CN109033459A - A kind of soil weight data space grid construction method - Google Patents
A kind of soil weight data space grid construction method Download PDFInfo
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- CN109033459A CN109033459A CN201811004198.5A CN201811004198A CN109033459A CN 109033459 A CN109033459 A CN 109033459A CN 201811004198 A CN201811004198 A CN 201811004198A CN 109033459 A CN109033459 A CN 109033459A
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Abstract
The invention discloses a kind of soil weight data space grid construction methods, comprising the following steps: soil profile investigation, sample acquisition and test data；Soil weight vertical section variability COEFFICIENT KSBDWith soil organic carbon vertical section variability COEFFICIENT KSOCRegression analysis；The building of stratified soil bulk density appraising model；The soil weight estimation and inspection of different soil；Grassland soil bulk density spatial grid calculation method；The analysis of grassland soil bulk density Features In Pattern of Spatial.The present invention has the advantages that realizing the spatial gridization estimation of the soil weight, solves the problems, such as the data reconstruction of soil vertical section layered volume weight；Using limited data or index, quickly and easily inverting and the soil weight spatial data of grassland soil vertical demixing and horizontal distribution is obtained, method is simple, saves time, energy and financial resources；Precision and reliability with higher provide effective ways and data basis for the data building of soil attribute.
Description
Technical field
The present invention relates to soil weight spatial grid constructing technology field, in particular to a kind of soil weight vertically cuts open
The space construction process of face individual-layer data.
Background technique
The soil component part important as terrestrial ecosystems, is the important foundation that vegetation depends on for existence, physics and chemistry
Matter not only influences the growth of plant, also restricts the productivity level of plant.Bulk density is the important basic physical property of soil,
The characteristics such as the gas permeability of soil, infiltrating property, retentiveness, solute migration and soil resistance to corrosion are had an important influence.Soil
Bulk density not only can be with ecological functions such as the retentiveness of quantitatively characterizing soil, infiltrating property, corrosion resistance, gas permeabilities, and measure
One of the important indicator of soil environment quality.By changing soil hardness, soil weight variation is influenced, and then influence plant
Growth；With the raising of bulk density, soil hardness is increased with it, and root elongation speed slows down in soil, and root system shorten it is thicker.
By changing bulk density, the arrangement of soil solid particle is different, causes different zigzag channels, influences nutrient in the soil
Diffusion is changed with the change of bulk density by the intracorporal charge density of unit soil, and then influences diffusion coefficient.Pass through the soil weight
Variation, adjust soil environment in water, heat, the situation of gas, fertilizer, and then influence vegetation growth state.Pass through the soil weight
Variation, while indicating assessing index, also implies the feature representation of grassland degeneration situation.In addition, in region ruler
On degree, the soil weight is important necessary to the required argument of storage capacity of soil water estimation, and accurate estimation SOIL CARBON AND NITROGEN reserves
Parameter.So establishing the soil weight space-time data of holonomic system, China's agrology basic research, ecological environment are commented
Valence and Soil quality monitoring have important practical significance.
The soil weight refers to the soil quality (or weight) of unit volume under soil column state.International standardization at present
The method of sampling of the soil weight of organization prescribed has 3 kinds: core cutter method, slab method and soil block method, core cutter method are most common sides
Method.The industry standard methods (NY/T 1121.4~2006) that the Ministry of Agriculture issues the measurement of the soil weight, the Chinese Academy of Sciences
Guide's special project project, which formulates soil weight sampling, specific working specification " Chinese Grassland ecosystem carbon sequestration status, speed
Rate and potentiality research specification ".However, all soil weight method of samplings must be established before deep-cutting soil profile
It puts, the undisturbed soil sample of soil could be acquired, carry out the measurement of the soil weight.This operation is time-consuming, and in field large scale reality
It is heavy that there are work in, and human and material resources expend the problems such as larger, and the sampling point and data volume of soil weight measurement are limited
System.So more researchs are conducted a research for the bulk density of topsoil.Available more samples on regional space
Point and data.Meanwhile in recent years, using limited soil weight determination data, transmission function prediction model is established, soil is utilized
Earth other attributes predict the soil weight, and obtain good effect, are such as contained based on sticking grain and powder volume fraction, organic carbon
Amount, the gradient and its shifting combination establish transmission function prediction model, and to loess plateau region scale topsoil bulk density
It is simulated, soil weight prediction model is as simple, fast soil weight acquisition methods, more and more by state
The concern and application of inside and outside scholar.However, its research does not consider the influence that soil depth simulates the soil weight.
