CN110058262A - A kind of method of vegetation radiative transfer model inverting forest fire burning earthquake intensity - Google Patents
A kind of method of vegetation radiative transfer model inverting forest fire burning earthquake intensity Download PDFInfo
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Abstract
A method of the vegetation radiative transfer model inverting forest fire burning earthquake intensity based on the layering of trees coverage parameter belongs to remote-sensing inversion technical field.For this method by introducing trees coverage parameter in vegetation radiative transfer model forward simulation and carrying out hierarchy parameters according to its variation range, building is suitable for the look-up table of different trees coverage ranges；Pass through section where inputting trees coverage Remote Sensing Products to determine trees coverage into refutation process rear, so that burning earthquake intensity inverting carries out in the look-up table corresponding to section where trees coverage, to improve the matching degree of burning earthquake intensity and Remote Spectra response curve, it reduces spectrum to obscure on burning earthquake intensity inverting bring influence, and then improves burning earthquake intensity inversion accuracy.The present invention can more true, ground after accurately simulation and inverting fire occur actual conditions, the burning earthquake intensity precision that inverting obtains is higher, and the indicative function of forest management and protection is definitely after the condition of a disaster assessment and calamity after fire occurs.
Description
Technical field
The invention belongs to remote-sensing inversion technical field, in particular to a kind of vegetation radiative transfer model inverting forest fire combustion
Burn the method for earthquake intensity
Background technique
Forest fire burning earthquake intensity is generally defined as influence of the fire to vegetation and soil in specific region.Accurately estimate
Forest fire burning earthquake intensity is calculated for quantization fire to crucial ecological process (revegetation and object after such as tree death situation, calamity
Kind in/object interspecies competition) influence and fire after forest conservation and management all have great importance.
Fire can cause to directly affect to the physicochemical property of surface vegetation and soil.Vegetation, soil and the calamity of different conditions
Ground ashes generate different echo-signals to remote sensor afterwards, therefore, so that estimating Forest Fire based on satellite remote sensing date
Calamity burning earthquake intensity is possibly realized.It is different from general vegetation biochemical parameter (chlorophyll, canopy water content, dry matter content), combustion
Burning earthquake intensity is not singly some single vegetation parameter, but is related to the synthesis of the multiple factors such as earth's surface ashes after vegetation, soil and calamity
Assessment.Most representative ground quantitative assessment burning earthquake intensity and to verify the actual measurement earthquake intensity index of remote sensing inversion accuracy be comprehensive at present
Combination burning index (CBI), variation range are 0~3, and " 0 " represents unburned, and " 3 " represent completely burned.CBI is by forest cover
Structure is divided into 5 layers (surface soil layer, low cover, middle low cover, at the middle and upper levels vegetation and upper layer vegetation) from top to bottom, to every
The burning degree of one layer of vegetation is assessed to obtain the burning earthquake intensity value CBI of specific stratum respectivelyi, wherein i is stratum's number,
The average combustion earthquake intensity value for finally calculating 5 stratum obtains the CBI of all stratum.In actual operation, often by this 5 stratum
It is reduced to 4 layers, i.e. surface soil layer, low cover, middle layer vegetation (middle low cover, at the middle and upper levels vegetation) and upper layer vegetation.
Be broadly divided into following four classes currently based on the method that optical remote sensing means estimate burning earthquake intensity: based on vegetation index and
The empirical statistics method of differential form, spectral mixing decomposition method, machine learning method and vegetation radiation transmission after calamity before its calamity
Model method.Empirical statistics method based on differential form after calamity before vegetation index and its calamity is convenient, efficient, but according to statistics
The empirical relation of foundation is different according to specific time and site, does not have universality and relies on measured data for fitting empirical model.In fire
By decomposing the method estimation burning earthquake intensity of mixed pixel after generation, its advantage is that all of image after single width fire can be used
Spectral band information, but since the application of such method is restricted because needing the endmember spectra library of extensive, given area.
