CN102184162A - Method for remotely sensing and quantitatively monitoring steppe vegetation coverage space-time dynamic change - Google Patents

Abstract

The invention relates to a method for remotely sensing and quantitatively monitoring steppe vegetation coverage space-time dynamic change based on normalized difference vegetation index (NDVI) data, and belongs to the technical field of vegetation coverage dynamic remote sensing and monitoring. In order to solve the problem that the quantitative research on remote sensing and monitoring of steppe vegetation coverage dynamic change is rare, the quantitative monitoring method provided by the invention comprises the following steps of: calculating to obtain six NDVI indexes, such as an NDVI yearly value, a yearly maximum value, a yearly minimum value, a yearly maximum value appearance date, a yearly minimum value appearance date and a season dynamic, which represent a steppe vegetation coverage situation, by using an NDVI time sequence file; and quantitatively monitoring a space-time dynamic change process, a phenological characteristic and a dynamic change tendency of steppe vegetation coverage by calculating a yearly dynamic change rate of the NDVI indexes within a certain time period and performing trend analysis by a Mann-Kendall method. The method is applicable to all vegetation NDVI data.

Description

Steppe vegetation covers the remote sensing Quantitative Monitoring method that space-time dynamic changes

Technical field

The present invention relates to vegetation and cover the dynamic remote monitoring technical field, particularly relate to a kind of steppe vegetation and cover the remote sensing Quantitative Monitoring method that space-time dynamic changes based on vegetation NDVI data.

Background technology

Vegetation is the most outstanding soil cover type of top; have a distinct seasonal variation and a year border variation characteristic; its change in time and space has significant effects in the biochemical cycle of global energy circulation and material; the variation research that vegetation covers all is widely used in fields such as ecologic environment investigation, research soil and water conservation, evapotranspiration researchs; simultaneously; carrying out vegetation space-time and develop dynamic monitoring and evaluation, is the important foundation of assessment ecological protection measure, environmental management policy and global change research due.In recent years; along with Global climate change and interference from human factor; the grassland desertification of northern China, grassland degeneration phenomenon are serious; utilize remote sensing means monitoring steppe vegetation space-time dynamic variation characteristic; understanding steppe vegetation Changing Pattern is for the protection of the steppe vegetation ecosystem and administer significant.

Remote sensing technology as a kind of technological means for a long time sequence, obtain the ground vegetation coverage information on a large scale.Wherein, normalized differential vegetation index (Normalized DifferenceVegetation Index, NDVI) be to use more a kind of vegetation at present to cover the condition monitoring index, it has eliminated the influence to index such as most of atmosphere, instrument calibration and landform, has strengthened the responding ability to vegetation.After deliberation, vegetation NDVI data and vegetation cover has very high positive correlation, the NDVI value is big more, vegetation covers high more, therefore, vegetation NDVI data can reflect the covering situation of steppe vegetation to a certain extent, by the dynamic change of research vegetation NDVI data, and then realize the space-time dynamic research that vegetation covers.

And the at present domestic vegetation NDVI data monitoring steppe vegetation covering space-time dynamic of utilizing changes the main NDVI of analysis mean variation situation, and do not set up the method for quantitatively evaluating of many indexs, this respect research is still also limited, can not support the research of steppe vegetation dynamic change characterization comprehensively, deeply, quantitatively; And it is less to carry out the monitoring of steppe vegetation covering space-time dynamic change indicator abroad, and research lacks systematicness, fails to be used well.

Summary of the invention

(1) technical matters that will solve

The technical problem to be solved in the present invention is how to improve to utilize vegetation NDVI data to carry out the validity that steppe vegetation covers space-time dynamic variation research, overcome the deficiency of quantitative examination of the prior art, form steppe vegetation Cover Change remote sensing Quantitative Monitoring method based on vegetation NDVI data.

