Forest aboveground biomass estimation method and system based on remote sensing image

By using Sentinel-2 data and DEM data, a forest AGB estimation model including trees under threshold is constructed, which solves the problem of difficulty in accurately estimating tree biomass in the prior art, and improves the accuracy and scientificity of the estimation.

CN119851156APending Publication Date: 2025-04-18CHONGQING FORESTRY PLANNING & DESIGN INST
View PDF 0 Cites 2 Cited by

Patent Information

Application Number
CN202411956907.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-29
Publication Date
2025-04-18

AI Technical Summary

Technical Problem

The prior art is difficult to accurately consider the contribution of trees with breast diameters smaller than the preset threshold in forest land biomass estimation, resulting in uncertainty in the estimation results.

Method used

By obtaining Sentinel-2 data and DEM data, after preprocessing, input the trained forest AGB estimation model to calculate the sample AGB of trees under the threshold, thereby building a more accurate forest AGB estimation model.

Benefits of technology

It improves the accuracy of forest land biomass estimation, takes into account the biomass contribution of all trees in forest ecosystems more comprehensively, and reduces estimation uncertainty.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN119851156A_ABST
    Figure CN119851156A_ABST
Patent Text Reader

Abstract

The invention discloses a forest above-ground biomass estimation method based on a remote sensing image. The method comprises the following steps: acquiring Sentinel-2 data and DEM data of a target area through a satellite; the Sentinel-2 data and the DEM data of the target area are input into the trained forest AGB estimation model, so that the forest AGB of the target area is estimated, and training of the forest AGB estimation model comprises the steps of setting a plurality of sample plots in the target area; obtaining Sentinel-2 data and DEM data of each sample plot, and extracting a reflectivity index, a vegetation index, biophysical characteristics and a terrain index; determining AGB of each sample plot; and training the forest AGB estimation model by using the training feature corresponding to each sample plot and the AGB of the sample plot. According to the method, the accuracy of forest AGB estimation is improved.
Need to check novelty before this filing date? Find Prior Art

Citation Information

Cited By

  • Forest cooling effect prediction method and device based on forest age and forest attributes, equipment and medium

    CN122310465A

  • Forest aboveground biomass estimation method and device and electronic equipment

    CN122615441A