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http://dx.doi.org/10.7780/kjrs.2021.37.6.1.5

Analysis of the Cloud Removal Effect of Sentinel-2A/B NDVI Monthly Composite Images for Rice Paddy and High-altitude Cabbage Fields  

Eun, Jeong (UST21)
Kim, Sun-Hwa (UST21)
Kim, Taeho (UST21)
Publication Information
Korean Journal of Remote Sensing / v.37, no.6_1, 2021 , pp. 1545-1557 More about this Journal
Abstract
Crops show sensitive spectral characteristics according to their species and growth conditions and although frequent observation is required especially in summer, it is difficult to utilize optical satellite images due to the rainy season. To solve this problem, Constrained Cloud-Maximum Normalized difference vegetation index Composite (CC-MNC) algorithm was developed to generate periodic composite images with minimal cloud effect. In thisstudy, using this method, monthly Sentinel-2A/B Normalized Difference Vegetation Index (NDVI) composite images were produced for paddies and high-latitude cabbage fields from 2019 to 2021. In August 2020, which received 200mm more precipitation than other periods, the effect of clouds, was also significant in MODIS NDVI 16-day composite product. Except for this period, the CC-MNC method was able to reduce the cloud ratio of 45.4% of the original daily image to 14.9%. In the case of rice paddy, there was no significant difference between Sentinel-2A/B and MODIS NDVI values. In addition, it was possible to monitor the rice growth cycle well even with a revisit cycle 5 days. In the case of high-latitude cabbage fields, Sentinel-2A/B showed the short growth cycle of cabbage well, but MODIS showed limitations in spatial resolution. In addition, the CC-MNC method showed that cloud pixels were used for compositing at the harvest time, suggesting that the View Zenith Angle (VZA) threshold needsto be adjusted according to the domestic region.
Keywords
CC-MNC; NDVI; Sentinel-2A/B; cloud-free composite; Crop monitoring;
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1 Kim, S.H., J. Eun, 2021. Development of Cloud and Shadow Detection Algorithm for Periodic Composite of Sentinel-2A/B Satellite Images, Korean Journal of Remote Sensing, 37(5-1): 989-998 (in Korean with English abstract)..   DOI
2 Skakun, S., C.O. Justice, E. Vermote, and J.C. Roger, 2017. Transitioning from MODIS to VIIRS: an analysis of inter-consistency of NDVI data sets for agricultural monitoring, International Journal of Remote Sensing, 39(4): 971-992.   DOI
3 Holben, B.N., 1986. Characteristics of maximum-value composite images from temporal AVHRR data, International Journal of Remote Sensing, 7: 1417-1434.   DOI
4 Botta, A., N. Viovy, and P. Ciais, 2000. A global prognostic scheme of leaf onset using satellite data, Global Change Biology, 6: 709-725.   DOI
5 Griffiths, P., C. Nendel, and P. Hostert, 2019. Intraannual reflectance composites from Sentinel-2 and Landsat for national-scale crop and land cover mapping, Remote Sensing of Environment, 220: 135-151.   DOI
6 Dickinson, R.E., A. Henderson-Sellers, P.J. Kennedy, and M.F. Wilson, 1986. Biosphere-Atmosphere Transfer Scheme (BATS) for the NCAR CCM, NATIONAL CENTER FOR: ATMOSPHERIC RESEARCH, Boulder, CO, USA.
7 Fraser, A.D., R.A. Massom, and K.J. Michael, 2009. A method for compositing polar MODIS satellite images to remove cloud cover for landfast seaice detection, IEEE Trans Actions on Geoscience and Remote Sensing, 47(9): 3272-3282.   DOI
8 Gallo, K., L. Ji, B. Reed, J. Eidenshink, and J. Dwyer, 2005. Multi-platform comparisons of MODIS and AVHRR normalized difference vegetation index data, Remote Sensing of Environment, 99: 221-231.   DOI
9 Kim, S.H., J. Eun, S.J. Kang, and K.S. Lee, 2011. Detection of short-term changes using MODIS daily dynamic cloud-free composite algorithm, Korean Journal of Remote Sensing, 27(3): 259-276 (in Korean with English abstract).   DOI
10 Wang, L., P. Xiao, X. Feng, H. Li, W. Zhang, and J. Lin, 2014. Effective compositing method to produce cloud-free AVHRR image, IEEE Geoscience and Remote Sensing Letters, 11(1): 328-332.   DOI
11 Hahn, C.J., S.G. Warren, and J. London, 1995. The effect of moonlight on observation of cloud cover at night, and application to cloud climatology, Journal of Climate, 8(5): 1429-1446.   DOI