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Stable regression method for remote sensing individual tree canopy and forest diameter

A robust regression and regression method technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as inexhaustible outliers, normal points, and observation data cannot be deleted

Inactive Publication Date: 2015-05-13
RES INST OF FOREST RESOURCE INFORMATION TECHN CHINESE ACADEMY OF FORESTRY
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  • Application Information

AI Technical Summary

Problems solved by technology

There are two situations. One situation is to use 2-3 times the standard deviation to eliminate outliers. It may not be possible to eliminate outliers, but normal points may also be eliminated. The other situation is that the observation data is very important and cannot be deleted. "For example, there is an "outlier point" in the 21 (daily) observation data of the frost heaving force of the anchor ingot of the Runyang Bridge. Since it is not a human factor, it cannot be deleted. Therefore, the M-estimation method proposed by Huber is used. That is, the Robust Estimatours method, that is, the robust regression method that does not remove outliers

Method used

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  • Stable regression method for remote sensing individual tree canopy and forest diameter
  • Stable regression method for remote sensing individual tree canopy and forest diameter
  • Stable regression method for remote sensing individual tree canopy and forest diameter

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Experimental program
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Effect test

Embodiment 1

[0052] Embodiment 1: as figure 1 , figure 2 , image 3 As shown, a robust remote sensing individual tree crown width and tree diameter regression method is generally divided into the following steps: the first step is the acquisition of data related to single tree crown width and tree diameter; the second step is the construction of a robust regression model; the third step The iterative determination of the parameters of the robust regression model of single tree crown width and tree diameter;

[0053] Specifically, it contains the following steps:

[0054] Step 1) The following methods are used to obtain the data related to the crown width of a single tree and the tree diameter:

[0055] Method A), remote sensing image crown extraction method:

[0056] In the wild, select a medium-sized forest land with medium canopy as the test site, use differential GPS to determine the geographical coordinates of the "related trees" in the forest, and then measure the diameter of the...

Embodiment 2

[0113] Embodiment 2: as figure 1 , figure 2 , image 3 As shown, a robust remote sensing single tree crown width and tree diameter regression method also includes the following steps:

[0114] Step 1), crown data acquisition;

[0115] Since there is a mapping relationship between the crown of a single tree and the crown of forest trees on the remote sensing image, but it is not necessarily possible to achieve a one-to-one mapping relationship, so the corresponding trees (related trees) can only be obtained from the ground forest plot. According to the definition of single tree canopy in remote sensing images, this kind of related tree can only be selected in the forest land.

[0116] In the field, use differential GPS to determine the position of trees in the forest and measure the corresponding tree diameters, etc., compile the geographic coordinates measured by GPS into a file, which can be loaded into the Arcgis system at one time, and superimposed with high-resolution ...

Embodiment 3

[0119] Embodiment 3: as figure 1 , figure 2 , image 3 As shown, a robust remote sensing single tree crown width and tree diameter regression method also includes the following steps:

[0120] Step 1) acquisition of data related to crown width and tree diameter;

[0121] Since there is a mapping relationship between the crown of a single tree and the crown of the ground forest on the remote sensing image, but it may not be possible to achieve a one-to-one mapping relationship, so the corresponding trees can only be selected from the ground forest plot.

[0122] By visual identification:

[0123] Find an obvious object mark at the edge of the forest land, draw a lead line into the plot in the forest, first identify the corner points of the plot, and then find the plot from the remote sensing image, and outline the "related trees" in the plot through the visual recognition method of the remote sensing image The tree crown profile of the tree, measure the crown width, and re...

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Abstract

The invention provides a stable regression method for a remote sensing individual tree canopy and a forest diameter, and belongs to the technical field of the computer program and measurement. The method comprises the following steps: obtaining relevant data of the canopy and the forest diameter; establishing a stable regression model; carrying out an iterative determination on a stable regression model parameter of the individual tree canopy and the forest diameter. In a typical north east mid-temperature zone coniferous and broad-leaved mixed forest, based on extracting an individual tree canopy image of the high spatial resolution, by utilizing the Huber, an M- estimation method is proposed for solving the 'defect' that the traditional least square method is over sensitive for the data of the 'abnormal point', and the stable regression model of a remote sensing image individual tree canopy and the forest diameter is successfully established. The weighting factor distribution of an objective function is introduced through the M- estimation method, so that the 'defect' of the equivalent weighting of various samples (including the abnormal point) in the traditional least square method is changed. A menu program module of the stable regression model has the independence, the completeness, and the good portability.

Description

technical field [0001] The invention relates to a robust remote sensing single tree crown width and tree diameter regression method, which belongs to the technical field of computer programs and measurement. Background technique [0002] Obtaining the crown width of a single tree through remote sensing images reduces the workload of forest investigation, and the purpose of estimating the diameter of a tree can be achieved by the regression model of the crown width of a single tree and the diameter of a tree. [0003] Because tree crowns are greatly affected by various random factors, there are many outliers in the linear relationship between the crown width of a single tree measured by remote sensing and the tree diameter measured in the field. Especially the effect of stand density is not easy to control. The commonly used least squares method is more sensitive to outliers, because the least squares method uses the minimum value of the sum of squared residuals to "optimize...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 黄建文郎璞玫郎奎健鞠洪波
Owner RES INST OF FOREST RESOURCE INFORMATION TECHN CHINESE ACADEMY OF FORESTRY
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