Detection of rice phenology through time series analysis of ground-based spectral index data

Monitoring crop phenology is of great importance for vegetation classification, yield estimation, and irrigation and fertilization management. To test the ability of ground-based remote sensing in detecting major phenological dates of rice, canopy spectra were collected by two portable spectrometers. The Red-edge Chlorophyll Index (CIred edge) and Normalized Difference Vegetation Index (NDVI) time-series derived from ground-based spectrometers were employed to detect the main specific phenological dates. CIred edge was obtained from ASD FieldSpec Pro spectrometer, while NDVI was from ASD FieldSpec Pro spectrometer (referred to as NDVIASD) and GreenSeeker RT 100 (referred to as NDVIGS). The phenology detection method consists of two procedures: (i) smoothing the temporal CIred edge and NDVI data with the double logistic regression function to represent intra-annual vegetation dynamics, (ii) determining the phenological dates through extracting the maximum, minimum and zero-crossing points (FDmax, FDmin and FDzero,) from the first derivative value of the smoothed NDVI and CIred (edge) temporal profiles. A comparison of remote sensing-based estimates with field observations over three growing seasons with different cultivars, planting densities and nitrogen (N) rates showed that CIred (edge) can accurately estimate the dates of jointing, middle booting and dough grain. NDVI from both spectrometers can be used to detect the dates of active tillering, middle heading and maturity. Specifically, NDVIGS yielded better performance than NDVIASD for estimating the three phenological dates. Compared with growing season and planting density, rice cultivar and N rate exhibited more significant impact on the accuracy for phenology detection. This work has great potential to provide valuable support for assessing crop growth status and providing precise management strategy. The dates of active tillering, jointing and maturity detected from a combination of CIred edge and NDVI could be useful for irrigation and fertilization management, and harvest determination, respectively. (C) 2016 Elsevier B.V. All rights reserved.