Abstract: A method of optical and microwave synergistic retrieval of aboveground biomass, the method including: 1) obtaining an observation value of aboveground biomass (AGB) of a sample plot; 2) pre-processing laser radar (LiDAR) data, optical remote sensing data and microwave remote sensing data covering a research region, to yield crown height model (CHM) data, surface reflectance data and a backscattering coefficient, respectively; 3) extracting different LiDAR variables, extracting a plurality of optical characteristic vegetation indexes, and extracting a plurality of microwave characteristic variables; 4) establishing a multiple stepwise linear regression model of the biomass; 5) taking the biomass value of the LiDAR data coverage region as a training set and a verification sample set, and selecting samples for modeling and verification; 6) screening out the optical and microwave characteristic variables; and 7) constructing an optical model, a microwave model, and an optical and microwave synergistic model of AG

Abstract: A method of optical and microwave synergistic retrieval of aboveground biomass, the method including: 1) obtaining an observation value of aboveground biomass (AGB) of a sample plot; 2) pre-processing laser radar (LiDAR) data, optical remote sensing data and microwave remote sensing data covering a research region, to yield crown height model (CHM) data, surface reflectance data and a backscattering coefficient, respectively; 3) extracting different LiDAR variables, extracting a plurality of optical characteristic vegetation indexes, and extracting a plurality of microwave characteristic variables; 4) establishing a multiple stepwise linear regression model of the biomass; 5) taking the biomass value of the LiDAR data coverage region as a training set and a verification sample set, and selecting samples for modeling and verification; 6) screening out the optical and microwave characteristic variables; and 7) constructing an optical model, a microwave model, and an optical and microwave synergistic model of AG

Abstract: The present invention discloses a method for preparing lithium-rich manganese-based cathode material. The method comprises: dispersing ?-MnO2 micron particles, a nickel salt and a lithium-containing compound in a solvent to obtain a mixture, then evaporating the mixture to remove the solvent, and calcining the solid product obtained from the evaporation; wherein the lithium-containing compound is a lithium salt and/or lithium hydroxide. The present invention also provides a lithium-rich manganese-based cathode material prepared by the above method. The present invention also provides a lithium-ion battery of which anode material contains the foregoing lithium-rich manganese-based anode material. The lithium-rich manganese-based cathode material provided by the present invention has high rate capability and prolonged cycle stability.

Abstract: The present invention discloses a method for preparing lithium-rich manganese-based cathode material. The method comprises: dispersing ?-MnO2 micron particles, a nickel salt and a lithium-containing compound in a solvent to obtain a mixture, then evaporating the mixture to remove the solvent, and calcining the solid product obtained from the evaporation; wherein the lithium-containing compound is a lithium salt and/or lithium hydroxide. The present invention also provides a lithium-rich manganese-based cathode material prepared by the above method. The present invention also provides a lithium-ion battery of which anode material contains the foregoing lithium-rich manganese-based anode material. The lithium-rich manganese-based cathode material provided by the present invention has high rate capability and prolonged cycle stability.