Location: Aerial Application Technology ResearchTitle: Comparisons between temporal statistical metrics, time series stacks and phenological features derived from NASA Harmonized Landsat Sentinel-2 data for crop type mapping
|LIU, XIAOMI - Shandong University
|XIE, SHUAI - Shandong University
|YANG, JIANGNING - Chinese Academy Of Sciences
|SUN, LIN - Shandong University
|LIU, LIANGYUN - Chinese Academy Of Sciences
|ZHANG, QING - Chinese Academy Of Sciences
Submitted to: Computers and Electronics in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/21/2023
Publication Date: 6/30/2023
Citation: Liu, X., Xie, S., Yang, J., Sun, L., Liu, L., Zhang, Q., Yang, C. 2023. Comparisons between temporal statistical metrics, time series stacks and phenological features derived from NASA Harmonized Landsat Sentinel-2 data for crop type mapping. Computers and Electronics in Agriculture. https://doi.org/10.1016/j.compag.2023.108015.
Interpretive Summary: Spectrotemporal features derived from satellite imagery are useful for characterizing land cover of highly dynamic crops. This research investigated three spectrotemporal features (temporal statistical metrics, time series image stacks, and phenological features) for mapping crop types using combined Landsat-8 and Sentinel-2 satellite data. The results from the study showed that time series image stacks performed better than the other two features in terms of accuracy and other measures. An analysis of the effects of different temporal factors on time series stacks further indicated that the best classification results were achieved when using Landsat-8 and Sentinel-2 data composited monthly for the growing season. The findings from this study provide valuable insights for spectrotemporal feature selection and optimization for accurate crop type mapping.