Phenology-based delineation of irrigated and rain-fed paddy fields with Sentinel-2 imagery in Google Earth Engine
Accompanying files for dela Torre et al. (2021). These include scripts in Javascript for Google Earth Engine and Jupyter Notebooks for data processing.
Paddy rice agriculture is practiced in both rain-fed and irrigated ecosystems in the Philippines. However, small farms are prevalent in the region, and current satellite-based mapping techniques do not distinguish between the two ecosystems at farm scales. This study developed an approach to rapidly map irrigated and rain-fed paddy rice in Iloilo, Philippines at 10 m resolutions using Google Earth Engine. This approach used an ensemble of classifiers based on time-series vegetation indices to produce dry and wet seasonal maps for the entire province. Results showed a predominance of rain-fed rice areas in both seasons, with irrigated rice making up only one-fourth of the total rice area. The overall accuracy was achieved at 68% for the dry season and 75% for the wet season based on ground-acquired points and very high-resolution imagery. The two types of paddies were classified at accuracies up to 87%. Furthermore, the land cover maps showed a strong agreement with the municipal statistics. The resultant maps complement current official statistics and demonstrate the prowess of phenology-based mapping to create paddy inventories in a timely manner to inform food security and agricultural policies.
D. M. G. dela Torre et al., “Phenology-based delineation of irrigated and rain-fed paddy fields with Sentinel-2 imagery in Google Earth Engine,” Geo-spatial Inf. Sci. 24(4), 695–710, Taylor & Francis (2021) doi:10.1080/10095020.2021.1984183.
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