Summary of the invention
The present invention in view of the drawbacks of the prior art, provides a kind of soil weight data space grid construction method, structure
The transmission function prediction model for building horizontal space and vertical section carries out soil and hangs down using the existing finite data easily obtained
The soil weight data estimation of straight section layered volume weight data reconstruction and horizontal space grid, inverting northern China grassland region soil
The soil weight data of earth bulk density vertical section and horizontal space provide clothes for agrology basic research and soil regime evaluation
Business.
In order to realize the above goal of the invention, the technical solution adopted by the present invention is as follows:
A kind of soil weight data space grid construction method, comprising the following steps:
The investigation of step 1. soil profile, sample acquisition and test data；
According to " Chinese Grassland ecosystem carbon sequestration status, rate and potentiality research specification ", according to specification, not
The investigation and sampling on meadow sample ground, including Grassland Communities investigation and soil investigation and sampling are carried out with area, by 0-5cm, 5-
10cm, 10-20cm, 20-30cm, 30-50cm layering acquisition soil weight and soil physical analysis sample.Soil physical analysis
Sample carries out the analysis of full carbon, inorganic carbon, organic carbon, full nitrogen, content of tatal phosphorus, and according to the soil of different soil test analysis
The data of bulk density and soil organic carbon are acquired soil organic carbon and are hung down with what soil layer changed by linear regression analysis
Straight section variability COEFFICIENT KSOCThe vertical section variability COEFFICIENT K changed with the soil weight with soil layerSBD。
Step 2. soil weight vertical section variability COEFFICIENT KSBDWith soil organic carbon vertical section variability COEFFICIENT KSOC
Regression analysis；
According to soil organic carbon vertical section variability COEFFICIENT KSOCData and soil weight vertical section variability coefficient
KSBDData carry out linear regression analysis, acquire soil layering changing bulk density with the transmitting of soil organic carbon layering variation
Functional equation: y=-0.056x+0.0254.
The building of step 3. stratified soil bulk density appraising model；
According to the transmission function equation of the resulting soil weight vertical section variation of step 2, the soil of different soil is constructed
The appraising model that bulk density changes with soil organic carbon layering:
SBD(x)=SBD(0)(1+KSBD* x) (x=0,1,2,3) ... ... ... (1)
KSBD=-0.056*KSOC+0.0254……………………….(2)
SBD(x)It is the soil weight of upper soll layer 0-10cm as x=0 for the soil weight value of x soil layer, when x=1 is
The soil weight value of soil 10-20cm soil layer；It is the soil weight value of soil 20-30cm soil layer when x=2；It is soil when x=3
The soil weight value of 30-50cm soil layer；SBD(0)For the value of bulk density of upper soll layer 0-10cm；KSBDIt hangs down for the soil on certain meadow sample ground
Straight section variability coefficient, the vertical section variability COEFFICIENT K with soil organic carbonSOCIt is related.
The soil weight estimation and inspection of step 4. different soil
According to formula (1) and formula (2), simulation estimate meadow sample ground 0-10cm, 10-20cm, 20-30cm, 30- again
The soil weight value of 50cm different soil.According to average forecasting error MPE, root-mean-square deviation RMSPE and coefficient of multiple correlation R2To soil
The precision of prediction of the transmission function of earth bulk density vertical section variation is tested.Inspection result shows: being contained using soil organic matter
The vertical section variability COEFFICIENT K of amountSOCTo predict that estimation different soil soil weight value has very high reliability and precision.
