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http://dx.doi.org/10.7780/kjrs.2022.38.6.1.27

Development of Score-based Vegetation Index Composite Algorithm for Crop Monitoring  

Kim, Sun-Hwa (Underwater Survey Technology 21 Inc.)
Eun, Jeong (PERPIXEL Inc.)
Publication Information
Korean Journal of Remote Sensing / v.38, no.6_1, 2022 , pp. 1343-1356 More about this Journal
Abstract
Clouds or shadows are the most problematic when monitoring crops using optical satellite images. To reduce this effect, a composite algorithm was used to select the maximum Normalized Difference Vegetation Index (NDVI) for a certain period. This Maximum NDVI Composite (MNC) method reduces the influence of clouds, but since only the maximum NDVI value is used for a certain period, it is difficult to show the phenomenon immediately when the NDVI decreases. As a way to maintain the spectral information of crop as much as possible while minimizing the influence of clouds, a Score-Based Composite (SBC) algorithm was proposed, which is a method of selecting the most suitable pixels by defining various environmental factors and assigning scores to them when compositing. In this study, the Sentinel-2A/B Level 2A reflectance image and cloud, shadow, Aerosol Optical Thickness(AOT), obtainging date, sensor zenith angle provided as additional information were used for the SBC algorithm. As a result of applying the SBC algorithm with a 15-day and a monthly period for Dangjin rice fields and Taebaek highland cabbage fields in 2021, the 15-day period composited data showed faster detailed changes in NDVI than the monthly composited results, except for the rainy season affected by clouds. In certain images, a spatially heterogeneous part is seen due to partial date-by-date differences in the composited NDVI image, which is considered to be due to the inaccuracy of the cloud and shadow information used. In the future, we plan to improve the accuracy of input information and perform quantitative comparison with MNC-based composite algorithm.
Keywords
Crop monitoring; Composite; MNC; SBC; Sentinel-2A/B; Paddy; Cabbage;
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Times Cited By KSCI : 2  (Citation Analysis)
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