Abstract
Present study explains the analysis of rice crop phenology using optical and SAR C-band of sentinel satellite data. Rice crop phenology is understood and analyzed based on various backscattered polarization. It will be useful to estimate crop acreage when the optical sensors data is not available or with cloud cover. The study also gives information of various stages of rice crop starting from sowing to the harvesting stage, along with NDVI and soil moisture data from SOMS.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Aghamolki, M. T. K., Yusop, M. K., Jaafar, H. Z., Kharidah, S., Musa, M. H., & Zandi, P. (2015). Preliminary analysis of growth and yield parameters in rice cultivars when exposed to different transplanting dates. Electronic Journal of Biology, 11(4), 147–153.
Kuenzer, C., & Knauer, K. (2013). Remote sensing of rice crop areas. International Journal of Remote Sensing, 34(6), 2101–2139.
Nelson, A., Setiyono, T., Rala, A., Quicho, E., Raviz, J., Abonete, P., et al. (2014). Towards an operational SAR-based rice monitoring system in Asia: Examples from 13 demonstration sites across Asia in the RIICE project. Remote Sensing, 6(11), 10773–10812.
Fontanelli, G., Crema, A., Azar, R., Stroppiana, D., Villa, P., & Boschetti, M. (2014). Agricultural crop mapping using optical and SAR multi-temporal seasonal data: A case study in Lombardy region, Italy. In 2014 IEEE Geoscience and Remote Sensing Symposium, 1489–1492.
Zeng, J., Li, Z., Chen, Q., Bi, H., Qiu, J., & Zou, P.: Evaluation of remotely sensed and reanalysis soil moisture products over the Tibetan Plateau using in-situ observations. Remote Sensing of Environment, 163, 91–110.
Nguyen, D. B., & Wagner, W. (2017). European rice cropland mapping with Sentinel-1 data: The Mediterranean region case study. Water, 9(6), 392.
Chen, C. F., Son, N. T., Chen, C. R., Chang, L. Y., & Chiang, S. H. (2016). Rice crop mapping using Sentinel-1A phenological metrics. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 41, 8.
Kurosu, T., Fujita, M., & Chiba, K. (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.
Stendardi, L., Karlsen, S. R., Niedrist, G., Gerdol, R., Zebisch, M., Rossi, M., & Notarnicola, C. (2019). Exploiting time series of Sentinel-1 and Sentinel-2 imagery to detect meadow phenology in mountain regions. Remote Sensing, 11(5), 542.
Wu, M., Yang, C., Song, X., Hoffmann, W. C., Huang, W., Zheng, N., et al. (2016). Monitoring cotton root by synthetic Sentinel-2 NDVI time series using improved spatial and temporal data fusion. Scientific Reports, 8, 2045–2322.
Souza, A., Neto, A., Rossato, L., Alvala, R., & Souza, L. (2018). Use of SMOS L3 Soil moisture data: validation and drought assessment for Pernambuco state, northeast Brazil. Remote Sensing, 10, 1314.
Sánchez, N., González-Zamora, Á., Piles, M., & Martínez-Fernández, J. (2016). A new soil moisture agricultural drought index (smadi) integrating MODIS and SMOS products: A case of study over the Iberian Peninsula. Remote Sensing, 8(4), 287.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Inteti, R.S., Mandla, V.R., Peddada, J.R., Ramesh, N. (2020). Analysis of Rice Crop Phenology Using Sentinel-1 and Sentinel-2 Satellite Data. In: Saride, S., Umashankar, B., Avirneni, D. (eds) Advances in Geotechnical and Transportation Engineering . Lecture Notes in Civil Engineering, vol 71. Springer, Singapore. https://doi.org/10.1007/978-981-15-3662-5_21
Download citation
DOI: https://doi.org/10.1007/978-981-15-3662-5_21
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-3661-8
Online ISBN: 978-981-15-3662-5
eBook Packages: EngineeringEngineering (R0)