(2) technical scheme

In order to solve the problems of the technologies described above, this patent provides a kind of steppe vegetation to cover the remote sensing Quantitative Monitoring method that space-time dynamic changes, and described method comprises the steps:

Step S1: the initial time that preestablishes the statistics time covers the time range that space-time dynamic changes as the Quantitative Monitoring steppe vegetation;

Step S2: utilize the normalized differential vegetation index NDVI data creating of vegetation to preset NDVI sequential file annual in the statistics time, eliminate the noise of NDVI sequential file then;

Step S3: in the sequential NDVI file after described elimination noise, calculate in the vegetation NDVI data and cover several indexs that space-time dynamic changes about steppe vegetation;

Step S4: calculate described each leisure of several indexs respectively and preset statistics year in one's duty year border dynamic change rate;

Step S5: presetting in the statistics time, according to the Mann-Kendall method described several indexs are carried out trend analysis, obtain each index and presetting statistics year in one's duty statistical test value, obtain each index and presetting statistics year in one's duty dynamic change trend;

Step S6: presetting year in one's duty year border dynamic change rate of statistics and statistical test value, the dynamic change trend of coming the quantitative examination steppe vegetation to cover based on described several indexs.

Among the described step S2, utilize the remote sensing image handling implement to handle vegetation NDVI data, generate and preset NDVI sequential file annual in the statistics time; At NDVI sequential file noise place, utilize averaging method then, promptly calculate the mean value of its front and back vegetation NDVI data and replace noise figure, eliminate noise with this mean value.

Among the described step S3,

Described several indexs comprise: the dynamic value RREL in season of date DMIN and vegetation NDVI data appears in the year minimum value that date DMAX, vegetation NDVI data appear in the year maximal value of the year maximal value MAX of the annual mean AVE of vegetation NDVI data, vegetation NDVI data, the year minimum value MIN of vegetation NDVI data, vegetation NDVI data;

Wherein,

The annual mean AVE of described vegetation NDVI data represents the long-run average that annual steppe vegetation covers;

On behalf of steppe vegetation, the year maximal value MAX of described vegetation NDVI data and the year minimum value MIN of vegetation NDVI data cover the highest and minimum situation;

The year minimum value that date DMAX and vegetation NDVI data appear in the year maximal value of described vegetation NDVI data occur date DMIN with ten days numerical table show, represent vegetation to cover mxm. and pairing date of minimum respectively;

Described NDVI dynamic value in season RREL represents the year border changing condition of vegetation, and its computing formula is:

RREL＝[DMAX-DMIN]/[AVE]。

Among the described step S4,

The year maximal value MAX of the annual mean AVE of described vegetation NDVI data, described vegetation NDVI data, described vegetation NDVI data year minimum value MIN and described vegetation NDVI data season dynamic value RREL year border dynamic change rate with coefficient of variation CV _tRepresent;

The year minimum value that date DMAX and described vegetation NDVI data appear in the year maximal value of described vegetation NDVI data the year border dynamic change rate of date DMIN occurs with standard deviation SD _tRepresent;

Wherein, CV _tWith SD _tComputing formula be respectively:

${\mathrm{SD}}_t=\sqrt{\frac{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}(x_i-\stackrel{\‾}{x})}{n-1}};$

${\mathrm{CV}}_t=\frac{{\mathrm{SD}}_t}{\stackrel{\‾}{x}};$

Wherein, n is the in one's duty annual quantity of statistics year that presets among the step S1, x _iBe respectively described each index at each annual numerical value, i=1,2,3...n,

Be respectively described each index and presetting statistics year in one's duty mean value.

Among the described step S5, specifically comprise the steps:

Step 501: presetting degree of confidence is 95%, the level of signifiance α of trend test=0.05;

Step 502: utilize following formula to calculate each index and presetting statistics year in one's duty statistics S:

$S=\underset{k=1}{\overset{n-1}{\mathrm{\Σ}}}\underset{j=k+1}{\overset{n}{\mathrm{\Σ}}}\mathrm{sgn}(x_j-x_k);$

Wherein, x _jAnd x _kBe respectively the numerical value of each index at j and k, j＞k, n are the in one's duty annual quantity of statistics year that presets among the step S1; And,

Step 503: utilize following formula to obtain each index and presetting average E (S) and the variance Var (S) that adds up year in one's duty statistics S:

E(S)＝0；

$\mathrm{Var}\left(S\right)=\frac{n(n-1)(2n+5)}{18};$

Step 504: utilize following formula to calculate each index and presetting statistics year in one's duty statistical test value Z _S:

$Z_S=\left\{\begin{array}{cc}\frac{S-1}{\mathrm{Var}\left(S\right)}& S>0;\\ 0& S=0;\\ \frac{S+1}{\mathrm{Var}\left(S\right)}& S<0.\end{array}\right.$

Among the described step S6, the process of the space-time dynamic variation tendency that the quantitative examination steppe vegetation covers specifically comprises the steps:

Step S601: judge described statistical test value Z _SThe trend significant change;

Step S602: if Z _SBe positive number, and Z _S＞Z _1-α/2, show that then steppe vegetation is coated with significant ascendant trend, if Zs is a negative, and Z _S＞Z _1-α/2, show that then steppe vegetation is coated with significant downtrending, if | Z _S|≤Z _1-α/2, show that then steppe vegetation covers no change trend.