Step 5. grassland soil bulk density spatial grid calculation method, the steps include:
5.1 grassland soil surface layer (0-10cm) soil weight SBD(0)The preparation of space lattice data；
According to the survey data of the topsoil bulk density of meadow investigation, using multi-data source inverting interpolation method, inverting is inserted
It is worth meadow surface layer 0-10cm soil weight space lattice data out.
5.2 grassland soil organic carbon content vertical section variability COEFFICIENT KsSOCThe preparation of space lattice data；
According to the data of the soil layering organic carbon content of meadow investigation, using linear regression analysis, with obtaining corresponding sample
The vertical section variability COEFFICIENT K that changes with soil depth of organic carbon contentSOC, and multi-data source inverting interpolation method is used,
Inverting interpolation goes out grassland soil organic carbon content vertical section variability COEFFICIENT KSOCSpace lattice data.
The spatial gridization of the 5.3 meadow different soil soil weight calculates；
The different soil soil weight constructed according to step 3 is estimated with the transmission function of soil organic carbon layering variation
Calculate model, in ArcGis platform, upper soll layer soil weight SBD in load step 5.1(0)Space lattice data and step
Soil organic carbon vertical section variability COEFFICIENT K in 5.2SOCSpace lattice data.Open " Spatial in ArctoolBox
" map algebra "-" raster symbol-base device " tool of Analyst " substitutes into formula (1) and formula (2) in raster symbol-base device,
Interpolation is finally inversed by the soil weight space lattice data of different soil respectively.
It is the soil weight data of upper soll layer 0-10cm as x=0；
It is the soil weight data of soil 10-20cm soil layer as x=1；
It is the soil weight data of soil 20-30cm soil layer as x=2；
It is the soil weight data of soil 30-50cm soil layer as x=3.
The analysis of step 6. grassland soil bulk density Features In Pattern of Spatial；
According to the soil for meadow 0-10cm, 10-20cm, 20-30cm, 30-50cm soil layer that step 5 inverting interpolation obtains
It is empty to statistically analyze the different geographic regions soil weight using the statistical and analytical tool in ArcGis for the space lattice data of bulk density
Between Distribution Pattern feature and soil weight vertical section heterogeneous variation features.
Compared with prior art the present invention has the advantages that realizing the spatial gridization estimation of the soil weight, and realize
The data reconstruction of soil vertical section layered volume weight；Meanwhile utilizing the data or index relatively easily obtained, building transmitting
Functional equation estimates simultaneously inverting meadow stratified soil bulk density data, and method is simple, saves time, energy and financial resources；Method tool
There are higher precision and reliability, provides effective ways and data basis for the data building of soil attribute.
Detailed description of the invention
Fig. 1 is the soil weight of embodiment of the present invention vertical section variability coefficient (KSBD) and the full carbon content vertical section of soil
Variability coefficient (KSOC) correlation regressive trend figure；
Fig. 2 is different soil of embodiment of the present invention soil weight predicted value and measured value comparison schematic diagram；
Fig. 3 is the north of the embodiment of the present invention temperate grassland area meadow surface layer (0-10cm) soil weight spatial distribution map；
Fig. 4 is the north of embodiment of the present invention temperate grassland area grassland soil organic carbon content vertical section variability coefficient
(KSOC) spatial distribution map；
Fig. 5 is the north of embodiment of the present invention temperate grassland area meadow 0-10cm soil layer soil weight spatial distribution map；
Fig. 6 is the north of embodiment of the present invention temperate grassland area meadow 10-20cm soil layer soil weight spatial distribution map；
Fig. 7 is the north of embodiment of the present invention temperate grassland area meadow 20-30cm soil layer soil weight spatial distribution map；
Fig. 8 is the north of embodiment of the present invention temperate grassland area meadow 30-50cm soil layer soil weight spatial distribution map.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention more comprehensible, it is exemplified below embodiment, to the present invention
It is described in further details.
