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Strip LiDAR data upscaling-based forest biomass estimating method

A technology for forest biomass and biomass, applied in computing, computer parts, instruments, etc., can solve problems such as single independent variable of upscaling model and low mapping resolution.

Inactive Publication Date: 2016-08-31
NANJING FORESTRY UNIV
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AI Technical Summary

Problems solved by technology

The above studies have proved the feasibility and effectiveness of discontinuous LiDAR data for forest parameter upscaling inversion and continuous distribution mapping, but the independent variable of the upscaling model is relatively single (for example, MERIS data only provides NDVI as the inversion parameter) Lower resolution (300m)
At the same time, none of the above studies and applications have been implemented in the northern subtropical region.

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  • Strip LiDAR data upscaling-based forest biomass estimating method
  • Strip LiDAR data upscaling-based forest biomass estimating method
  • Strip LiDAR data upscaling-based forest biomass estimating method

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Embodiment 1

[0031] A method for estimating forest biomass through strip LiDAR data upscaling, comprising the following steps:

[0032] 1) Overview of the test area

[0033] The research area is located in the state-run Yushan Forest Farm in Changshu City, Jiangsu Province (120°42′9.4″E, 31°40′4.1″N), which has a subtropical monsoon climate with a mild climate, an average annual precipitation of 1054 mm, and an area of ​​about 1103hm 2 , and its altitude is 20-261m. Yushan Forest Farm belongs to the northern subtropical secondary mixed forest. The main forest types are coniferous forest, broad-leaved forest and mixed forest. The main coniferous tree species are Pinus massoniana, Cunninghamia lanceolata and Pinuselliottii, etc. The main broad-leaved tree species are Quercus acutissima, Liquidambarformosana and some evergreen broad-leaved tree species, such as Fagaceae, Lauraceae and Theaceae. The test area and sample plot distribution are as follows: figure 1 .

[0034] 2) Remote sensin...

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Abstract

The invention discloses a strip LiDAR data upscaling-based forest biomass estimating method. A method implementation object is a subtropical natural secondary forest at a hilly area of southern Jiangsu Province; 9 characteristic variables are extracted from LiDAR strip data and are combined with ground estimated biomass to invert biomass continuous distribution information in a strip, sampling operation is conducted in a strip inverting result zone, samples are combined with Landsat OLI image characteristic variables covering a whole research zone, and biomass of the whole research zone can be estimated in an upscaling manner. Based on full acquisition of remote sensing data characteristic information, forest farm level biomass estimation cost is lowered via strip LiDAR data, and biomass estimating precision of a remote sensing method on the scale is improved.

Description

technical field [0001] The invention belongs to the technical fields of forestry investigation, dynamic monitoring and biological diversity, and relates to a method for estimating forest biomass by upscaling strip LiDAR data. Background technique [0002] The forest ecosystem is the main body of the terrestrial biosphere, and its biomass accounts for about 85% of the entire terrestrial ecosystem. It plays an irreplaceable role in mitigating global climate change. Forests assimilate atmospheric CO as they grow 2 , and fix it in the form of biomass for a long time. Subtropical trees are rich in tree species and have high forest productivity, which not only has a great impact on the regional ecological environment, but also plays an important role in maintaining global carbon balance. Traditional biomass survey methods are time-consuming and laborious, and can only obtain limited "point" information. However, remote sensing technology can accurately and quickly obtain contin...

Claims

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V20/194G06V20/188
Inventor 曹林申鑫佘光辉
Owner NANJING FORESTRY UNIV
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