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Land utilization change and carbon reserve quantitative estimation method based on remote sensing data

A technology of remote sensing data and land, applied in the field of remote sensing, can solve problems such as variable collinearity

Active Publication Date: 2021-05-25
平衡机器科技(深圳)有限公司
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Problems solved by technology

[0006] Although the regression model commonly used in domestic research on regional carbon storage is simple to use, collinearity problems are likely to exist between variables

Method used

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  • Land utilization change and carbon reserve quantitative estimation method based on remote sensing data
  • Land utilization change and carbon reserve quantitative estimation method based on remote sensing data
  • Land utilization change and carbon reserve quantitative estimation method based on remote sensing data

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Embodiment Construction

[0025] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0026] Such as figure 1 The shown method for quantitative estimation of land use change and carbon storage based on remote sensing data includes the following steps:

[0027] Step 1. Image download: According to the research needs, download the remote sensing images of the designated research area over the years. Obtain the labeled land classification dataset;

[0028] Step 2. Image preprocessing: perform preprocessing operations such as geometric correction, mosaicking, cropping, radiometric calibration, and atmospheric correction on remote sensing images;

[0029] Geometric correction: the process of using a series of mathematical models to correct and eliminate geometric errors in remote sensing images.

[0030] Radiometric Calibration: Converts the value or voltage recorded by the sensor to absolute radiance.

[0031] Atmosphe...

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Abstract

The invention discloses a land utilization change and carbon reserve quantitative estimation method based on remote sensing data. The method comprises the following steps: downloading an image; preprocessing the image; using and classifying land; calculating ground object carbon density according to ground survey data; making correlation analysis on the carbon reserves in the sample plots and the characteristic values, and selecting the characteristic values with significant correlation for modeling; and normalizing the screened characteristic values as an input layer of the convolutional neural network, putting the calculated carbon density of each sample plot into a network output layer, carrying out network training, and carrying out carbon reserve quantitative estimation on a to-be-studied region by utilizing a trained model. The invention is based on a hierarchical learning architecture of the multi-scale convolutional neural network, so that a land utilization classification result is better. On the basis of different feature values in the image and the carbon density obtained from ground survey data, the nonlinear relation between the feature variables and the carbon reserves is better fitted, and the final quantitative estimation result of the regional carbon reserves is improved.

Description

technical field [0001] The invention relates to the field of remote sensing, in particular to a method for quantitatively estimating land use change and carbon storage based on remote sensing data. Background technique [0002] Land use change is the largest uncertainty factor in estimating carbon storage and release in terrestrial ecosystems. Land use change affects the fixation, accumulation and release of carbon in the soil and vegetation of the ecosystem, and then affects the carbon cycle process of the entire ecosystem, changing the original carbon storage and carbon release mode of the ecosystem. [0003] Accurately predicting the impact of future land use changes on regional carbon storage is of great significance in land use decision-making and urban expansion planning. The existing calculation methods of carbon storage mainly include direct estimation method of remote sensing image, estimation method of vegetation index, spectrometry analysis method, InVEST model, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/04G06N3/08G06V20/13G06F18/241G06F18/214
Inventor 李君吕新杰沈焰姜峥超
Owner 平衡机器科技(深圳)有限公司
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