A kind of soil weight data space grid construction method, comprising the following steps:
The investigation of step 1. soil profile, sample acquisition and test data
This seminar assumes responsibility for the sample-plot survey of special " Guangxi-Hainan-Jiangxi-Anhui " special topic of Chinese Academy of Sciences guide.
According to " Chinese Grassland ecosystem carbon sequestration status, rate and potentiality research specification ", in Guangxi, Hainan, Jiangxi and Anhui
Four provinces and regions have carried out Grassland Communities investigation, soil investigation and the sampling on 143 meadows sample ground.Wherein with the sample of complete section
117, ground, 5 repetitions (corresponding with sample prescription) in each sample ground, by 0-5cm, 5-10cm, 10-20cm, 20-30cm, 30-50cm
The layering acquisition soil weight and soil physical analysis sample.Soil physical analysis sample send plant analysis center of institute of the Chinese Academy of Sciences into
The analysis of row full carbon, inorganic carbon, organic carbon, full nitrogen, content of tatal phosphorus.Soil layering organic carbon content analysis data are shown in Table 1, soil
Earth layered volume weight experimental data is shown in Table 2.
- Anhui-, 1 Guangxi of table-Hainan Grassland in Jiangxi Province sample ground organic carbon content data
*KSOCFor the variability coefficient that soil organic carbon changes with soil depth, obtained by linear regression.
- Anhui-, 2 Guangxi of table-Hainan Grassland in Jiangxi Province sample ground soil weight data
*KSBDFor the variability coefficient that the soil weight changes with soil depth, obtained by linear regression.
Step 2. soil weight vertical section variability coefficient (KSBD) and soil organic carbon vertical section variability coefficient
(KSOC) regression analysis, as shown in Figure 1；
According to the soil organic carbon vertical section variability coefficient (K of table 1SOC) data and table 2 the soil weight it is vertical
Section variability coefficient (KSBD) data, linear regression analysis is carried out, acquires soil layering changing bulk density with soil organic carbon
It is layered the transmission function equation of variation:
Y=-0.056x+0.0254.
The building of step 3. soil weight appraising model
According to the transmission function equation of the resulting soil weight vertical section variation of step 2, different soil can be constructed
The appraising model that the soil weight changes with soil organic carbon layering:
SBD(x)=SBD(0)(1+KSBD* x) (x=0,1,2,3) ... ... (1)
KSBD=-0.056*KSOC+0.0254……………………(2)
SBD(x)It is the soil weight of upper soll layer (0-10cm) as x=0 for the soil weight value of x soil layer, when x=1
For the soil weight value of soil 10-20cm soil layer；It is the soil weight value of soil 20-30cm soil layer when x=2；It is soil when x=3
The soil weight value of earth 30-50cm soil layer； SBD(0)For the value of bulk density of upper soll layer；KSBDFor the soil vertical on certain meadow sample ground
Section variability coefficient, the vertical section variability coefficient (K with soil organic carbonSOC) related (formula 2).
The estimation and inspection of the step 4. different soil soil weight
It, can 117 meadows such as simulation estimate Guangxi-Hainan-Jiangxi-Anhui again according to formula (1) and formula (2)
Sample the different soils such as 0-10cm, 10-20cm, 20-30cm, 30-50cm soil weight value.The soil of its simulation estimate holds
The comparison result of weight values and measured value is shown in Fig. 2.According to average forecasting error (MPE), root-mean-square deviation (RMSPE) and complex phase relationship
Number (R2) test to the precision of prediction of the transmission function of soil weight vertical section variation, the results showed that have using soil
Machine carbon content vertical section variability coefficient (KSOC) come predict estimation different soil soil weight value have very high reliability and
Precision.
3 soil weight predicted value of table and measured value precision of prediction are examined
| Soil layering | MPE | RMSPE | R2 |
| 0-10cm | 0.00 | 0.00 | 1.00 |
| 10-20cm | 0.022 | 0.104 | 0.617 |
| 20-30cm | 0.001 | 0.118 | 0.513 |
| 30-50cm | -0.027 | 0.124 | 0.469 |
Step 5. north temperate grassland area's grassland soil bulk density space delamination Data gridization calculates
Show to establish stratified soil using soil organic carbon vertical section variability coefficient from the check analysis of step 4
The transfer function model of bulk density estimation, estimates the soil weight data of different soils depth, is a kind of reliable evaluation method.
