CN108009384A - A kind of urban forests organic C storage landscape scale deduction method - Google Patents
A kind of urban forests organic C storage landscape scale deduction method Download PDFInfo
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Abstract
A kind of urban forests organic C storage landscape scale deduction method, the present invention relates to urban forests organic C storage landscape scale deduction method, during it is in order to solve existing urban forests management, the problem of urban forests organic C storage data are difficult to obtain in landscape scale.Deduction method：First, the position of each forest sample prescription is positioned using GPS system, calculates the urban forests organic C storage in each sample prescription；2nd, city forest cover index in forest sample prescription is extracted by the position of each forest sample prescription, the data as structure model；3rd, using the qualitative relationships between the urban forests organic C storage in each vegetation index of correlation analysis and each forest sample prescription, the best vegetation index of correlation is determined as optimal vegetation index, then using the relation between the urban forests organic C storage in the optimal vegetation index of multiple regression quantitative analysis and each forest sample prescription.Urban forests organic C storage landscape scale deduction method of the present invention is easy, reconstruction speed is fast, low cost and management are easy.
Description
Technical field
The present invention relates to urban forests organic C storage landscape scale deduction method.
Background technology
Since industrial age, due to caused by mankind's activity greenhouse gas emission roll up, using climate warming as
The whole world change of main feature, generates tremendous influence to natural ecosystems, human socioeconomic system, is international society
The significant problem of meeting common concern, numerous studies show：CO in air2The rise of concentration is to cause the main driving of climate warming
Factor, therefore how effectively to adsorb with reducing CO in air2Concentration becomes current urgent problem.Forest passes through photosynthetic work
With the CO absorbed in air2, and it is fixed in plant and soil in the form of biomass, so as to play in fixed air
CO2Carbon remittance effect, as the main body of terrestrial ecosystems, it plays the function of important " buffer " and " valve ".City is gloomy
Woods is referred to as " lung in city ", is an important component in forest ecosystem, is absorbing fixed, mitigation of climate change
Aspect plays an important role.On the one hand the CO in air is fixed by photosynthesis2, on the other hand by shade and keep out the wind come
Reduce the energy consumption carbon emission of architecture refrigerating and heating.Therefore urban forests organic C storage how is quickly obtained so as to understand
Urban forests ability to pool carbon and then to greatest extent the carbon sequestration ecological functions of raising urban forests are current be badly in need of solving one
Problem.
However, current urban forests organic C storage data are in short supply, the biography being primarily due to based on sample investigation
The acquisition modes of system urban forests organic C storage are time-consuming and laborious.And the point-like non-continuous data for being all based on sample prescription obtained, can not
Urban forests organic C storage is evaluated on urban landscape scale, the missing of the spatial data of urban forests organic C storage can be shown
Write ground influence the spatial analysis of urban forests carbon sequestration ecological functions study, urban forests organic C storage spatially how to present and its
Heterogeneous rule is the major issue to merit attention.In short, still lack the acquisition urban forests organic C storage in landscape scale at present
Rapid and effective method, can not meet the actual demand of China's urban forests management and city good for habitation's construction.
The content of the invention
During solving existing urban forests management, urban forests organic C storage number in landscape scale
The problem of according to being difficult to obtain, and a kind of urban forests organic C storage landscape scale deduction method is provided.
