CN105303295B - Uncertain appraisal procedure based on biomass conversion factor method estimation region scale biomass - Google Patents
Uncertain appraisal procedure based on biomass conversion factor method estimation region scale biomass Download PDFInfo
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Abstract
A kind of uncertain appraisal procedure based on biomass conversion factor method estimation region scale biomass, key step are as follows: step 1: establishing single tree biomass model and single tree volume model respectively；If step 2 is with randomly selecting dry sample, estimation sample ground BEF(biomass conversion factor) and corresponding error；Step 3 repeats step 2 number with thousand times, and estimation BEF mean value and assessment BEF are uncertain；Step 4 estimation area scale biomass, assessment biomass are uncertain.The beneficial effects of the present invention are: providing new approaches for being assessed based on the uncertainty in biomass conversion factor method estimation area scale biomass for large scale biomass estimation and biomass uncertainty appraisal procedure.
Description
Technical field
The present invention relates to the analysis of uncertainty fields of regional scale biomass estimation, especially a kind of to be turned based on biomass
Change the uncertain appraisal procedure during factorization method estimation region scale biomass.
Background technique
Regional scale biomass estimation and analysis of uncertainty are Intergovernmental Panel on Climate Change
(IPCC) one of the report content of guide clear stipulaties.At present the method for large-scale forest biomass estimation mainly have IPCC method,
Biomass regression model method and biomass conversion factor (BEF) method.In the world existing uncertain appraisal procedure generally directed to
Based on the biomass estimation of biomass regression model method, and lack very much for the analysis of uncertainty based on BEF method.
Summary of the invention
For the deficiency of existing method, the purpose of the present invention is to provide one kind for based on BEF method estimation area scale
The uncertain appraisal procedure of biomass, while effectively improving the accuracy and estimation of BEF method estimation large-scale forest biomass
Precision.
To achieve the above object, a kind of uncertainty based on biomass conversion factor method estimation region scale biomass is commented
Estimate method, which is characterized in that comprise the following steps:
Step 1: single tree biomass model and single tree volume model are established respectively.
(1) single tree biomass model is established
Based on modeling data, using single tree biomass measured value as dependent variable, the diameter of a cross-section of a tree trunk 1.3 meters above the ground, the high factors of enumeration of tree are independent variable,
Single tree biomass model is established, expression formula is as follows:
Wherein, g is single tree biomass measured value, and D is diameter of a cross-section of a tree trunk 1.3 meters above the ground measured value, and H is to set high measured value, α0、α1、α2For model ginseng
Number, ε are model residual error, and model estimation uses common least square method.
(2) single tree volume model is established
Using single tree volume measured value as dependent variable, the diameter of a cross-section of a tree trunk 1.3 meters above the ground, the high factors of enumeration of tree are independent variable, establish single tree volume mould
Type, expression formula are as follows:
Wherein, v is single tree volume measured value, and D is diameter of a cross-section of a tree trunk 1.3 meters above the ground measured value, and H is to set high measured value, β0、β1、β2, join for model
Number, ε are model residual error, and model estimation uses common least square method.
Step 2: with randomly selecting N number of sample, estimation sample ground BEF and corresponding error.
(1) it is based on survey data and step 1 model built, estimates single tree biomass and single tree volume in sample ground
(2) to single tree biomass and volume of timber summation, biomass and the volume of timber, expression formula are as follows with calculating sample:
Wherein, j for sample serial number, j=1 ..., n；I is single wood number, i=1 ..., nj, njFor sample trees strain in jth sample ground
Number.
(3) sample ground BEF, expression formula are estimated are as follows:
(4) BEF mean value is estimatedAnd BEF error amountExpression formula is as follows:
Wherein, k indicates kth time circulation.
Step 3: step 2 number is repeated with thousand times, estimation BEF mean value and assessment BEF are uncertain.
(1) assume to repeat step 2 nkSecondary, estimation BEF mean value and corresponding uncertainty, expression formula are as follows:
Wherein,B1Between all cyclic processes
Error, B2It is the error in single cycle.
(2) assessment BEF is uncertain, and expression formula is as follows:
Step 4: estimation area scale biomass, assessment biomass are uncertain.
