Method for determining reasonable sample number in forest aboveground biomass remote sensing estimation

A biomass and sample number technology, applied in complex mathematical operations, instruments, character and pattern recognition, etc., can solve problems such as difficulty in determining the number of samples, large manpower and material resources, and modeling accuracy that cannot meet the needs

Inactive Publication Date: 2021-02-19
SOUTHWEST FORESTRY UNIVERSITY
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Problems solved by technology

It can be seen that the larger the sample size, the better the representativeness of the sample, and the higher the accuracy of the modeling, but the more manpower and material resources are consumed, and it is even difficult to complete
On the contrary, if the sample size is too small, its modeling accurac...

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  • Method for determining reasonable sample number in forest aboveground biomass remote sensing estimation
  • Method for determining reasonable sample number in forest aboveground biomass remote sensing estimation
  • Method for determining reasonable sample number in forest aboveground biomass remote sensing estimation

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Embodiment Construction

[0043] The technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Apparently, the described examples are only part of the embodiments of the present invention, not all of them. 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.

[0044] A method for determining a reasonable number of samples in forest aboveground biomass remote sensing estimation, comprising the following steps:

[0045] 1) Overview of the study area

[0046] Shangri-La City in the study area, formerly known as Zhongdian County, is called "Jiantang" in Tibetan. It belongs to the Diqing Tibetan Autonomous Prefecture of Yunnan Province. It is located in the northwest of Yunnan Province and the hinterland of the Hengduan...

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Abstract

The invention discloses a method for determining the number of reasonable samples in forest aboveground biomass remote sensing estimation. The method comprises steps of taking two tree species, i.e.,pinus alpine and fir yunnanensis, as research objects, combining a Landsat 8 image and ground survey sample plot data, taking a k-NN remote sensing estimation model as a case and taking a root-mean-square error as an evaluation index based on a geostatistics semi-variance function theory; and calculating to obtain the number of samples when the precision of the pinus alpine and fir clovershanensismodels is optimal, and determining a reasonable sample number range. In order to discuss uncertainty of the number of samples in quantitative remote sensing inversion, the uncertainty influence of the number of samples in forest aboveground biomass estimation is analyzed based on a geostatistics semi-variation function theory and a k-NN model, and a reference basis is provided for a problem thatthe number of samples in traditional quantitative remote sensing inversion is difficult to determine.

Description

technical field [0001] The invention relates to an uncertainty analysis technique for sample quantity in forest biomass remote sensing estimation, in particular to a method for determining reasonable sample number in forest biomass remote sensing estimation. Background technique [0002] Forest biomass is one of the important indicators to evaluate forest ecosystem productivity, terrestrial ecosystem function and sustainability. With the rapid development of remote sensing technology, the use of multi-source remote sensing data instead of traditional survey methods to quantify aboveground forest biomass can not only obtain information on the quantity, spatial distribution and dynamic changes of forest resources, but also combine various models and plot surveys. Realize the quantitative inversion of forest parameters (He Xingyuan et al., 2018), and save survey costs while meeting the needs of monitoring and analysis of forest resources and ecological processes at different sc...

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Application Information

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IPC IPC(8): G06K9/62G06F17/11
CPCG06F17/11G06F18/24147
Inventor 舒清态谢福明赵耘赖虹燕
Owner SOUTHWEST FORESTRY UNIVERSITY
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