Novel Vegetation Indices for Cotton Boll Opening Status Estimation Using Sentinel-2 Data

Remote Sensing

Yanhua Meng¹  Yuxing Han²  Wenjiang Huang³  Bei Cui³  Yu Ren³  Naichen Xing³  Huichun Ye³  Anting Guo³  Yun Geng³  Weiping Kong⁴  Xianfeng Zhou⁵ 

[1] Anyang Institute of Technology, Anyang 455000, China;Department of Electrical Engineering, South China Agricultural University, Guangzhou 510642, China;Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China;Key Laboratory of Quantitative Remote Sensing Information Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China;School of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou 310018, China;

关键词: boll opening rate (BOR);    Sentinel-2;    vegetation index;    cotton;    harvest aids;   

DOI  :  10.3390/rs12111712

来源: DOAJ

【 摘 要 】

The application of chemical harvest aids to defoliate leaves and ripen bolls plays a significant role in the once-over machine harvest of cotton (Gossypium hirsutum L.) fields. The boll opening rate (BOR) is a key indicator for the determination of harvest aid spraying times. However, the most commonly used method to determine BOR is manual investigation, which is subjective and cannot have a holistic judgment of the entire area. Remote sensing can be employed to overcome these limitations, due to a wide field of vision, acceptably spatial and temporal resolution, and rich spectral information beyond the perception of the human eye. The reflectance of open cotton bolls is relatively high in the visible and near-infrared bands. High reflectance of open bolls has a great influence on the reflectance of the mixed pixels on remote sensing imagery. Therefore, it is an effective method to detect boll opening status by constructing vegetation indices with the sensitive spectral bands of imagery. In this study, we proposed two new vegetation indices based on Sentinel-2 remote sensing data, namely, the boll area ratio index (BARI) and the boll opening rate index (BORI), in order to estimate the boll opening status on a regional scale. The proposed indices were strongly correlated with the boll area ratio (BAR) and BOR. In particular, BARI exhibited the most accurate and robust performance with BAR in the prediction (R² = 0.754, RMSE = 2.56%) and validation (R² = 0.706, RMSE = 5.00%) among all the indices, including published indices we chose. Furthermore, when comparing to all other indices, BORI demonstrated the best and satisfactory estimation with BOR in the prediction (R² = 0.675, RMSE = 7.96%) and validation (R² = 0.616, RMSE = 2.79%). Meanwhile, an exponential growth relationship between BOR and BAR was identified, and the underlying mechanisms behind this phenomenon were discussed. Overall, through our study, we provided convenient and accurate vegetation indices for the investigation of boll opening status in a cotton-producing area by accessible and free Sentinel-2 imagery.

【 授权许可】

Unknown