Urban forests organic C storage landscape scale deduction method of the present invention is realized according to the following steps：
First, the field survey of urban forests organic C storage：In summer, used using ArcGIS spatial analysis software in research area
The mode of stratified random sampling carries out the laying of urban forests sample prescription, after the completion of the setting of forest sample prescription, using GPS system to each
The position of forest sample prescription is positioned, and then carries out every wooden dipping for the trees in sample prescription, calculates the city in each sample prescription
Forest carbon storage, the urban forests organic C storage in sample prescription are the sum of individual organic C storage in sample prescription；
Individual organic C storage=0.5 × Individual Biomass wherein in sample prescription；Individual Biomass=0.8 × Bag；
Total strain biomass of each seeds is calculated by following different rate growth formula formula：
Pinus：Bag=Bs+Bb+Bl, wherein Bs=0.11*D2.34, Bb=0.01*D2.58, Bl=0.0049*D2.48；
Elm：Bag=Bs+Bb+Bl, wherein Bs=0.043*D2.87, Bb=0.007*D2.67, Bl=0.003*D2.50；
Picea：Bag=Bs+Bb+B1, wherein Bs=0.06*D2.48, Bb=0.01*D2.41, Bl=0.0083*D2.37；
Willow：Bag=0.067*D2.558；
Acer：Bag=0.085*D2.535；
Ash field：Bag=0.137*D2.408；
Tilia：Bag=0.041*D2.668；
The rose family：Bag=0.216*D1.705；
Wherein Bag:Total strain biomass；Bs:Trunk biomass；Bb：Branch biomass；Bl：Leaf biomass；D：Trees chest
Footpath；
2nd, urban forests vegetation index obtains：Pass through TM/ETM image remote sensing shadows in the same time for laying forest sample prescription
As gathered data source, then a variety of vegetation indexs from data source in extraction research area, then using remote sensing software ENVI into
Row calculates inverting, obtains the spatial data of urban forests vegetation index, and forest sample prescription is extracted by the position of each forest sample prescription
Interior city forest cover index, the data as structure model；
Wherein described urban forests vegetation index is ratio vegetation index SR, green normalized differential vegetation index GNDVI and returns
One changes vegetation index NDVI；
3rd, build urban forests organic C storage scale and deduce model：The city in each forest sample prescription obtained according to step 1
The urban forests vegetation index that city's forest carbon storage and step 2 obtain, on forest sample size, first using correlation point
The qualitative relationships between the urban forests organic C storage in each vegetation index and each forest sample prescription are analysed, the best vegetation of correlation refers to
Number is determined as optimal vegetation index, then using the city in the optimal vegetation index of multiple regression quantitative analysis and each forest sample prescription
Relation between city's forest carbon storage, structure obtain urban forests organic C storage scale and deduce model.
The present invention carries out position (GPS) positioning of sample prescription using high-precision difference GPS system, so that effectively accurately extraction
The vegetation index of TM image picture elements where sample prescription, deduces model for structure scale and offers precise data support.
The method that integrated use remote sensing of the present invention, geographic information system technology are combined with sample prescription on-site inspection, realizes pin
To quick reconstruction of the urban forests organic C storage in landscape scale, the space lattice for showing urban forests organic C storage of quicklook
Office's situation.For clear and definite urban forests, rational deployment provides data reference to the present invention in landscape scale, to urban forests
Make rational planning for important directive significance.
Urban forests organic C storage landscape scale deduction method of the present invention is easy, reconstruction speed is fast, low cost and management are easy,
It can be widely used in the management of urban forest ecosystem.
Brief description of the drawings
Fig. 1 is the urban forests sample prescription distribution map in embodiment one, wherein ● represent modeling sampling point, the verification of ▲ representative model
Sampling point；
Fig. 2 is urban forests organic C storage estimation models curve of the embodiment one based on NDVI；
Fig. 3 is the organic C storage estimation models precision test of embodiment one；
Fig. 4 is one NDVI vegetation index spatial distribution maps of embodiment；
Fig. 5 is one urban forests organic C storage spatial distribution map of embodiment.
Embodiment
Embodiment one：Present embodiment urban forests organic C storage landscape scale deduction method is real according to the following steps
Apply：
First, the field survey of urban forests organic C storage：In summer, used using ArcGIS spatial analysis software in research area
The mode of stratified random sampling carries out the laying of urban forests sample prescription, after the completion of the setting of forest sample prescription, using GPS system to each
The position of forest sample prescription is positioned, and then carries out every wooden dipping for the trees in sample prescription, calculates the city in each sample prescription
Forest carbon storage, the urban forests organic C storage in sample prescription are the sum of individual organic C storage in sample prescription；
Individual organic C storage=0.5 × Individual Biomass wherein in sample prescription；Individual Biomass=0.8 × Bag；
Total strain biomass of each seeds is calculated by following different rate growth formula formula：
Pinus：Bag=Bs+Bb+Bl, wherein Bs=0.11*D2.34, Bb=0.01*D2.58, Bl=0.0049*D2.48；
Elm：Bag=Bs+Bb+Bl, wherein Bs=0.043*D2.87, Bb=0.007*D2.67, Bl=0.003*D2.50；
Picea：Bag=Bs+Bb+Bl, wherein Bs=0.06*D2.48, Bb=0.01*D2.41, Bl=0.0083*D2.37；
Willow：Bag=0.067*D2.558；
Acer：Bag=0.085*D2.535；
Ash field：Bag=0.137*D2.408；
Tilia：Bag=0.041*D2.668；
The rose family：Bag=0.216*D1.705；
Wherein Bag:Total strain biomass；Bs:Trunk biomass；Bb：Branch biomass；Bl：Leaf biomass；D：Trees chest
Footpath；
2nd, urban forests vegetation index obtains：Pass through TM/ETM image remote sensing shadows in the same time for laying forest sample prescription
As gathered data source, then a variety of vegetation indexs from data source in extraction research area, then using remote sensing software ENVI into
Row calculates inverting, obtains the spatial data of urban forests vegetation index, and forest sample prescription is extracted by the position of each forest sample prescription
Interior city forest cover index, the data as structure model；
Wherein described urban forests vegetation index is ratio vegetation index SR, green normalized differential vegetation index GNDVI and returns
One changes vegetation index NDVI；
3rd, build urban forests organic C storage scale and deduce model：The city in each forest sample prescription obtained according to step 1
The urban forests vegetation index that city's forest carbon storage and step 2 obtain, on forest sample size, first using correlation point
The qualitative relationships between the urban forests organic C storage in each vegetation index and each forest sample prescription are analysed, the best vegetation of correlation refers to
Number is determined as optimal vegetation index, then using the city in the optimal vegetation index of multiple regression quantitative analysis and each forest sample prescription
Relation between city's forest carbon storage, structure obtain urban forests organic C storage scale and deduce model.
