Abstract
Obtaining detailed data on the spatio-temporal variation in crop phenology is critical to increasing our understanding of agro-ecosystem function, such as their response to weather variation and climate change. It is challenging to collect such data over large areas through field observations. The use of satellite remote sensing data has made phenology data collection easier, although the quality and the utility of such data to understand agro-ecosystem function have not been widely studied. Here, we evaluated satellite data-based estimates of rice phenological stages in California, USA by comparing them with survey data and with predictions by a temperature-driven phenology model. We then used the satellite data-based estimates to quantify the crop phenological response to changes in weather. We used time-series of MODIS satellite data and PhenoRice, a rule-based rice phenology detection algorithm, to determine annual planting, heading and harvest dates of paddy rice in California between 2002 and 2017. At the state level, our satellite-based estimates of rice phenology were very similar to the official survey data, particularly for planting and harvest dates (RMSE = 3.8–4.0 days). Satellite based observations were also similar to predictions by the DD10 temperature-driven phenology model. We analyzed how the timing of these phenological stages varied with concurrent temperature and precipitation over this 16-year time period. We found that planting was earlier in warm springs (−1.4 days °C−1 for mean temperature between mid-April and mid-May) and later in wet years (5.3 days 100 mm-1 for total precipitation from March to April). Higher mean temperature during the pre-heading period of the growing season advanced heading by 2.9 days °C−1 and shortened duration from planting to heading by 1.9 days °C−1. The entire growing season was reduced by 3.2 days °C−1 because of the increased temperature during the rice season. Our findings confirm that satellite data can be an effective way to estimate variations in rice phenology and can provide critical information that can be used to improve understanding of agricultural responses to weather variation.
Highlights
Crop phenology, the timing of crop growth stages, is influenced by crop management and environmental conditions, temperature [1,2,3]
Our estimates were very similar to the reported harvested area (USDA) for 2002–2017 (R2 = 0.93; p < 0.001) with an RMSE of 6762 ha, and a relative root mean square error of 3.2% (Figure 2a and Table S2)
While the satellite data do not differentiate between varieties, it does have the ability to capture the difference in crop responses to weather conditions. These findings suggest that remote sensing can be used to detect the crop phenology and may be more useful than weather-driven phenology models to study the variation in crop phenology
Summary
The timing of crop growth stages, is influenced by crop management and environmental conditions, temperature [1,2,3]. The physiological processes related to the effect of weather on crop phenology are well understood from experimental observations and modeling studies [11]. It is less clear how these processes play out in farmers’ fields over larger temporal and spatial scales [12]. Quantifying crop phenological development over space and time is important for understanding how variation in the weather affects crop development on farms
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