Optical microwave cooperative inversion method and system for urban above-ground biomass

Abstract

The invention discloses an optical microwave cooperative inversion method and system for an urban above-ground biomass. The method comprises the steps of obtaining an AGB observation value of a samplebiomass by use of a sample area single-plant parameter data set acquired by a ground surface observation test; performing pretreatment to obtain a canopy height value CHM, surface reflectance data and a backscattering coefficient; extracting various LiDAR variables based on the CHM data, and extracting multiple optical characteristic vegetation indices based on the optical surface reflectance data, and simultaneously extracting multiple microwave characteristic variables based on the microwave backscattering coefficient data; extracting a biomass estimation value of an LiDAR data coverage area; selecting a sample for subsequent modeling and verification by use of a stratified random sampling method with the biomass value of the LiDAR data coverage area as a training and verification sample set; screening out an optimal optical and microwave characteristic variable by use of a variable screening method; and constructing an AGB-inverted optical model, a microwave model and an optical and microwave cooperative model, and selecting an optimal model to realize biomass inversion.

Description

technical field [0001] The invention relates to an inversion method, in particular to an optical and microwave collaborative inversion method and system for urban aboveground biomass. Background technique [0002] The aboveground biomass of vegetation plays an important role in indicating the carbon sequestration capacity and carbon storage of ecosystems. In the International Geosphere-Biosphere Research Program (IGBP), the carbon cycle is identified as an important part of programs such as Global Change and Terrestrial Ecosystems (GCTE). research content. Therefore, accurate extraction of vegetation aboveground biomass is of great significance for global change and terrestrial ecosystem monitoring. [0003] Due to its macro-dynamic, real-time and multi-source characteristics, remote sensing technology has been vigorously developed in the study of vegetation aboveground biomass and other vegetation parameters. A common method is to estimate vegetation parameters by establi...

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Problems solved by technology

However, biomass estimation using SAR backscatter coefficients still faces severe challenges. On the one hand, when the vegetation coverage is relatively low, microwave remote sensing has a significant impact on surface soil moisture and roughness; on the other hand, in dense In vegetation areas, the response of SAR backscatter to vegetation information will also be saturated

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