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- W2758788511 abstract "Remote sensing imagery derived from different sensors has different crop identification capability. due to the different spatial and temporal resolution, availability of certain spectral bands. Landsat OLI and RapidEye provide an important part of data sources for agricultural monitoring with a relative long historic records. As the availability of the data from these two sensors is totally different, an analysis of the crop identification capability using these sensors could provide the stakeholders data source selection for the operational perspectives. This paper took Bei'an city, Heilongjiang province as the study area, where major planted crops are maize and soybean. The authors used maximum likelihood classification methods to try tried to identify best registration phase, best spectral band combination for crop type identification in the study region. Especially, the authors evidenced the identification improvement contributed by the unique short infrared wave band from LANDSAT OLI and red edge band from RapidEye." @default.
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- W2758788511 date "2017-08-01" @default.
- W2758788511 modified "2023-09-23" @default.
- W2758788511 title "Comparative study on crop recognition of LandSat-OLI and RapidEye data" @default.
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- W2758788511 doi "https://doi.org/10.1109/agro-geoinformatics.2017.8047024" @default.
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