(3) beneficial effect

Technique scheme is by carrying out quantitative examination to several indexs that change about steppe vegetation covering space-time dynamic in several vegetation NDVI data, thereby can realize quantitative examination to the steppe vegetation Cover Change, truly reflect dynamic change situation, phenology feature and the variation tendency that steppe vegetation covers in the regular period, remedy the deficiency of current qualitative examination.

Description of drawings

Fig. 1 is the process flow diagram that the related steppe vegetation of the specific embodiment of the invention covers the remote sensing Quantitative Monitoring method of space-time dynamic variation;

Fig. 2 is the block diagram that the related steppe vegetation of the specific embodiment of the invention covers the data flow in the remote sensing Quantitative Monitoring method that space-time dynamic changes;

Fig. 3-1 and Fig. 3-2 is that the related steppe vegetation of the specific embodiment of the invention covers each the NDVI index year border dynamic change rate synoptic diagram in the remote sensing Quantitative Monitoring method that space-time dynamic changes;

Fig. 4-1 covers in the remote sensing Quantitative Monitoring method that space-time dynamic changes the (result schematic diagram that the method for Man-Ken Deer) is carried out trend analysis to each NDVI index by Mann-Kendall for the related steppe vegetation of the specific embodiment of the invention to Fig. 4-6.

Embodiment

For making purpose of the present invention, content and advantage clearer,, the specific embodiment of the present invention is described in further detail below in conjunction with drawings and Examples.

The related steppe vegetation of the specific embodiment of the invention covers the remote sensing Quantitative Monitoring method that space-time dynamic changes, and as shown in Figures 1 and 2, comprises the steps:

Step S1: the initial time that preestablishes the statistics time covers the time range that space-time dynamic changes as the Quantitative Monitoring steppe vegetation;

Step S2: SPOT_VGT vegetation NDVI data or other NVDI data of utilizing steppe vegetation to cover are made the NDVI sequential file that presets every year in the statistics time, eliminate the noise of NDVI sequential file then; Be specially: utilize the remote sensing image handling implement to handle vegetation NDVI data, generate and preset NDVI sequential file annual in the statistics time; At NDVI sequential file noise place, utilize averaging method then, promptly calculate the mean value of its front and back vegetation NDVI data and replace noise figure, eliminate noise with this mean value.

Selected vegetation NDVI data are to cover space-time dynamic with steppe vegetation to change remote sensing monitoring be purpose among above-mentioned steps S1 and the step S2, what obtain is Hulunbuir Pasture Land 1998 to 2008 data in totally 11 years, on this basis, according to administrative division, the steppe vegetation space-time dynamic changing condition of each city such as the Xinbaerhu Right Banner in research area, Hulun Buir, Xinbaerhu Left Banner, Manzhouli, Chenbarhu Banner, Hailaer, Ergun City, Yakeshi City, Ewenki automonous banner, flag.

Step S3: in through the sequential NDVI file after eliminating noise, based on 1998 to 2008 vegetation NDVI data, six indexs of dynamic value RREL etc. in season of date DMIN and vegetation NDVI data appearred in the year minimum value that date DMAX, vegetation NDVI data appear in the year maximal value that calculates year minimum value MIN, the vegetation NDVI data of year maximal value MAX, the vegetation NDVI data of annual mean AVE, the vegetation NDVI data of the vegetation NDVI data of annual each city, flag;

The annual mean AVE of described vegetation NDVI data represents the long-run average that annual steppe vegetation covers; On behalf of steppe vegetation, the year maximal value MAX of described vegetation NDVI data and the year minimum value MIN of vegetation NDVI data cover the highest and minimum situation; The year minimum value that date DMAX and vegetation NDVI data appear in the year maximal value of described vegetation NDVI data occur date DMIN with ten days numerical table show, represent vegetation to cover mxm. and pairing date of minimum respectively; Described NDVI dynamic value in season RREL represents the year border changing condition of vegetation, and its computing formula is:

RREL＝[DMAX-DMIN]/[AVE]。

Step S4: calculate described six each leisures of index respectively and preset statistics year in one's duty year border dynamic change rate, by each index year border dynamic change rate, the reflection vegetation covers temporal degree of stability, obtains spatial distribution characteristic and year border dynamic rule that steppe vegetation covers;

Fig. 3-1 and Fig. 3-2 is that each NDVI refers to target year border dynamic change rate synoptic diagram in 1998 to 2008, wherein, Fig. 3-1 relate to annual mean AVE, year maximal value MAX, minimum value MIN and season dynamic value RREL; Fig. 3-2 relates to that date DMAX appears in a year maximal value and date DMIN appears in a year minimum value; Reflected among the figure and presetted that statistics time interplantation is capped, the overall state of the seasonal dynamic change of vegetation phenology feature and vegetation.Wherein, each index all relates to the situation of eight regions among above-mentioned Fig. 3-1 and Fig. 3-2, represent the data of each region year border dynamic change rate in the drawings with perpendicular shape column, each perpendicular shape column is followed successively by from left to right: Ergun City, Ewenki automonous banner, Hailaer, Manzhouli, Xinbaerhu Right Banner, Xinbaerhu Left Banner, Yakeshi City, Chenbarhu Banner.

Wherein, because AVE, MAX, MIN, RREL unit's difference, so in Fig. 3-1, represent its year border dynamic change rate with the coefficient of variation, that is, the year maximal value MAX of the annual mean AVE of described vegetation NDVI data, described vegetation NDVI data, described vegetation NDVI data year minimum value MIN and described vegetation NDVI data season dynamic value RREL year border dynamic change rate with coefficient of variation CV _tRepresent;

In addition, because DMAX, DMIN unit are identical, so adopt standard deviation to represent its year border dynamic change rate in Fig. 3-2, that is, the year minimum value that date DMAX and described vegetation NDVI data appear in the year maximal value of described vegetation NDVI data the year border dynamic change rate of date DMIN occurs with standard deviation SD _tRepresent;

Wherein, CV _tWith SD _tComputing formula be respectively:

${\mathrm{SD}}_t=\sqrt{\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}(x_i-\stackrel{\&OverBar;}{x})}{n-1}};$

${\mathrm{CV}}_t=\frac{{\mathrm{SD}}_t}{\stackrel{\&OverBar;}{x}};$

Wherein, n is the in one's duty annual quantity of statistics year that presets among the step S1, x _iBe respectively described each index at each annual numerical value, i=1,2,3...n,

Be respectively described each index and presetting statistics year in one's duty mean value; That is, when calculating described year maximal value and date DMAX and year minimum value occur and the year border dynamic change rate of date DMIN occurs, x _iThe ten days number that date DMIN appears in date DMAX and year minimum value appears in the year maximal value that is respectively each year, What the year maximal value that is respectively each year occurred that date DMIN appears in the mean value of date DMAX and the year minimum value of each year counts mean value in ten days; Calculate described annual mean AVE, year maximal value MAX, year minimum value MIN and season dynamic value RREL year border dynamic change rate the time, x _iBe respectively each year annual mean AVE, year maximal value MAX, year minimum value MIN and season dynamic value RREL,

Be respectively each year annual mean AVE, year maximal value MAX, year minimum value MIN and season dynamic value RREL mean value.

Step S5: presetting in the statistics time, (Man-Ken Deer) method is carried out trend analysis to described six indexs according to Mann-Kendall, obtain each index and presetting statistics year in one's duty statistical test value, obtain each index and presetting statistics year in one's duty dynamic change trend;

When carrying out the Mann-Kendall trend analysis, it is 95% that degree of confidence at first is set, the level of signifiance α of trend test=0.05;

Wherein, in the Mann-Kendall trend analysis computation process, utilize following formula to calculate each index and presetting statistics year in one's duty statistics S:

$S=\underset{k=1}{\overset{n-1}{\mathrm{\&Sigma;}}}\underset{j=k+1}{\overset{n}{\mathrm{\&Sigma;}}}\mathrm{sgn}(x_j-x_k);$

Wherein, x _jAnd x _kBe respectively the numerical value of each index at j and k, j＞k, n are the in one's duty annual quantity of statistics year that presets among the step S1; And,