In random forest method as the machine learning method of representative, it its advantage lies in being able to make full use of polynary environmental variance but it estimated
Precision depends critically upon the selection of training data, and the model of training does not often have universality.And vegetation radiation transmission mould
Type is a kind of physical model, and the basis of building is the Physical Mechanism that solar photon is transmitted in vegetation internal radiation, is thus established
Reflectivity empirical statistics method compared with the relationship of burning earthquake intensity has more universality.It is estimated and is burnt based on vegetation radiative transfer model
Earthquake intensity is broadly divided into two steps, is parameterized and carried out forward simulation to model first, and building is used for the look-up table of inverting CBI；
Secondly, rear into refutation process, by the Reflectivity for Growing Season extracted based on remote sensing image and the earth's surface simulated in model lookup table
Reflectivity is matched, and then finds the corresponding CBI value of the highest simulated reflectivity of matching degree.Such method is independent of ground
Measured data, and can make full use of all reflectivity band class informations of remote sensing image, be it is a kind of not only there is stronger universality but also
It is relatively easy to the inversion method realized.
Since the estimation of CBI considers the combustion information of multilayer vegetation stratum, it is therefore necessary to which selection can simulate multilayer plant
By the physical model (such as: ACRM, MCRM, FRT model) of radiation transmission characteristic.However, in optical remote sensing image imaging process
In, due to the variation of trees coverage, underlying surface soil and ashes is caused to generate difference to the signal contribution of remote sensor.Cause
Even if this identical burning earthquake intensity when using vegetation radiative transfer model inverting burning earthquake intensity can correspond to different spectral responses
Curve；Identical spectral response curve can also correspond to different burning earthquake intensitys.There is scholar for trees coverage to burning earthquake intensity
The influence of estimation is improved (GeoCBI), and way is during fieldwork by the vegetative coverage of each vegetation stratum
It spends as the weight for calculating CBI, as shown in Equation 1.
In formula, GeoCBI represents the burning earthquake intensity index after improving；M represents each vegetation stratum；N represents total stratum's layer
Number；FCOVmRepresent the vegetation coverage of specific stratum；CBImRepresent the CBI value of specific stratum.It is improved in this way the result is that improve
The one-to-one relationship of remote sensing image reflectivity and burning earthquake intensity index.However, this mode of operation exist it is artificial improve or
The defect for reducing burning earthquake intensity estimation grade assesses low trees according to the calculation method of the index that is, during fieldwork
The burning earthquake intensity in coverage region, which can exist, over-evaluates；It estimates that the burning earthquake intensity in high trees coverage region can exist to underestimate.Because
When the lower region of trees coverage calculates GeoCBI, weighted value shared by the trees of upper layer is smaller and burning degree is lower and under
The meadow and shrub proportion that layer is burned are larger and burning is serious, so calculated GeoCBI can be higher than original CBI；?
The higher region of trees coverage, when calculating GeoCBI, weighted value shared by the trees of upper layer is larger and burning degree is lower and under
The meadow and shrub proportion that layer is burned are smaller and burning is serious, so calculated GeoCBI can be lower than original CBI, this
It is inconsistent with actual burning earthquake intensity situation.Therefore, how accurately to establish fire burning earthquake intensity and remote sensing image reflects
This problem of corresponding relationship between rate is generally existing in based on vegetation radiative transfer model inverting burning earthquake intensity research, so far
It could not effectively be solved.
Summary of the invention
For in existing forest fire burning earthquake intensity refutation process, fired based on the inverting forest fire of vegetation radiative transfer model
There are spectrum confounding issues caused by being changed by trees coverage when burning earthquake intensity, provides a kind of vegetation radiative transfer model inverting
The new method of forest fire burning earthquake intensity.
Technical solution provided by the invention is specific as follows:
A kind of method of vegetation radiative transfer model inverting forest fire burning earthquake intensity, which is characterized in that including walking as follows
It is rapid:
Step A: the optical remote sensing image after research area's forest fire occurs and the trees coverage before fire generation are obtained
Remotely-sensed data；；
Step B: the earth surface reflection of multilayer vegetation after selection vegetation radiative transfer model forward simulation research area's fire occurs
Rate carries out hierarchy parameters operation to the vegetation radiative transfer model, trees coverage parameter is divided into several sections,
Then simulation is carried out according to the trees covering angle value in each section respectively and look-up table constructs；
Step C: in the rear trees coverage input mould that preceding remote sensing image will occur according to fire into refutation process and extract
Type is fired in the corresponding look-up table in specific trees coverage section after determining the section where trees cover angle value
Burn earthquake intensity inverting.