(1) by always accumulating in tree species estimation area, expression formula is as follows:
(2) estimation area scale biomass, expression formula are as follows:
(3) assessment biomass is uncertain, and expression formula is as follows:
UB=Ubef·Vtotal。
Advantage of the invention include: (1) provide it is a kind of for uncertain based on BEF method estimation area scale biomass
Property appraisal procedure；(2) biomass uncertainty is had evaluated, BEF uncertainty is also had evaluated；(3) estimation of BEF method is effectively improved
The accuracy and estimated accuracy of large-scale forest biomass.
Detailed description of the invention
Fig. 1 is implementing procedure schematic diagram of the invention.
Fig. 2 is BEF estimation and uncertain assessment simulation trend.
Fig. 3 is BEF frequency histogram.
Specific embodiment
Embodiment 1
Test data is divided into modeling data and survey data using masson pine as object:
Modeling data is permanent sample plot masson pine measured data, including the diameter of a cross-section of a tree trunk 1.3 meters above the ground (cm), tree high (m) and forest aerial part are done
Quality (kg).
Survey data is that permanent sample plot is continuously checked data (diameter of a cross-section of a tree trunk 1.3 meters above the ground), sample area 0.067ha, plays survey diameter and is
5cm, sets the high pass list wood diameter of a cross-section of a tree trunk 1.3 meters above the ground and Tree Height Models are estimated, and does not do and is unfolded herein.
The present invention is a kind of uncertain appraisal procedure based on biomass conversion factor method estimation region scale biomass,
Specific step is as follows:
Step 1: single tree biomass model and single tree volume model are established respectively.
(1) single tree biomass model is established
Based on modeling data, using single tree biomass measured value as dependent variable, the diameter of a cross-section of a tree trunk 1.3 meters above the ground, the high factors of enumeration of tree are independent variable,
Single tree biomass model is established, expression formula is as follows:
Wherein, g is single tree biomass measured value, and D is diameter of a cross-section of a tree trunk 1.3 meters above the ground measured value, and H is to set high measured value, α0、α1、α2For model ginseng
Number, ε are model residual error, and model estimation uses common least square method.
(2) single tree volume model is established
Using single tree volume measured value as dependent variable, the diameter of a cross-section of a tree trunk 1.3 meters above the ground, the high factors of enumeration of tree are independent variable, establish single tree volume mould
Type, expression formula are as follows:
Wherein, v is single tree volume measured value, and D is diameter of a cross-section of a tree trunk 1.3 meters above the ground measured value, and H is to set high measured value, β0、β1、β2, join for model
Number, ε are model residual error, and model estimation uses common least square method.
Step 2: with randomly selecting N number of sample, estimation sample ground BEF and corresponding error.
(1) it is based on survey data and step 1 model built, estimates single tree biomass and single tree volume in sample ground
(2) to single tree biomass and volume of timber summation, biomass and the volume of timber, expression formula are as follows with calculating sample:
Wherein, j for sample serial number, j=1 ..., n；I is single wood number, i=1 ..., nj, njFor sample trees strain in jth sample ground
Number.
(3) sample ground BEF, expression formula are estimated are as follows:
(4) BEF mean value is estimatedAnd BEF error amountExpression formula is as follows:
Wherein, k indicates kth time circulation.
Step 3: step 2 number is repeated with thousand times, estimation BEF mean value and assessment BEF are uncertain.
(1) assume to repeat step 2 nkSecondary, estimation BEF mean value and corresponding uncertainty, expression formula are as follows:
Wherein,B1Between all cyclic processes
Error, B2It is the error in single cycle.
(2) assessment BEF is uncertain, and expression formula is as follows:
Step 4: estimation area scale biomass, assessment biomass are uncertain.
(1) by always accumulating in tree species estimation area, expression formula is as follows:
(2) estimation area scale biomass, expression formula are as follows:
(3) assessment biomass is uncertain, and expression formula is as follows:
UB=Ubef·Vtotal。
As shown in Fig. 2, simulated through Monte Carlo method less than 200 times using the above method, biomass estimated value and not true
The proportion of qualitative relative biomass tends towards stability, and the present invention effectively increases the stability of BEF and uncertain estimation
And reliability.