The present invention, to the survey data in northern temperate grassland area, is layered northern China temperate grassland area's different soils using seminar
Bulk density carry out spatial grid inverting and estimation.Its method and step are as follows:
5.1 northern temperate grassland area grassland soil topsoil bulk density SBD(0)The preparation of space lattice data
According to the tune of the topsoil bulk density on 576 meadows investigation sample ground of northern temperate grassland area grassland degeneration investigation
Data are looked into, using multi-data source inverting interpolation method, inverting interpolation goes out northern China temperate grassland area meadow surface layer (0-10cm)
Soil weight space lattice data (as shown in Fig. 3,1km × 1km).
5.2 northern temperate grassland area grassland soil organic carbon content vertical section variability coefficient (KSOC) space lattice data
Preparation
Equally, having according to the soil layering on 576 meadows investigation sample ground of northern temperate grassland area grassland degeneration investigation
The survey data of machine carbon content obtains what the organic carbon content on corresponding sample ground changed with soil depth using linear regression analysis
Slope variation coefficient (KSOC), and multi-data source inverting interpolation method is used, inverting interpolation goes out northern China temperate grassland area grass
Oblique variability (the K of ground soil organic carbon vertical sectionSOC) space lattice data (as shown in figure 4,1km × 1km).
The spatial gridization of the 5.3 northern temperate grassland area meadow different soil soil weight calculates
The transmission function that the soil weight of the different soil constructed according to step 3 changes with soil organic carbon layering
Appraising model loads northern temperate grassland area grassland soil topsoil bulk density SBD in ArcGis platform(0)Space lattice
Data (data of step 5.1) and northern temperate grassland area grassland soil organic carbon content vertical section variability coefficient (KSOC) empty
Between raster data (data of step 5.2).Open " map algebra "-of " Spatial Analyst " in ArctoolBox
" raster symbol-base device " tool substitutes into formula (1) and formula (2) in raster symbol-base device, and interpolation is finally inversed by different soil respectively
Soil weight spatial distribution data (1km × 1km).
It is the soil weight data of upper soll layer 0-10cm (with upper soll layer soil weight SBD as x=0(0)Space
Raster data is identical) (Fig. 5)；
It is the soil weight data (Fig. 6) of soil 10-20cm soil layer as x=1；
It is the soil weight data (Fig. 7) of soil 20-30cm soil layer as x=2；
It is the soil weight data (Fig. 8) of soil 30-50cm soil layer as x=3.
The temperate grassland area's grassland soil bulk density Features In Pattern of Spatial analysis of step 6. north
According to step 5 inverting interpolation obtain northern China temperate grassland area meadow 0-10cm, 10-20cm, 20-30cm,
The space lattice data (Fig. 5-8) of the soil weight of the soil layers such as 30-50cm can be with using the statistical and analytical tool in ArcGis
The heterogeneous variation for statisticalling analyze different geographic regions soil weight Spatial Distribution Pattern feature and soil weight vertical section is special
Sign.
According to soil layers such as the northern China temperate grassland area Fig. 5-8 meadow 0-10cm, 10-20cm, 20-30cm, 30-50cm
The soil weight space lattice data, carry out data statistic analysis show: northern China temperate grassland area grassland vegetation it is total
Body is averaged the soil weight as 1.47g/cm3, wherein the average soil of 0-10cm, 10-20cm, 20-30cm, 30-50cm soil layer holds
It is again respectively 1.39g/cm3、1.44g/cm3、1.50g/cm3、1.55g/cm3。
4 different soils bulk density distribution area proportion of table
According to the statistical analysis of table 4, the soil weight on northern China temperate grassland area meadow is mainly distributed on 1.5g/cm3
More than, account for about 60% or more of total grassland area, the soil weight is in 0.8g/cm3Meadow below accounts for 5% less than the soil weight
In 0.8-1.5g/cm3Meadow account for about 35% or so.And with the increase of soil depth, high bulk density (1.5g/cm3More than)
Meadow proportion have increase trend, 30-50cm soil layer soil weight 1.5g/cm3Above meadow accounts for about the gross area
70%；And low bulk density (0.8g/cm3Meadow proportion below) is reduced trend, is reduced to 3% or so from 6% or so.
