Identifying multiple stressors in regional agro-ecosystems based on sentinel-2 spectral indices time series

The purpose of this study focused on integrating spectral indices with spatio-temporal characteristics to identify multistressor in crops. The experimental areas are located in Dongting Lake (DL), Hunan Province, China. Multitemporal Sentinel-2 (S2) images in 2016, 2017 were collected. Red-edge chlorophyll index (CIred-edge), rededge position (REP), normalized difference red-edge 2 (NDRE2) were calculated. The coefficients of spatiotemporal variation (CSTV) from spectral indices allowed us to discriminate crops exposed to pollution from heavy metal as well as environmental stressors. The results indicated that three indices were good indicators for identifying different environmental stressor in agriculture ecosystem. Crops under heavy metal stress remained stable with lower CSTV values, while crop ‘hot spots’ (with greater CSTV values) were affected by abrupt stressors (i.e., pest and disease, drought) at some growth stage. It concluded that spectral indices and spatio-temporal characteristics show promise for monitoring crops with various stressors.