The trees in sample prescription are carried out in present embodiment step 1 per wooden dipping, investigation index to include：Seeds name, chest
Footpath, tree height, hat width, health status etc., finally calculate the urban forests organic C storage in each sample prescription.In present embodiment
The estimation of urban forests individual trees ground biomass dry weight uses different rate growth formula, and equation is chosen and is based on near-earth principle.
If some species does not have available different rate growth formula, use is belonged to together with it or the different rate growth formula of equal species,
If belong to together or the different rate growth formula of equal species still lacks, using general different rate growth formula, that is, Bag=
0.0881*D2.467.Since urban trees need daily trimming and maintenance, its ground biomass is less than the life grown in natural forests
Object amount, therefore, in urban forests the estimation of trees biomass should be multiplied by coefficient 0.8.Individual Biomass is converted to carbon C and is multiplied by coefficient
0.5。
Embodiment two：The present embodiment is different from the first embodiment in that urban forests sample prescription in step 1
Laying place includes road woods, attached woods, forest for landscape and recreation, production forest and ecological public welfare forests.Other steps and parameter with it is specific
Embodiment one is identical.
Embodiment three：The present embodiment is different from the first and the second embodiment in that forest described in step 1
The area of sample prescription is 30m × 30m.Other steps and parameter are the same as one or two specific embodiments.
Embodiment four：Unlike one of present embodiment and embodiment one to three described in step 1
The quantity of forest sample prescription is more than 40.Other steps and parameter are identical with one of embodiment one to three.
Embodiment five：If certain in step 1 unlike one of present embodiment and embodiment one to four
A seeds do not have available different rate growth formula, then using being belonged to together with it or the different rate growth formula of equal species.Other steps
Rapid and parameter is identical with one of embodiment one to four.
Embodiment six：If present embodiment belongs to together or equal from step 1 unlike embodiment five
The different rate growth formula of seeds still lacks, then using general different rate growth formula, that is, Bag=0.0881*D2.467.Other steps
Rapid and parameter is identical with embodiment five.
Embodiment seven：Pass through in step 2 unlike one of present embodiment and embodiment one to six
TM/ETM image remote sensing image gathered datas source, image cutting-out, geometric correction and atmospheric correction are carried out to data source.Other steps
And parameter is identical with one of embodiment one to six.
Embodiment eight：Step 2 unlike one of present embodiment and embodiment one to seven is distant in TM
On the basis of feeling image band value, wave band calculating is carried out in remote sensing software ENVI using calculation formula, and then inverting obtains
NDVI, SR, GNDVI vegetation index, corresponding calculation formula are NDVI=(b4-b3)/(b4+b3), SR=(b4/b3), GNDVI
=(b4-b2)/(b4+b2), wherein b2, b3 and b4 are respectively TM remote sensing images second band, the 3rd wave band and the 4th wave band
Band value.Other steps and parameter are identical with one of embodiment one to five.
Embodiment nine：Obtained unlike one of present embodiment and embodiment one to eight according to step 3
The urban forests organic C storage scale arrived deduces model, with reference to optimal vegetation index in the landscape scale based on remote sensing, so that clearly
Urban forests organic C storage spatial framework in (display) research area's landscape scale.Other steps and parameter and embodiment one to
One of eight is identical.
