Hyperspectral remote sensing method for estimating species richness of vascular plants

Abstract

The invention discloses a hyperspectral remote sensing method for estimating the species richness of a vascular plant, and the method comprises the steps: obtaining remote sensing data, carrying out the radiation correction, geometric correction and terrain correction, and extracting spectral data; correcting and checking the obtained spectral data to ensure that no data error exists; smoothing the obtained spectral data, and obtaining the mean value of intermediate data on the basis of four adjacent data; calculating a first-order spectral derivative; calculating the first-order derivative ratio of each waveband; and calculating a species diversity index estimated value. According to the method, the diversity of the plant species can be rapidly estimated, and the method can be widely applied to rapid evaluation of the abundance of the vascular plant species in grassland, grassland, shrubs, farmlands, nursery lands and the like; different from a large amount of manpower and material resources consumed by on-site quadrat investigation or a large amount of expenditure for purchasing remote sensing images, the diversity index of the plant species can be rapidly determined, a large amount of manpower and material resource investment is not needed, and the method has the advantages of efficient information processing and investment cost saving.

Description

technical field [0001] The invention relates to a method for estimating the species richness of vascular plant communities, in particular to a method for estimating the species richness of vascular plant communities based on hyperspectral remote sensing data. Background technique [0002] Remote sensing technology has been widely used in ecological environment monitoring, crop pests and diseases, crop yield estimation, geological and mineral exploration, etc., and is playing an increasingly important role. The spectral characteristics of plants are the changes in light absorption, transmission and reflection caused by physiological and ecological characteristics and compositional structure characteristics. Remote sensing data can be used to quantitatively invert vegetation physiological and biochemical parameters, mainly involving vegetation coverage, biomass, and leaf area. index, as well as leaf or canopy water content, chlorophyll content, mineral nutrient content, cellul...

AI Technical Summary

Problems solved by technology

However, there is no effective remote sensing monitoring method for the monitoring of plant species richness. Therefore, it is urgent to develop a method for rapid assessment of plant species richness suitable for grassland, grassland, farmland and other objects.

Images