Because, random series S _i(i=1,2 ..., n) Normal Distribution approx, therefore utilize following formula to calculate each index at the average E (S) and the variance Var (S) that are presetting statistics year in one's duty statistics S:

E(S)＝0；

$\mathrm{Var}\left(S\right)=\frac{n(n-1)(2n+5)}{18};$

Utilize following formula to calculate each index then and presetting statistics year in one's duty statistical test value Z _S:

$\mathrm{Zs}=\left\{\begin{array}{cc}\frac{S-1}{\mathrm{Var}\left(S\right)}& S>0\\ 0& S=0\\ \frac{S+1}{\mathrm{Var}\left(S\right)}& S<0\end{array}\right..$

Step S6: presetting year in one's duty year border dynamic change rate of statistics and statistical test value, dynamic change situation, phenology feature and the dynamic change trend of coming the quantitative examination steppe vegetation to cover based on described six indexs;

Specifically comprise the steps:

Step S601: judge described statistical test value Z _SThe trend significant change;

Step S602: if Z _SBe positive number, and Z _S＞Z _1-α/2, show that then steppe vegetation is coated with significant ascendant trend, if Zs is a negative, and Z _S＞Z _1-α/2, show that then steppe vegetation is coated with significant downtrending, if | Z _S|≤Z _1-α/2, show that then steppe vegetation covers no change trend.

Fig. 4-1 is the Mann-Kendall method trend analysis result's of each NDVI index synoptic diagram to Fig. 4-6, wherein, Fig. 4-1 relates to annual mean AVE, Fig. 4-2 relates to a year maximal value MAX, Fig. 4-3 relates to a year minimum value MIN, Fig. 4-4 relates to dynamic value RREL in season, and Fig. 4-5 relates to a year maximal value and date DMAX occurs, and Fig. 4-6 relates to a year minimum value and date DMIN occurs.Fig. 4-1 is to Fig. 4-6, and the part of blank box represents to be the pixel number percent of remarkable ascendant trend, and the part of black filling frame represents to be the pixel number percent of remarkable downtrending; The data that all relate to eight regions among each figure, order from left to right is identical with the order of survey region object among Fig. 3-1 and Fig. 3-2.

From the trend analysis result, the pixel number percent that AVE presents remarkable downtrending is bigger, shows that the study area vegetation is coated with minimizing trend; MAX and MIN variation tendency are not obvious, show that mxm. and minimum that vegetation covers do not have to change substantially; Each city, flag RREL present different remarkable rising, downtrending, show study area spatially different regions tables seasonal variety rate differ greatly; The pixel number percent that DMAX presents remarkable downtrending on the whole is bigger, show that the study area vegetation covers the maximal value date in advance, vegetation phenology characteristic change, and minority city, flag DMIN present remarkable ascendant trend, show that these regional vegetation cover minimum value dates and postpone, vegetation phenology changes.

As can be seen from the above embodiments, technical solution of the present invention is utilized SPOT VGT vegetation NDVI data configuration NDVI sequential file, cover situation, phenology feature and seasonal dynamic six NDVI indexs thereof by the reflection vegetation, space-time dynamic evolution process and phenology variation characteristic that quantitative test grass vegetation covers have been inquired into the dynamic change trend that vegetation covers.

The above only is a preferred implementation of the present invention; should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the technology of the present invention principle; can also make some improvement and distortion, these improvement and distortion also should be considered as protection scope of the present invention.

Claims (6)

1. a steppe vegetation covers the remote sensing Quantitative Monitoring method that space-time dynamic changes, and it is characterized in that described method comprises the steps:

Step S1: the initial time that preestablishes the statistics time covers the time range that space-time dynamic changes as the Quantitative Monitoring steppe vegetation;

Step S2: utilize the normalized differential vegetation index NDVI data creating of vegetation to preset NDVI sequential file annual in the statistics time, eliminate the noise of NDVI sequential file then;

Step S3: in the sequential NDVI file after described elimination noise, calculate in the vegetation NDVI data and cover several indexs that space-time dynamic changes about steppe vegetation;

Step S4: calculate described each leisure of several indexs respectively and preset statistics year in one's duty year border dynamic change rate;

Step S5: presetting in the statistics time, according to the Mann-Kendall method described several indexs are carried out trend analysis, obtain each index and presetting statistics year in one's duty statistical test value, obtain each index and presetting statistics year in one's duty dynamic change trend;

Step S6: presetting year in one's duty year border dynamic change rate of statistics and statistical test value, the dynamic change trend of coming the quantitative examination steppe vegetation to cover based on described several indexs.

