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Alpine meadow ecosystem respiratory carbon emission estimation method based on remote sensing

An ecosystem and carbon emission technology, applied in the field of quantitative remote sensing, can solve the problems of high construction and maintenance costs of flux stations

Pending Publication Date: 2019-09-20
SOUTHWEST UNIVERSITY
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Problems solved by technology

[0003] The purpose of this invention is to solve the problem that the current flux station construction and maintenance costs are high and it is difficult to apply it on a global scale, and use remote sensing data to realize the inversion of respiratory carbon emissions of large-scale ecosystems

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  • Alpine meadow ecosystem respiratory carbon emission estimation method based on remote sensing
  • Alpine meadow ecosystem respiratory carbon emission estimation method based on remote sensing
  • Alpine meadow ecosystem respiratory carbon emission estimation method based on remote sensing

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Embodiment Construction

[0022] The Arou Super Station is located in the upper reaches of the Heihe River Basin in Northwest my country. It has been established since the end of 2012. It runs from east to west and is 3km wide from north to south. The terrain around Arou Station is relatively flat, descending slowly from southeast to northwest. The surface is covered with alpine meadows. The annual average temperature and total annual precipitation are about 0.9°C and 403.1mm respectively. The technical solution of the present invention will be further elaborated below by taking the Arou station located on the alpine meadow as the underlying surface as an example:

[0023] Step 1 Acquisition and processing of ground flux tower site data

[0024] 1) Query and download the Arou flux site data. The flux tower site data required by this method include the eddy observation data and the micro-meteorological data of the automatic weather station. The original eddy data is 10Hz, mainly obtained from the Arou s...

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Abstract

The invention discloses an alpine meadow ecosystem respiratory carbon emission estimation method based on remote sensing. The alpine meadow ecosystem respiratory carbon emission estimation method comprises the following steps: 1) acquiring and processing flux data of observation stations of a field vortex motion related system; 2) downloading the time sequence MODIS remote sensing data, and calculating to obtain parameters such as an enhanced vegetation index, a leaf area index, a surface water index and a day and night average temperature which are matched with the scale of the flux station; 3) performing seasonal dynamic analysis on respiratory carbon emission of the ecosystem and environmental variables of the respiratory carbon emission; 4) determining a key environmental control factor, 5) establishing an ecological system respiratory carbon emission regression model, 6) estimating the ecological system respiratory carbon emission by utilizing the obtained model, and 7) performing precision evaluation and verification. The method can realize to obtain large-scale alpine meadow ecological system respiratory carbon emission data by utilizing a remote sensing environmental parameter product.

Description

technical field [0001] The invention relates to a method for estimating respiration carbon emissions of a large-area alpine meadow ecosystem based on remote sensing data, and belongs to the technical field of quantitative remote sensing. Background technique [0002] As one of the most widely distributed vegetation types on earth, grassland ecosystem breathes through the ecosystem (R e ) and carbon uptake by plant photosynthesis (GPP) play an important role in the terrestrial carbon cycle. Alpine meadow is an important part of the grassland ecosystem, and the accurate assessment of alpine meadow R e It is critical to accurately quantify terrestrial ecosystem carbon emissions and their impact on climate change. With the establishment of the global flux site based on eddy covariance technology, the continuous observation of carbon flux from the alpine meadow ecosystem to the atmosphere has been realized, and it can be split into GPP based on the split method of daytime or ni...

Claims

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Application Information

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IPC IPC(8): G06F17/18G06Q10/06G06Q50/26
CPCG06F17/18G06Q10/0639G06Q50/26Y02A90/10
Inventor 汤旭光辜清马明国韩旭军
Owner SOUTHWEST UNIVERSITY
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