Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5755012 | Remote Sensing of Environment | 2017 | 19 Pages |
Abstract
Regional product accuracy assessments showed that PhenoRice made a conservative, spatially representative and robust detection of rice cultivation in all sites (r2 between 0.75 and 0.92) and crop establishment dates were in close agreement with the reference data (r2 = 0.98, Mean Error = 4.07 days, Mean Absolute Error = 9.95 days, p < 0.01). Variability in algorithm performance in different conditions in each site (irrigated vs rainfed, direct seeding vs transplanting, fragmented vs clustered rice landscapes and the impact of cloud contamination) was analysed and discussed. Analysis of the maps revealed that cropping intensity and season length per site matched well with local information on agro-practices and cultivated varieties. The results show that PhenoRice is robust for deriving essential temporal descriptions of rice systems in both temperate and tropical regions at a level of spatial and temporal detail that is suitable for regional crop monitoring on a seasonal basis.
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Computers in Earth Sciences
Authors
Mirco Boschetti, Lorenzo Busetto, Giacinto Manfron, Alice Laborte, Sonia Asilo, Sellaperumal Pazhanivelan, Andrew Nelson,