Embodiment：The present embodiment urban forests organic C storage landscape scale deduction method is implemented according to the following steps：
First, the field survey of urban forests organic C storage：Main city zone is research in the present embodiment selection Changchun outer shroud high speed
Region, in summer, city is carried out by the way of being sampled using ArcGIS10.3 spatial analysis software in research area using stratified random
The laying of forest sample prescription, after the completion of the setting of forest sample prescription, positions the position of each forest sample prescription using GPS system, into
And carried out for the trees in sample prescription per wooden dipping, investigation index includes：Seeds name, the diameter of a cross-section of a tree trunk 1.3 meters above the ground, tree height, hat width and health status,
The urban forests organic C storage in each sample prescription is calculated, the forest sample prescription includes road woods, attached woods, forest for landscape and recreation, production
Woods and ecological public welfare forests；
Individual organic C storage=0.5 × Individual Biomass wherein in sample prescription；Individual Biomass=0.8 × Bag (total strain biology
Amount)；
Trees biomass calculation formula
Bag:Total strain biomass；Bs:Trunk biomass；Bb：Branch biomass；Bl：Leaf biomass；
2nd, urban forests vegetation index obtains：Pass through TM/ETM image remote sensing at the same time point for laying forest sample prescription
Image collection data source, carries out image cutting-out, geometric correction and atmospheric correction to data source, research is then extracted from data source
A variety of vegetation indexs in area, then carry out calculating inverting in ENVI 4.6, obtain the space number of urban forests vegetation index
According to, by city forest cover index in the position extraction forest sample prescription of each forest sample prescription, the data as structure model；
Wherein described vegetation index is ratio vegetation index SR, green normalized differential vegetation index GNDVI and normalization vegetation
Index NDVI；
3rd, build urban forests organic C storage scale and deduce model：The city in each forest sample prescription obtained according to step 1
A variety of vegetation indexs that city's forest carbon storage and step 2 obtain, it is each using correlation analysis first on forest sample size
The qualitative relationships between urban forests organic C storage in vegetation index and each forest sample prescription, the best vegetation index of correlation are true
It is set to optimal vegetation index, it is then gloomy using the optimal vegetation index of multiple regression quantitative analysis and the city in each forest sample prescription
Relation between woods organic C storage, structure obtain urban forests organic C storage scale and deduce model.
The present embodiment sets the urban forests sample prescription (Fig. 1) of 159 30m × 30m, and gloomy to city in 2012-2013
Woods organic C storage is investigated.Wherein 129 are used to build urban forests organic C storage estimation models, remaining is used to verify the model
Accuracy.
The present embodiment step 2 selects three kinds of vegetation indexs (normalized differential vegetation index, ratio vegetation index, greening normalization
Vegetation index) it is used for model construction, correlation analysis shows shown in following table：The correlation of normalized differential vegetation index and organic C storage is most
It is good, it is most suitable for structure organic C storage estimation models and obtains Fig. 2, wherein y=101.63e4.9201x, R2=0.613.Model verification shows：
The organic C storage precision of forecasting model of the present embodiment structure is good as shown in figure 3, wherein R2=0.904, RMSE=68.327, can answer
For in practice.
1. vegetation index of table and urban forests organic C storage correlation analysis
| Vegetation index | LAI |
| Normalized differential vegetation index (NDVI) | 0.613** |
| Ratio vegetation index (SR) | 0.586** |
| Green normalized differential vegetation index (GNDVI) | 0.534** |
The present embodiment deduces model using the urban forests organic C storage scale built, with reference to the landscape scale based on remote sensing
Upper optimal urban forests vegetation index, that is, NDVI obtains Fig. 4, so that it is empty clearly to study urban forests organic C storage in area's landscape scale
Between general layout see Fig. 5.