Further, the Reflectivity for Growing Season data after the fire occurs should carry out pre- before for inverting burning earthquake intensity
The step of processing, the pretreatment include the removal of radiation calibration, atmospheric correction, Yun Jiyun shade.
Further, trees coverage remotely-sensed data can be calculated by image Reflectivity for Growing Season before calamity before the fire occurs
Or related Remote Sensing Products obtain.
Further, since ground actual measurement CBI considers the respective combustion state of soil stratum and multilayer vegetation stratum, because
This described vegetation radiative transfer model should be the multilayered model that can simulate multilayer vegetation structure radiation transmission characteristic.
Further, parameters sensitivity analysis should be carried out to model before model parameterization operation.Since vegetation radiates
Mode is complex, is related to that parameter is numerous, but and not all parameter variation it is sensitive to target reflectivity, therefore, be
It improves model execution efficiency and reduces since model ill-posed inversion introduces excessive uncertainty, sensibility point should be carried out to model
Analysis operation.
Further, hierarchy parameters are carried out (i.e. to trees coverage parameter according to trees coverage parameter variation range
Carry out interval division) precision that trees coverage assists product is depended primarily on, the number that division obtains section is unrestricted, draws
The length for getting section may be the same or different.
As a kind of specific embodiment, trees coverage (0~100%) parameter is divided into 5 with 20% for interval
Section carries out simulation and look-up table building respectively.
As a kind of specific embodiment, trees coverage (0~100%) parameter is divided into 10 with 10% for interval
Section carries out simulation and look-up table building respectively.
As a kind of specific embodiment, trees coverage (0~100%) parameter is divided into 20 with 5% for interval
Section carries out simulation and look-up table building respectively.
As a kind of specific embodiment, trees coverage (0~100%) parameter is divided into 25 with 4% for interval
Section carries out simulation and look-up table building respectively.
Design concept of the invention is particular by the introducing trees coverage in vegetation radiative transfer model forward simulation
Parameter simultaneously carries out hierarchy parameters according to its variation range to trees coverage parameter, and building is suitable for different trees coverage models
The look-up table enclosed；Trees coverage is defined by inputting trees coverage Remote Sensing Products into refutation process rear, is made
Burning earthquake intensity inverting is operated in the corresponding look-up table of specific trees coverage range, to improve burning earthquake intensity and distant
Feel the matching degree of spectral response curve, reduces spectrum and obscure on burning earthquake intensity inverting bring influence, and then improve burning earthquake intensity
Inversion accuracy.
Compared with prior art, the beneficial effects of the present invention are:
The present invention be suitable for solve it is all based on the inverting forest fire of vegetation radiative transfer model burning earthquake intensitys during by
The spectrum confounding issues caused by trees coverage changes.The present invention is first according to the trees coverage parameter by stages in model
Simulate and construct look-up table, secondly, it is rear occurred into inverting according to fire before trees coverage determine inverting section, to combustion
Earthquake intensity is burnt to carry out inverting in the corresponding look-up table in specific trees coverage section rather than carry out global optimum's retrieval, the processing
Method can be effectively improved the corresponding relationship of canopy reflectance spectrum acquired in burning earthquake intensity and remote sensing image, and then improve burning earthquake intensity
Inversion accuracy.Compared to traditional method based on vegetation radiative transfer model inverting forest fire burning earthquake intensity, the present invention
Method forward simulation and after consider into inverting trees coverage rather than consider in fieldwork link, so as to
The actual conditions on ground after more true, accurate simulation and inverting fire occur, the burning earthquake intensity precision of institute's inverting is higher, right
Fire occur after the condition of a disaster assessment and calamity after the indicative function of forest management and protection definitely.
Detailed description of the invention
Fig. 1 is the evaluation scheme of ground actual measurement burning earthquake intensity (CBI).
