Extraction of Irrigation Signals by Using SMAP Soil Moisture Data

نویسندگان

چکیده

To allow extraction of irrigation signals from satellite-derived data on soil moisture, this study describes the development an signal method that takes into account multiple environmental factors in irrigation. Firstly, fuzzy membership functions relating to are constructed. Then, a model is built based by using operation rules sets, which used infer relevant degree nonirrigation. Finally, satellite-based moisture recognized according degree. Taking Henan Province North China Plain as area, proposed extract SMAP Level 3 Passive Soil Moisture Product. Extracted two grids validated daily situ and precipitation data, with results showing correct identification most signals. By grading extracted signals, frequency maps for 2016–2017 winter crop growth season 2017 summer obtained Province. Compared annual potential evapotranspiration, show spatial pattern opposite similar evapotranspiration. It common sense areas low high evapotranspiration need more water. Thus, patterns reasonable sense. However, it should be noted observed qualitative assessments rendered less convincing product’s coarse resolution. Quantitative validation remains significant challenge, small-scale cannot captured coarse-resolution products. high-resolution product future.

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ژورنال

عنوان ژورنال: Remote Sensing

سال: 2021

ISSN: ['2315-4632', '2315-4675']

DOI: https://doi.org/10.3390/rs13112142