The present invention not only can more accurately estimate biomass and BEF value, can be with precise quantification biomass and BEF value
Uncertainty value, as shown in Figure 3 and Table 1, the probability distribution of BEF is in good Normal Distribution Characteristics, and concentrates on 0.63t/
m3, BEF uncertainty is 0.042t/m3.Biomass uncertainty relative biomass estimated value about 6.71%.
Table 1BEF and biomass estimation and uncertain assessment statistical form
As described above, It should be understood by those skilled in the art that embodiment of the present invention and specification only describe this
The main feature of invention is not limiting the scope of the invention.The present invention can also have many variations, for example, by using other
Biomass Models or timber volume model form, the obvious variation thus amplified out are included in protection model of the invention
It encloses.
Claims (1)
1. a kind of uncertain appraisal procedure based on biomass conversion factor method estimation region scale biomass, feature exist
In comprising the following steps:
Step 1: single tree biomass model and single tree volume model are established respectively；
(1) single tree biomass model is established
Based on modeling data, using single tree biomass measured value as dependent variable, the diameter of a cross-section of a tree trunk 1.3 meters above the ground, the high factors of enumeration of tree are independent variable, are established
Single tree biomass model, expression formula are as follows:
Wherein, g is single tree biomass measured value, and D is diameter of a cross-section of a tree trunk 1.3 meters above the ground measured value, and H is to set high measured value, α0、α1、α2For model parameter, ε
For model residual error, model estimation uses common least square method；
(2) single tree volume model is established
Using single tree volume measured value as dependent variable, the diameter of a cross-section of a tree trunk 1.3 meters above the ground, the high factors of enumeration of tree are independent variable, establish single tree volume model, table
It is as follows up to formula:
Wherein, v is single tree volume measured value, and D is diameter of a cross-section of a tree trunk 1.3 meters above the ground measured value, and H is to set high measured value, β0、β1、β2, it is model parameter, ε is
Model residual error, model estimation use common least square method；
Step 2: with randomly selecting N number of sample, estimation sample ground BEF and corresponding error；
(1) it is based on survey data and step 1 model built, estimates single tree biomass and single tree volume in sample ground；
(2) to single tree biomass and volume of timber summation, biomass and the volume of timber, expression formula are as follows with calculating sample:
Wherein, j for sample serial number, j=1 ..., n；I is single wood number, i=1 ..., nj, njFor sample trees strain number in jth sample ground；
(3) sample ground BEF, expression formula are estimated are as follows:
(4) BEF mean value is estimatedAnd BEF error amountExpression formula is as follows:
Wherein, k indicates kth time circulation；
Step 3: step 2 number is repeated with thousand times, estimation BEF mean value and assessment BEF are uncertain；
(1) assume to repeat step 2 nkSecondary, estimation BEF mean value and corresponding uncertainty, expression formula are as follows:
Wherein,B1For the mistake between all cyclic processes
Difference, B2It is the error in single cycle；
(2) assessment BEF is uncertain, and expression formula is as follows:
Step 4: estimation area scale biomass, assessment biomass are uncertain；
(1) by always accumulating in tree species estimation area, expression formula is as follows:
(2) estimation area scale biomass, expression formula are as follows:
(3) assessment biomass is uncertain, and expression formula is as follows:
UB=Ubef·Vtotal。
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| WO2010040872A1 (en) * | 2008-10-08 | 2010-04-15 | Universidad Politecnica De Valencia | Method for determining the contribution of biomass to cod |
| CN104483271A (en) * | 2014-12-19 | 2015-04-01 | 武汉大学 | Forest biomass amount retrieval method based on collaboration of optical reflection model and microwave scattering model |
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| WO2010040872A1 (en) * | 2008-10-08 | 2010-04-15 | Universidad Politecnica De Valencia | Method for determining the contribution of biomass to cod |
| CN104483271A (en) * | 2014-12-19 | 2015-04-01 | 武汉大学 | Forest biomass amount retrieval method based on collaboration of optical reflection model and microwave scattering model |
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| 区域尺度杉木生物量估计的不确定性度量;傅煜等;《林业科学》;20141231;第79-86页 |
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