Vegetation canopy transpiration inversion algorithm considering phenological information

A vegetation canopy and inversion algorithm technology, applied in the field of vegetation canopy transpiration inversion algorithm, can solve problems such as stomatal conductance and uncertainty of transpiration estimation results, and achieve the effect of reducing seasonal errors and high estimation accuracy

Active Publication Date: 2021-01-05
HOHAI UNIV
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Problems solved by technology

[0006] Therefore, linear simulation of the key parameters of the stomatal conductance model using only the

Method used

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  • Vegetation canopy transpiration inversion algorithm considering phenological information
  • Vegetation canopy transpiration inversion algorithm considering phenological information
  • Vegetation canopy transpiration inversion algorithm considering phenological information

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Embodiment

[0071] Select the US-MMS experimental station in the global flux observation data set FLUXNET2015, the technical process is as follows figure 1 shown. The US-MMS experimental station is located in the south-central region of Indiana in the Midwest of the United States (39°19'N, 86°25'W). It has a 48-meter high-throughput observation tower. The vegetation around the tower is relatively uniform. The main tree species are maple beech, oak, Hickory and other deciduous broad-leaved forests, the canopy is about 27 meters high.

[0072] The observation data is preprocessed, and effective data identification is carried out according to the conditions described in step (1) of the technical solution. After screening, a total of 1222 data samples met the requirements. This site is the forest site with the most effective data in the FLUXNET2015 dataset, so US-MMS site is selected as an example to illustrate the specific implementation and results.

[0073] After quality control, select...

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Abstract

The invention discloses a vegetation canopy transpiration inversion algorithm considering phenological information, belongs to the technical field of water circulation key parameter quantitative inversion. According to the invention, seasonal leaf area change and phenological rhythm information of a vegetation canopy by utilizing satellite remote sensing vegetation index data. The invention provides a dynamic parameterization method for a stomatal conductance slope parameter in a photosynthetic conductance model. The remote sensing leaf area index (LAI) refers to the growth activity of the vegetation canopy leaf, which indicates that the LAI and the stomatal conductance slope parameter have a good linear relationship in the annual period. The vegetation growth season is divided into a growth period and a fading period by utilizing the LAI time sequence change, and the relationship between the LAI and the stomatal conductance slope parameter is respectively established for different phenological periods, so that the asymmetric response of the stomatal conductance slope parameter to the LAI change can be clearly identified, and the important influence of the phenology on the leaf function is reflected; the result shows that the estimation precision of the nonlinear model on the stomatal conductance slope parameter is higher, and the seasonal error of canopy stomatal conductance and transpiration can be effectively reduced.

Description

technical field [0001] The invention belongs to the technical field of quantitative inversion of key parameters of water cycle, and in particular relates to a vegetation canopy transpiration inversion algorithm considering phenological information. Background technique [0002] Surface evapotranspiration (Evapotransspiration, ET) is the sum of vegetation transpiration, vegetation interception evaporation and soil evaporation, and plays an important role in the exchange of land-atmosphere water and energy. About 60% of the world's precipitation comes from ET, and the evapotranspiration process consumes more than 50% of the energy absorbed by the surface. In the global surface ET, transpiration accounts for about 80%, especially in areas with high vegetation coverage, ET is dominated by vegetation transpiration. Therefore, accurate estimation of vegetation transpiration is the key to ET estimation, and it is of great scientific significance to understand the dynamics and caus...

Claims

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Application Information

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IPC IPC(8): G06F30/20G06K9/00G06Q10/06G06F17/18G06F17/10G01N33/00
CPCG06F30/20G01N33/0098G06F17/18G06Q10/06393G06F17/10G06V20/188
Inventor 金佳鑫郭丰生严涛雍斌王卫光
Owner HOHAI UNIV
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