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It is difficult to accurately identify and extract bodies of water and underwater vegetation from satellite images using conventional vegetation indices, as the strong absorption of water weakens the spectral feature of high near-infrared (NIR) reflected by underwater vegetation in shallow lakes. This study used the shallow Lake Ulansuhai in the semi-arid region of China as a research site, and proposes a new concave-convex decision function to detect submerged aquatic vegetation (SAV) and identify bodies of water using Gao Fen 1 (GF-1) multi-spectral satellite images with a resolution of 16 meters acquired in July and August 2015. At the same time, emergent vegetation, "Huangtai algae bloom", and SAV were classified simultaneously by a decision tree method. Through investigation and verification by field samples, classification accuracy in July and August was 92.17% and 91.79%, respectively, demonstrating that GF-1 data with four-day short revisit period and high spatial resolution can meet the standards of accuracy required by aquatic vegetation extraction. The results indicated that the concave-convex decision function is superior to traditional classification methods in distinguishing water and SAV, thus significantly improving SAV classification accuracy. The concave-convex decision function can be applied to waters with SAV coverage greater than 40% above 0.3 m and SAV coverage 40% above 0.1 m under 1.5 m transparency, which can provide new methods for the accurate extraction of SAV in other regions.

We present a technique for the coherence transfer of laser light through a fiber link, where the optical phase noise induced by environmental perturbation via the fiber link is compensated by remote users. When compensating the fiber noise by remote users, the time base at the remote site independent from that at the local site does not destroy the performance of the fiber output light. Using this technique, we demonstrate the transfer of subhertz-linewidth laser light through a 25-km-long, lab-based spooled fiber. After being compensated, the relative linewidth between the fiber input and output light is 1 mHz, and the relative frequency instability is 4×10^-17 at 1 s averaging time and scales down to 2×10^-19 at 800 s averaging time. The frequency uncertainty of the light after transferring through the fiber relative to that of the input light is 3.0×10^-19. This system is suitable for the simultaneous transfer of an optical signal to a number of end users within a city.

Narrow-linewidth ultrastable lasers at 1.5 μm are essential in many applications such as coherent transfer of light through fiber and precision spectroscopy. Those applications all rely on the ultimate performance of the lasers. Here we demonstrate two ultrastable lasers at 1557 nm with a most probable linewidth of 0.26 Hz by independently frequency-stabilizing to the resonance of 10-cm-long ultrastable Fabry-Pérot cavities at room temperature. The fractional frequency instability of each laser system is nearly 8 × 10−16 at 1–30 s averaging time, approaching the thermal noise limit of the reference cavities. A remarkable frequency instability of 1 × 10−15 is achieved on the long time scale of 100–4000 s.

Multi-term time fractional diffusion model is not only an important physical subject, but also a practical problem commonly involved in engineering. In this paper, we apply the alternating segment technique to combine the classical explicit and implicit schemes, and propose a parallel nature difference method alternating segment pure explicit-implicit (PASE-I) and alternating segment pure implicit-explicit (PASI-E) difference schemes for multi-term time fractional order diffusion equations. The existence and uniqueness of the solutions are proved, and stability and convergence analysis of the two schemes are also given. Theoretical analyses and numerical experiments show that the PASE-I and PASI-E schemes are unconditionally stable and satisfy second-order accuracy in spatial precision and 2 − α order in time precision. When the computational accuracy is equivalent, the CPU time of the two schemes are reduced by up to 2/3 compared with the classical implicit difference method. It indicates that the PASE-I and PASI-E parallel difference methods are efficient and feasible for solving multi-term time fractional diffusion equations.