Claims (9)
1. a kind of urban forests organic C storage landscape scale deduction method, it is characterised in that this method carries out according to the following steps：
First, the field survey of urban forests organic C storage：In summer, using ArcGIS spatial analysis software in research area using layering
The mode of stochastical sampling carries out the laying of urban forests sample prescription, after the completion of the setting of forest sample prescription, using GPS system to each forest
The position of sample prescription is positioned, and then carries out every wooden dipping for the trees in sample prescription, calculates the urban forests in each sample prescription
Organic C storage, the urban forests organic C storage in sample prescription are the sum of individual organic C storage in sample prescription；
Individual organic C storage=0.5 × Individual Biomass wherein in sample prescription；Individual Biomass=0.8 × Bag；
Total strain biomass of each seeds is calculated by following different rate growth formula formula：
Pinus：Bag=Bs+Bb+Bl, wherein Bs=0.11*D2.34, Bb=0.01*D2.58, Bl=0.0049*D2.48；
Elm：Bag=Bs+Bb+Bl, wherein Bs=0.043*D2.87, Bb=0.007*D2.67, Bl=0.003*D2.50；
Picea：Bag=Bs+Bb+Bl, wherein Bs=0.06*D2.48, Bb=0.01*D2.41, Bl=0.0083*D2.37；
Willow：Bag=0.067*D2.558；
Acer：Bag=0.085*D2.535；
Ash field：Bag=0.137*D2.408；
Tilia：Bag=0.041*D2.668；
The rose family：Bag=0.216*D1.705；
Wherein Bag:Total strain biomass；Bs:Trunk biomass；Bb：Branch biomass；Bl：Leaf biomass；D：Tree breast-height diameter；
2nd, urban forests vegetation index obtains：Adopted in the same time for laying forest sample prescription by TM/ETM image remote sensing images
Collect data source, then a variety of vegetation indexs from data source in extraction research area, are then counted using remote sensing software ENVI
Inverting is calculated, obtains the spatial data of urban forests vegetation index, forest sample prescription inner city is extracted by the position of each forest sample prescription
City's forest cover index, the data as structure model；
Wherein described urban forests vegetation index is ratio vegetation index SR, green normalized differential vegetation index GNDVI and normalization
Vegetation index NDVI；
3rd, build urban forests organic C storage scale and deduce model：The city in each forest sample prescription obtained according to step 1 is gloomy
The urban forests vegetation index that woods organic C storage and step 2 obtain, it is each using correlation analysis first on forest sample size
The qualitative relationships between urban forests organic C storage in vegetation index and each forest sample prescription, the best vegetation index of correlation are true
It is set to optimal vegetation index, it is then gloomy using the optimal vegetation index of multiple regression quantitative analysis and the city in each forest sample prescription
Relation between woods organic C storage, structure obtain urban forests organic C storage scale and deduce model.
A kind of 2. urban forests organic C storage landscape scale deduction method according to claim 1, it is characterised in that step 1
Middle urban forests sample prescription, which lays place, includes road woods, attached woods, forest for landscape and recreation, production forest and ecological public welfare forests.
A kind of 3. urban forests organic C storage landscape scale deduction method according to claim 1, it is characterised in that step 1
Described in the area of forest sample prescription be 30m × 30m.
A kind of 4. urban forests organic C storage landscape scale deduction method according to claim 1, it is characterised in that step 1
Described in forest sample prescription quantity be more than 40.
A kind of 5. urban forests organic C storage landscape scale deduction method according to claim 1, it is characterised in that step 1
If some seeds does not have available different rate growth formula in, and use is belonged to together with it or the different rate growth formula of equal species.
A kind of 6. urban forests organic C storage landscape scale deduction method according to claim 5, it is characterised in that step 1
Belonged to together in if or the different rate growth formula of equal seeds still lacks, using general different rate growth formula, that is, Bag=
0.0881*D2.467。
A kind of 7. urban forests organic C storage landscape scale deduction method according to claim 1, it is characterised in that step 2
In by TM/ETM image remote sensing image gathered datas source, image cutting-out, geometric correction and atmospheric correction are carried out to data source.
A kind of 8. urban forests organic C storage landscape scale deduction method according to claim 1, it is characterised in that step 2
On the basis of TM remote sensing image band values, wave band calculating, and then inverting are carried out in remote sensing software ENVI using calculation formula
NDVI is obtained, SR, GNDVI vegetation indexs, corresponding calculation formula is NDVI=(b4-b3)/(b4+b3), SR=(b4/b3),
GNDVI=(b4-b2)/(b4+b2), wherein b2, b3 and b4 are respectively TM remote sensing images second band, the 3rd wave band and the 4th ripple
The band value of section.
9. a kind of urban forests organic C storage landscape scale deduction method according to claim 1, it is characterised in that according to step
Rapid three obtained urban forests organic C storage scales deduce models, with reference to optimal vegetation index in the landscape scale based on remote sensing, from
And clearly study urban forests organic C storage spatial framework in area's landscape scale.
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| CN115131370A (en) * | 2022-07-04 | 2022-09-30 | 东北林业大学 | Forest carbon sequestration and oxygen release capacity and benefit evaluation method and equipment |
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