Corresponding period double high resolution remote sensing image-based forest biomass estimation method

A technology of forest biomass and remote sensing images, applied in the field of forest biomass estimation based on simultaneous dual high-resolution remote sensing images

Inactive Publication Date: 2016-08-31
NANJING FORESTRY UNIV
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Problems solved by technology

These studies were based on dual high-resolution data that were not acquired simultaneously and were not implemented in subtropical regions

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  • Corresponding period double high resolution remote sensing image-based forest biomass estimation method
  • Corresponding period double high resolution remote sensing image-based forest biomass estimation method
  • Corresponding period double high resolution remote sensing image-based forest biomass estimation method

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Embodiment 1

[0033] A forest biomass estimation method based on simultaneous dual high-resolution remote sensing images, comprising the following steps:

[0034] 1) Overview of the study area

[0035] The research area is selected from the state-run Yushan Forest Farm in Jiangsu Province (120°42′9.4″E, 31°40′4.1″N), with a total area of ​​1422hm 2, the range of elevation change is 20~260m. The study area is located in a typical northern subtropical monsoon climate zone, with an annual precipitation of 1062.5mm, of which June (171.3mm) and July (147.0mm) have the largest precipitation, accounting for 30% of the annual precipitation. The main soil type is yellow brown soil, which is acidic and has a pH value of 5-6. The main forest type of Yushan Forest Farm is subtropical secondary mixed forest, which can be subdivided into three forest types: coniferous, broad-leaved and mixed. The main coniferous tree species are Pinus massoniana, Chinese fir (Cunninghamia lanceolata) and slash pine (P...

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Abstract

The invention discloses a corresponding period double high resolution remote sensing image-based forest biomass estimation method which comprises the following steps: the method is applied to a subtropical zone natural secondary forest in a hilly area in southern Jiangsu Province; based on double high resolution remote sensing image data obtained in a corresponding period, single tree crown breadth is extracted via an object-oriented segmentation method, five groups of hyperspectrum characteristic variables and seven single tree crown breadth structure statistical variables are extracted, biomass estimation is conducted via multiple regression model construction, and model precision is evaluated via a cross validation method. According to the method, when model parameters are determined, one of all sample areas is chosen randomly as a validation sample area, and the rest of the sample areas are used for modeling, a model obtained via fitting operation can be used for validating the sample area which is randomly chosen, the above steps are repeated in cycles till all sample areas are validated, and therefore forest biomass estimation accuracy can be improved while corresponding period double high resolution remote sensing image characteristics are fully discovered.

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 based on simultaneous dual high-resolution remote sensing images. Background technique [0002] As the main body of terrestrial ecosystems, forests play a huge role in maintaining regional ecological environment and global carbon balance. Forest biomass is an important indicator for measuring forest structure and function, and provides key data for ecosystem carbon sink and carbon cycle research. Accurate estimation of forest biomass is of great significance to the study of global carbon sink, carbon balance and understanding of global climate change. Biomass information at various scales can also be used for forestry surveys, dynamic monitoring, and biodiversity, and to parameterize forest growth models, forest fire prediction models, and optimize forest resource management. The t...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06V20/194G06V20/188
Inventor 曹林申鑫佘光辉
Owner NANJING FORESTRY UNIV
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