(table 5) is analyzed from regional distribution, northern China temperate grassland area meadow is averaged the soil weight as 1.47g/
cm3, wherein the Tianshan Mountainous soil weight is minimum, volume-weighted average 1.07g/cm3, surface layer bulk density average out to 0.99g/cm3；Secondly
For Altay mountain area, volume-weighted average 1.11g/cm3, surface layer bulk density average out to 1.04g/cm3；Third is Pamir-Kun Lun Mountain-
Altun highlands, volume-weighted average 1.12g/cm3, surface layer bulk density average out to 1.04g/cm3.The meadow in South Sinkiang basin
Soil weight highest, volume-weighted average 1.91g/cm3, surface layer bulk density average out to 1.85g/cm3；It secondly is Alxa Plateau and river
The meadow in set and the silent river Plain of soil, volume-weighted average is all 1.84g/cm3, surface layer bulk density is respectively 1.76g/cm3；Third is North SinKiang
Junggar Basin meadow, volume-weighted average are respectively 1.71g/cm3, surface layer bulk density is respectively 1.63g/cm3。
The 5 different geographic regions soil weight of table statistical analysis
Those of ordinary skill in the art will understand that the embodiments described herein, which is to help reader, understands this
The implementation method of invention, it should be understood that protection scope of the present invention is not limited to such specific embodiments and embodiments.This
The those of ordinary skill in field disclosed the technical disclosures can make according to the present invention and various not depart from essence of the invention
Various other specific variations and combinations, these variations and combinations are still within the scope of the present invention.
Claims (4)
1. a kind of soil weight data space grid construction method, which comprises the following steps:
The investigation of step 1. soil profile, sample acquisition and test data；
According to " Chinese Grassland ecosystem carbon sequestration status, rate and potentiality research specification ", according to specification, in different regions
The investigation and sampling on meadow sample ground, including Grassland Communities investigation and soil investigation and sampling are carried out, by 0-5cm, 5-10cm, 10-
20cm, 20-30cm, 30-50cm layering acquisition soil weight and soil physical analysis sample；Soil physical analysis sample carries out complete
The analysis of carbon, inorganic carbon, organic carbon, full nitrogen, content of tatal phosphorus, and had according to the soil weight and soil of different soil test analysis
The data of machine carbon content acquire the vertical section variability system that soil organic carbon changes with soil layer by linear regression analysis
Number KSOCThe vertical section variability COEFFICIENT K changed with the soil weight with soil layerSBD；
Step 2. soil weight vertical section variability COEFFICIENT KSBDWith soil organic carbon vertical section variability COEFFICIENT KSOCIt returns
Analysis；
According to soil organic carbon vertical section variability COEFFICIENT KSOCData and soil weight vertical section variability COEFFICIENT KSBDNumber
According to progress linear regression analysis acquires soil layering changing bulk density with the transmission function side of soil organic carbon layering variation
Journey: y=-0.056x+0.0254；
The building of step 3. stratified soil bulk density appraising model；
According to the transmission function equation of the resulting soil weight vertical section variation of step 2, the soil weight of different soil is constructed
With the appraising model of soil organic carbon layering variation:
SBD(x)=SBD(0)(1+KSBD* x) (x=0,1,2,3) ... ... (1)
KSBD=-0.056*KSOC+0.0254………………………(2)
SBD(x)It is the soil weight of upper soll layer 0-10cm as x=0 for the soil weight value of x soil layer, is soil when x=1
The soil weight value of 10-20cm soil layer；It is the soil weight value of soil 20-30cm soil layer when x=2；It is soil 30- when x=3
The soil weight value of 50cm soil layer；SBD(0)For the value of bulk density of upper soll layer 0-10cm；KSBDFor the soil vertical on certain meadow sample ground
