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Method for predicting net primary productivity of vegetation in regional marsh wetland

A technology of net primary productivity and wetland vegetation, applied in the direction of forecasting, complex mathematical operations, data processing applications, etc., can solve problems such as the inability to accurately predict the net primary productivity of swamp wetland vegetation

Pending Publication Date: 2022-01-04
NORTHEAST INST OF GEOGRAPHY & AGRIECOLOGY C A S
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the existing technical means cannot accurately predict the net primary productivity of swamp wetland vegetation in the future, and provides a method for predicting the net primary productivity of swamp wetland vegetation in the region

Method used

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  • Method for predicting net primary productivity of vegetation in regional marsh wetland
  • Method for predicting net primary productivity of vegetation in regional marsh wetland
  • Method for predicting net primary productivity of vegetation in regional marsh wetland

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Experimental program
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specific Embodiment approach 1

[0031] Specific implementation mode one: the steps of a method for predicting the net primary productivity of regional swamp wetland vegetation in this implementation mode are as follows:

[0032] Step 1. Obtain two phases of swamp and wetland distribution data sets, NPP data sets, and monthly observation meteorological data sets of meteorological stations within a period of time covering the study area, and preprocess the NPP data sets;

[0033] Step 2. Based on the distribution data of the two phases of swamp wetlands, extract the distribution of swamp wetlands that have not changed during the research period, and use them as the scope of the research area;

[0034] Step 3. Using the ordinary Kriging interpolation method, interpolation and resampling are carried out on the monthly observation meteorological data sets of the meteorological stations in the study time period, so as to obtain the monthly meteorological data sets of each meteorological element with the same resolu...

specific Embodiment approach 2

[0040] Embodiment 2: The difference between this embodiment and Embodiment 1 is that in Step 1, the year-by-year NPP data set is preprocessed in the form of format conversion and reprojection to unify it into the same coordinate system and projection. Others are the same as the first embodiment.

specific Embodiment approach 3

[0041] Specific implementation mode three: the difference between this implementation mode and specific implementation mode one or two is that step six: through multivariate stepwise regression analysis pixel by pixel, construct the net primary productivity prediction model of swamp wetland vegetation under the influence of climate change, select the fitting The model with the highest coefficient value is used as the final prediction model, and the formula is as follows:

[0042] NPP=a 0 +a 1 x 1 +a 2 x 2 +a 3 x 3 +…+a n x n Formula 1)

[0043] where x 1 , x 2 , x 3 ,...x n are the values ​​of a certain meteorological element in a certain month during the research period, a 1 , a 2 , a 3 ,...a n are the corresponding coefficients, a 0 is a constant term. Others are the same as those in Embodiment 1 or 2.

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Abstract

The invention discloses a method for predicting the net primary productivity of vegetation in a regional marsh wetland, and relates to a method for predicting the net primary productivity of future regional marsh wetland vegetation under the influence of climate change. The invention aims to solve the problem that the prior art means cannot accurately predict the net primary productivity of future marsh wetland vegetation. The method comprises the following steps: selecting unchanged marsh wetland distribution within a certain research time period as a research area; acquiring and preprocessing remote sensing data and meteorological data of marsh wetland vegetation in the research area; interpolating the meteorological data, and resampling; extracting net primary productivity and meteorological element values corresponding to all marsh vegetation pixels in the research area; constructing a prediction model; and predicting the net primary productivity of the marsh wetland vegetation in the future by using the prediction model in combination with meteorological data in a future climate change scene. The net primary productivity of the marsh vegetation under the influence of future climate change is predicted by utilizing the advantages that the remote sensing data is large in spatial scale and easy to obtain and combining the existing meteorological data.

Description

technical field [0001] The invention relates to a method for predicting the net primary productivity of swamp wetland vegetation, in particular to a method for predicting the net primary productivity of regional swamp wetland vegetation under future climate scenario changes by using remote sensing data and meteorological data. Background technique [0002] Marsh wetlands are one of the main types of wetlands and play an important role in the global carbon cycle. Marsh wetlands can not only promote water storage, regulate regional climate, but also maintain ecological balance, protect biodiversity, and provide habitat for wild animal breeding. As an important part of the swamp ecosystem and one of the external manifestations of wetland characteristics, the vegetation of the swamp can maintain the ecological function of the swamp. Marsh vegetation plays a very important role in the energy exchange and biogeochemical cycle in the marsh ecosystem. [0003] Vegetation net prima...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06F17/18
CPCG06Q10/04G06F17/18Y02A90/10
Inventor 王延吉神祥金佟守正姜明吕宪国
Owner NORTHEAST INST OF GEOGRAPHY & AGRIECOLOGY C A S
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