Background return schematic diagram after Fig. 2 occurs for the fire that remote sensing image obtains identical burning earthquake intensity.Wherein, Fig. 2 a
The higher situation of trees coverage is represented, Fig. 2 b represents the lower situation of trees coverage.
It is different when being 2.0 that Fig. 3 is the CBI value that vegetation radiative transfer model is simulated after being improved according to the present invention conventional method
Spectral response curve under trees coverage, TC represents trees coverage in figure.
Fig. 4 is the inversion method based on method proposed by the invention and the estimation burning earthquake intensity of conventional radiation mode
Accuracy comparison figure, wherein RTM+TCC represents burning earthquake intensity inversion result of the invention in figure (a), RTM+GOS is represented in figure (b)
The inversion result of conventional method.
Specific embodiment
It is anti-to improved vegetation radiative transfer model provided by the invention with Figure of description combined with specific embodiments below
The method for drilling forest fire burning earthquake intensity is described further:
Step 1: data preparation
The optical remote sensing image after research area's forest fire occurs is obtained first and the trees coverage before fire generation is distant
Feel data.Wherein, radiation calibration, atmospheric correction, the operation of Yun Jiyun shadow removal should be carried out to obtain to the remotely-sensed data after fire
To Reflectivity for Growing Season data.Current existing Remote Sensing Products or the earth's surface according to remote sensing image before calamity can be used in trees coverage data
Reflectivity is obtained by trees coverage extraction algorithm.According to current existing trees coverage Remote Sensing Products, it should be carried out
The spatial resolution of remotely-sensed data keeps unified after re-sampling operations and calamity.
Step 2: model selection
The assessment of the ground actual measurement index CBI of fire burning earthquake intensity is to comprehensively consider the combustion of multilayer vegetation and surface soil layer
The result of burning degree.During actual assessment, as shown in Figure 1, forest cover structure is divided into 5 layers of (ground by CBI from top to bottom
Soil horizon, low cover, middle low cover, at the middle and upper levels vegetation and upper layer vegetation), each stratum is assessed and calculated respectively
Final average CBI.Therefore, vegetation mode should select that the multilayer film of multilayer vegetation structure radiation transmission feature can be simulated
Type, such as ACRM, MCRM, FRT model.
Step 3: model sensitivity analysis and model forward simulation
Vegetation radiative transfer model parameter is numerous, but and not all parameter to fire burning earthquake intensity inverting used in target
Wave band is sensitive, and therefore, it is necessary to filter out sensitive to target wave band reflectivity in model by carrying out sensitivity analysis to model
Parameter carries out forward simulation and look-up table building.
Due to the variation of trees coverage, ground ashes and soil can become the contribution degree of remote sensor signal therewith
Change, different spectral responses can be generated on remote sensing image identical burning earthquake intensity.For situation shown in Fig. 2 a, due to
Trees covering is more dense, and green tree crown will block the reflection signal from ground, and Fig. 2 b is sparse since trees cover,
The signal of the vegetation and soil that are burned from underlying surface will be much larger than Fig. 2 a, therefore Fig. 2 a and Fig. 2 b will correspond to two differences
Obviously spectral reflectance curve, but burning earthquake intensity both actually be it is identical, because of the burning of each vegetation stratum
Grade is all the same.If, since the trees covering of Fig. 2 a is more dense, calculating GeoCBI according to the calculation method of GeoCBI
When upper layer trees shared by weight it is higher, trees layer burning degree is lower in addition, therefore the GeoCBI being calculated will be less than Fig. 2 b
GeoCBI value, this is inconsistent with actual conditions.
And the influence proposed by the invention based on conventional method introducing trees coverage (TC) and the variation range according to TC
By stages simulation is carried out, building is suitable for the look-up table of specific trees coverage range respectively.The identical burning of modeling is strong
The result of spectral response curve of the angle value (CBI=2.0) under different trees coverages section is as shown in figure 3, in modeling
In the process, other parameters are kept fixed, and only change trees coverage (TC) this parameter, we can intuitively find out from Fig. 3,
For TC by changing to lower than 10% higher than 50%, very big variation is had occurred in the shape of the curve of spectrum, it is seen that TC is to burning earthquake intensity
Influence be very big.
