Mapping rice cropping systems is important for grain yield prediction and food security assessments. Both single- and double-season rice are the dominant rice systems in central China. However, because of increasing labor shortages and high costs, there has been a gradual decline in double-season rice. Ratoon rice (RR) has been proposed as an alternative system that balances the productivity, cost, and labor requirements of rice cultivation. RR has been expanding in central China, encouraged by the improved cultivars, machinery, and favorable policies. However, to our knowledge, the distribution of RR has not been mapped with remote sensing techniques. This study developed a phenology-based algorithm to map RR at a 10 m resolution in Hubei Province, Central China, using dense time stacks of Sentinel-2 images (cloud cover <80%) in 2018. The key in differentiating RR from the other rice cropping systems is through the timing of maturity. We proposed to use two contrast vegetation indices to identify RR fields. The newly-developed yellowness index (YI) calculated with the reflectance of blue, green, and red bands was used to detect the ripening phase, and the enhanced vegetation index (EVI) was used to detect the green-up of the second-season crop to eliminate the misclassification caused by stubbles left in the field. The RR map demonstrated that RR was mainly distributed in the low alluvial plains of central and southern Hubei Province. The total planting area of RR in 2018 was 2225.4 km2, accounting for 10.03% of the total area of paddy rice fields. The overall accuracy of RR, non-RR rice fields, and non-rice land cover types was 0.76. The adjusted overall accuracy for RR and non-RR was 0.91, indicating that the proposed YI and the phenology-based algorithm could accurately identify RR fields from the paddy rice fields.
We describe a single beam compact spin exchange relaxation free (SERF) magnetometer whose configuration is simple and compatible with the silicon-glass bonding micro-machining method. Due to the small size of the vapor cell utilized in a miniature atomic magnetometer, the wall relaxation could not be neglected. In this study we show that Ne buffer gas is more efficient than that of the other typically utilized gas species such as nitrogen and helium for wall relaxation reduction theoretically and experimentally. 3 Amagats (1 Amagat=2.69×1019/cm3) Ne gas is filled in the vapor cell and this is the first demonstration of a Cs-Ne SERF magnetometer. In order to reduce the laser amplitude noise and the large background detection offset, which is reported to be the main noise source of a single beam absorption SERF magnetometer, we developed a laser power differential method and a factor of approximately two improvement of the power noise suppression has been demonstrated. In order to reduce the power consumption of the magnetometer, the Cs based atomic magnetometer is studied. We did an optimization of the magnetometer and a sensitivity of 23fT/Hz1/2@100Hz has been achieved. This is the first demonstration of a single beam Cs based SERF magnetometer.
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