino, J. A., Skoković, D., & Mattar, C. (2014). Land surface temperature retrieval methods from Landsat-8 thermal infrared sensor data. IEEE Geoscience and Remote Sensing Letters, 11(10), 1840–1843. https://doi.org/10.1109/LGRS.2014.2312032

Karnieli, A., Agam, N., Pinker, R. T., Atlas, R., Bayarjargal, Y., Berk, Y., et al. (2018). Use of NDVI and land surface temperature for drought assessment. Remote Sensing, 10(12), 1885. https://doi.org/10.3390/rs10121885

Kumar, A., Singh, R. P., & Patel, N. R. (2022). SCATSAT-1 applications for land surface monitoring in monsoon-dominated regions. Current Science, 122(5), 567–575.

Li, Z. L., Tang, B. H., Wu, H., Ren, H., Yan, G., Wan, Z., et al. (2013). Satellite-derived land surface temperature: Current status and perspectives. Remote Sensing of Environment, 131, 14–37. https://doi.org/10.1016/j.rse.2012.12.008

Mohanty, S., Patel, N. R., & Rathore, V. S. (2021). Fusion of Ku-band scatterometer and optical data for agricultural applications. ISPRS Journal of Photogrammetry and Remote Sensing, 175, 45–60. https://doi.org/10.1016/j.isprsjprs.2021.02.012

Palakuru, M., & Yarrakula, K. (2019). Study on paddy phenomics ecosystem and yield estimation using space-borne multi-sensor remote sensing data. Journal of Agrometeorology, 21(2), 115–123.

Palakuru, M., Adamala, S., & Debnath, S. (2020). Application of traditional irrigation systems for sustainable agriculture in India. International Journal of Modern Agriculture, 9(4), 12–22.

Rozenstein, O., Zhao, W., & Dash, J. (2019). Use of SCATSAT-1 sigma-0 for soil moisture and land surface temperature estimation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(9), 3456–3467. https://doi.org/10.1109/JSTARS.2019.2924538

Sobrino, J. A., Li, Z. L., & Romaguera, M. (2019). Split-window algorithm for land surface temperature retrieval from Landsat-8 data. Remote Sensing of Environment, 225, 1–12. https://doi.org/10.1016/j.rse.2019.02.017

Wang, F., Qin, Z., Song, X., Zhou, H., & Xiao, W. (2015). An improved mono-window algorithm for land surface temperature retrieval from Landsat-8 TIRS. Remote Sensing, 7(9), 11244–11263. https://doi.org/10.3390/rs70911244

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Published

04-06-2026

How to Cite

PALAKURU, M., M, S. P. R., ASHWINI KUMAR, BORKAR, S., D, J., R, S. K., C., S., & Y, B. (2026). Fusion of Multispectral and Microwave Sensor Data for Monitoring Land Surface Temperature in Agro Meteorological Studies. Journal of Agrometeorology, 28(2), 269–273. https://doi.org/10.54386/jam.v28i2.3276

Issue

Vol. 28 No. 2 (2026): June

Section

Short Communication

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Copyright (c) 2026 Mahesh Palakuru, Surya Prakash Reddy M, Aswini Kumar, Sundar Borkar, JAWAHARLAL D, SAI KUMAR R, Sudharsana C, BABY Y

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