Large-scale forest height remote sensing inversion method considering ecological partition

A technology of ecological zoning and remote sensing inversion, applied in the field of forestry remote sensing, can solve the problems of poor regional representation and low accuracy

Active Publication Date: 2022-02-11
WUHAN UNIV
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Problems solved by technology

[0004] Aiming at the problems of low accuracy and poor regional representation of current large-scale forest height estimation algorithms, the present invention provides a large-scale forest height remote sensing inversion method that takes into account ecological divisions

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  • Large-scale forest height remote sensing inversion method considering ecological partition
  • Large-scale forest height remote sensing inversion method considering ecological partition
  • Large-scale forest height remote sensing inversion method considering ecological partition

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Embodiment Construction

[0026] The present invention provides a high-scale forest height remote sensing inversion method takes into account the ecological partition, and the random forest model of the Landsat8 video data, Google Earth Engine structure in the eastern part of 2019, in conjunction with the drawings and examples of the technical solution Further explanation.

[0027] like figure 1 As shown, the flow of the embodiments of the present invention includes the following steps:

[0028] Step 1. Get the ICESAT-2 Trek Data, Landsat Data, SRTM Data, WORLDCLIM Data, Forest Type Data, and Ecological Partition Data within the target area, and pre-processes the data, including the following steps:

[0029] Step 1.1, use Google Earth Engine to collect Landsat data, SRTM data, WORLDCLIM data, and forest type data in China eastern region.

[0030] Step 1.2, use the cloud masking method CFMask to remove the clouds, cloud shadow pixels in the Landsat8 image, get high quality Landsat data.

[0031] Step 1.3, t...

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Abstract

The invention relates to a large-scale forest height remote sensing inversion method considering ecological partition. The method comprises the following steps: firstly, combining forest ecological partition data with a spaceborne photon counting laser radar, an optical image, topographic data, meteorological data and latitude and longitude data, then creating a multi-source remote sensing data nonparametric tree height model considering different ecological partitions and different forest types, and estimating the continuous forest height of the whole research area space by using the model. Ecological factors related to forest growth are comprehensively considered, the remote sensing-ecological coupling forest height estimation model is obtained by incorporating ecological partition factors into forest height modeling, and help can be provided for generating forest height space information from global and regional scales to more local scales.

Description

Technical field [0001] The present invention belongs to the field of forestry remote sensing, and therefore specifically involves a large-scale forest height remote sensing inversion method takes into account the ecological partition. Background technique [0002] In the field of forestry, the height is one of the most important measuring tree factors. Traditional tree high acquisition generally passed the test, using the triangular function principle to measure the single trees in the forest land, which mainly rely on manually obtaining trees highly information, for the national scale tree high estimation is hard, cumbersome, long ,Inefficient. Satellite remote sensing technology is repeatedly observed, achieving large area, high-efficiency forest height monitoring, but optical satellite remote sensing images can only characterize information in the forest level, and there is no ability to detect forest vertical structures. Satellite laser radar systems utilize laser ranging tec...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V20/13G06V10/764G06V10/774G06K9/62
CPCG06F18/24323G06F18/214Y02A90/10G06V20/194G06V20/188G06V20/13G06V10/58G06V10/774G06V10/764G01C11/04
Inventor 巫兆聪时芳琳
Owner WUHAN UNIV
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