Forest above-ground biomass remote sensing estimation general model construction method

A general model and biomass technology, applied in the field of forest aboveground biomass estimation, can solve problems that do not involve forest biomass, achieve the effect of improving simulation and prediction accuracy and reducing uncertainty

Pending Publication Date: 2018-11-23
SOUTHWEST FORESTRY UNIVERSITY
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Problems solved by technology

None of the above general models involve the estimation of forest biomass

Method used

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  • Forest above-ground biomass remote sensing estimation general model construction method
  • Forest above-ground biomass remote sensing estimation general model construction method
  • Forest above-ground biomass remote sensing estimation general model construction method

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Embodiment Construction

[0036] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0037] A kind of method that the above-ground biomass remote sensing estimation general model of forest is built, comprises the following steps (as figure 1 shown):

[0038] 1) Overview of the study area

[0039] The study area is Shangri-La City in Northwest Yunnan, China, the hinterland of the Hengduan Mountains and the southeastern edge of the Qinghai-Tibet Plateau. Its geographical range is from 26°52′ to 28°52′ north latitude and from 99°20′ to 100°19 east l...

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Abstract

The invention discloses a forest above-ground biomass remote sensing estimation general model construction method. Remote sensing data is preprocessed first to obtain a normalized data set with the remote sensing data of Landsat from 1987 to 2011 and 6 periods of measured data as data sources; a sample plot remote sensing factor, the biomass value and a change value are calculated; static and dynamic models of the forest above-ground biomass are constructed through multiple regression, linear simultaneous equations, geographical weighted regression and linear models; and the optimal model is determined as the general model of the forest above-ground biomass through verification, and a parameter form of the model is given. The invention fully exploits the relationship between the change ofthe remote sensing factor and the forest biomass change, therefore, the uncertainty caused by the estimation of single-period remote sensing data is reduced; the forest above-ground biomass model is constructed through a linear mixed model, therefore, the simulation and prediction accuracy is greatly improved; and the constructed general model can be used for real-time and on-site estimates of theforest biomass.

Description

technical field [0001] The invention relates to the field of forest aboveground biomass estimation, in particular to a method for constructing a general model for forest aboveground biomass estimation based on time series remote sensing data. Background technique [0002] In forest biomass measurement, traditional measurement methods and remote sensing monitoring methods are included. The ever-growing remote sensing technology has the advantages of being fast, accurate, non-destructive to forests, and capable of long-term, dynamic, and continuous macroscopic monitoring, making remote sensing monitoring methods the main way to obtain forest aboveground biomass. Because the parametric model established by the existing remote sensing estimation means relies on field survey data, the fitting and prediction accuracy is low, and the calculation is more complicated. Although the non-parametric model has high accuracy, the model is poor in portability, which leads to difficulties in...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T17/05G06F17/18
CPCG06F17/18G06T17/05
Inventor 张加龙胥辉
Owner SOUTHWEST FORESTRY UNIVERSITY
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