Therefore, for the burning earthquake intensity inverting in the case of different trees coverages, before vegetation radiative transfer model to
In simulation process, by stages simulation is carried out according to the variation range of trees coverage, building is suitable for the covering of specific trees respectively
Spend the look-up table of range, can more true, ground after accurately simulation and inverting fire occur actual conditions so that inverting
The precision of gained burning earthquake intensity is higher.
Step 4: backward inverting
Rear into refutation process, by the remotely-sensed data prepared in step 1 while it being used as input data, is sent out according to fire
Trees coverage data before death determine inverting section, to burning earthquake intensity in the corresponding look-up table in specific trees coverage section
Interior carry out inverting.The corresponding pass of canopy reflectance spectrum acquired in burning earthquake intensity and remote sensing image can be effectively improved by operating above
It is
As shown in Figure 4, method proposed by the invention significantly improves the inversion accuracy of burning earthquake intensity CBI, compared to tradition
Based on the inversion method of vegetation radiative transfer model, new method proposed by the present invention by survey CBI and inverting CBI between decision system
Number R2(better closer to 1) is increased to 0.54 from 0.33；The slope (better closer to 1) of fit line is increased to 0.8 from 0.56；
Root-mean-square error RMSE (the smaller the better) is reduced to 0.43 by 0.53.The experimental results showed that the mentioned method of the present invention effectively solves
Influence problem of the trees coverage of having determined to burning earthquake intensity estimation.As it can be seen that new method proposed by the present invention can effectively solve the problem that tree
The wooden coverage improves the precision of inversion result to the influence problem of burning earthquake intensity estimation.
Claims (6)
1. a kind of method of vegetation radiative transfer model inverting forest fire burning earthquake intensity, which comprises the steps of:
Step A: the optical remote sensing image after research area's forest fire occurs and the trees coverage remote sensing before fire generation are obtained
Data；
Step B: the Reflectivity for Growing Season of multilayer vegetation after selection vegetation radiative transfer model forward simulation research area's fire occurs, it is right
The vegetation radiative transfer model carries out hierarchy parameters operation, trees coverage parameter is divided into several sections, then
Simulation is carried out to the trees covering angle value in each section respectively and look-up table constructs；
Step C: in the rear trees coverage input model that preceding remote sensing image will occur according to fire into refutation process and extract, really
After determining the section where trees cover angle value, burning earthquake intensity is carried out in the corresponding look-up table in specific trees coverage section
Inverting.
2. the method according to claim 1, wherein the Reflectivity for Growing Season data after the fire occurs are being used for
Pretreated step should be carried out before inverting burning earthquake intensity, the pretreatment includes radiation calibration, atmospheric correction, Yun Jiyun shade
Removal.
3. the method according to claim 1, wherein trees coverage remotely-sensed data passes through before the fire occurs
Image Reflectivity for Growing Season calculates before calamity or related Remote Sensing Products obtain.
4. the method according to claim 1, wherein the vegetation radiative transfer model is that can simulate multilayer plant
By the multilayered model of structural radiation transmission characteristic.
5. the method according to claim 1, wherein joining before model layers parameterization operations to model
Number sensitivity analysis.
6. the method according to claim 1, wherein carrying out layering ginseng according to trees coverage parameter variation range
Numberization, the length that division obtains section are same or different.
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| CN112711833A (en) * | 2020-12-08 | 2021-04-27 | 电子科技大学 | Calculation method for non-continuous forest combustible load |
| CN115994618A (en) * | 2022-12-22 | 2023-04-21 | 江西师范大学 | Evaluation model construction and prediction method based on subtropical forest fire intensity |
| CN117436003A (en) * | 2023-12-15 | 2024-01-23 | 中国科学院、水利部成都山地灾害与环境研究所 | Remote sensing dynamic monitoring method for erosion of soil of fire trace land by considering fire severity |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117436003B (en) * | 2023-12-15 | 2024-03-15 | 中国科学院、水利部成都山地灾害与环境研究所 | Remote sensing dynamic monitoring method for erosion of soil of fire trace land by considering fire severity |
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