Section variability coefficient, the vertical section variability COEFFICIENT K with soil organic carbonSOCIt is related；
The soil weight estimation and inspection of step 4. different soil；
According to formula (1) and formula (2), again simulation estimate meadow sample 0-10cm, 10-20cm, 20-30cm, 30-50cm not
With the soil weight value of soil layer；According to average forecasting error MPE, root-mean-square deviation RMSPE and coefficient of multiple correlation R2To the soil weight
The precision of prediction of the transmission function of vertical section variation is tested；Inspection result shows: utilizing hanging down for soil organic carbon
Straight section variability COEFFICIENT KSOCTo predict that estimation different soil soil weight value has very high reliability and precision；
Step 5. grassland soil bulk density spatial grid calculation method, the steps include:
5.1 grassland soil surface layer 0-10cm soil weight SBD(0)The preparation of space lattice data；
5.2 grassland soil organic carbon content vertical section variability COEFFICIENT KsSOCThe preparation of space lattice data；
The spatial gridization of the 5.3 meadow different soil soil weight calculates；
It is the soil weight data of upper soll layer 0-10cm as x=0；
It is the soil weight data of soil 10-20cm soil layer as x=1；
It is the soil weight data of soil 20-30cm soil layer as x=2；
It is the soil weight data of soil 30-50cm soil layer as x=3；
The analysis of step 6. grassland soil bulk density Features In Pattern of Spatial；
According to the soil weight of meadow 0-10cm, 10-20cm, 20-30cm, 30-50cm soil layer of step 5 inverting interpolation acquisition
Space lattice data statistically analyze different geographic regions soil weight spatial distribution using the statistical and analytical tool in ArcGis
The heterogeneous variation features of pattern feature and soil weight vertical section.
2. according to the method described in claim 1, it is characterized by: the step 5.1 is specially the surface layer investigated according to meadow
The survey data of the soil weight, using multi-data source inverting interpolation method, inverting interpolation goes out the meadow surface layer 0-10cm soil weight
Space lattice data.
3. according to the method described in claim 2, it is characterized by: the step 5.2 is specially the soil investigated according to meadow
The survey data of layering organic carbon content obtains the organic carbon content on corresponding sample ground with soil depth using linear regression analysis
The vertical section variability COEFFICIENT K of variationSOC, and multi-data source inverting interpolation method is used, inverting interpolation goes out grassland soil organic carbon
Content vertical section variability COEFFICIENT KSOCSpace lattice data.
4. according to the method described in claim 3, it is characterized by: according to the method described in claim 1, it is characterized by:
The step 5.1 is specially the biography that the different soil soil weight constructed according to step 3 changes with soil organic carbon layering
Delivery function appraising model, in ArcGis platform, upper soll layer soil weight SBD in load step 5.2(0)Space lattice data
With soil organic carbon vertical section variability COEFFICIENT K in step 5.2SOCSpace lattice data；It opens in ArctoolBox
Formula (1) and formula (2) are substituted into grid meter by " map algebra "-" raster symbol-base device " tool of " Spatial Analyst "
It calculates in device, interpolation is finally inversed by the soil weight space lattice data of different soil respectively.
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| CN109856368A (en) * | 2019-03-28 | 2019-06-07 | 中国科学院地球环境研究所 | A kind of method that period of history soil erosion carbon storehouse number of dropouts calculates |
| CN112986058A (en) * | 2021-02-02 | 2021-06-18 | 贵州省烟草科学研究院 | Visual analysis method for migration rule of fertilizer nutrients in soil |
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| CN112986058A (en) * | 2021-02-02 | 2021-06-18 | 贵州省烟草科学研究院 | Visual analysis method for migration rule of fertilizer nutrients in soil |
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