2. steppe vegetation as claimed in claim 1 covers the remote sensing Quantitative Monitoring method that space-time dynamic changes, it is characterized in that, among the described step S2, utilize the remote sensing image handling implement to handle vegetation NDVI data, generate and preset NDVI sequential file annual in the statistics time; At NDVI sequential file noise place, utilize averaging method then, promptly calculate the mean value of its front and back vegetation NDVI data and replace noise figure, eliminate noise with this mean value.

3. steppe vegetation as claimed in claim 1 covers the remote sensing Quantitative Monitoring method that space-time dynamic changes, it is characterized in that, and among the described step S3,

Described several indexs comprise: the dynamic value RREL in season of date DMIN and vegetation NDVI data appears in the year minimum value that date DMAX, vegetation NDVI data appear in the year maximal value of the year maximal value MAX of the annual mean AVE of vegetation NDVI data, vegetation NDVI data, the year minimum value MIN of vegetation NDVI data, vegetation NDVI data;

Wherein,

The annual mean AVE of described vegetation NDVI data represents the long-run average that annual steppe vegetation covers;

On behalf of steppe vegetation, the year maximal value MAX of described vegetation NDVI data and the year minimum value MIN of vegetation NDVI data cover the highest and minimum situation;

The year minimum value that date DMAX and vegetation NDVI data appear in the year maximal value of described vegetation NDVI data occur date DMIN with ten days numerical table show, represent vegetation to cover mxm. and pairing date of minimum respectively;

Described NDVI dynamic value in season RREL represents the year border changing condition of vegetation, and its computing formula is:

RREL＝[DMAX-DMIN]/[AVE]。

4. steppe vegetation as claimed in claim 3 covers the remote sensing Quantitative Monitoring method that space-time dynamic changes, it is characterized in that, and among the described step S4,

The year maximal value MAX of the annual mean AVE of described vegetation NDVI data, described vegetation NDVI data, described vegetation NDVI data year minimum value MIN and described vegetation NDVI data season dynamic value RREL a year border dynamic change rate represent with coefficient of variation CVt;

The year minimum value that date DMAX and described vegetation NDVI data appear in the year maximal value of described vegetation NDVI data the year border dynamic change rate of date DMIN occurs with standard deviation SD _tRepresent;

Wherein, CV _tWith SD _tComputing formula be respectively:

${\mathrm{SD}}_t=\sqrt{\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}(x_i-\stackrel{\&OverBar;}{x})}{n-1}};$

${\mathrm{CV}}_t=\frac{{\mathrm{SD}}_t}{\stackrel{\&OverBar;}{x}};$

Wherein, n is the in one's duty annual quantity of statistics year that presets among the step S1, x _iBe respectively described each index at each annual numerical value, i=1,2,3...n,

Be respectively described each index and presetting statistics year in one's duty mean value.

5. steppe vegetation as claimed in claim 1 covers the remote sensing Quantitative Monitoring method that space-time dynamic changes, and it is characterized in that, among the described step S5, specifically comprises the steps:

Step 501: presetting degree of confidence is 95%, the level of signifiance α of trend test=0.05;

Step 502: utilize following formula to calculate each index and presetting statistics year in one's duty statistics S:

$S=\underset{k=1}{\overset{n-1}{\mathrm{\&Sigma;}}}\underset{j=k+1}{\overset{n}{\mathrm{\&Sigma;}}}\mathrm{sgn}(x_j-x_k);$

Wherein, x _jAnd x _kBe respectively the numerical value of each index at j and k, j＞k, n are the in one's duty annual quantity of statistics year that presets among the step S1; And,

Step 503: utilize following formula to obtain each index and presetting average E (S) and the variance Var (S) that adds up year in one's duty statistics S:

E(S)＝0；

$\mathrm{Var}\left(S\right)=\frac{n(n-1)(2n+5)}{18};$

Step 504: utilize following formula to calculate each index and presetting statistics year in one's duty statistical test value Z _S:

$Z_S=\left\{\begin{array}{cc}\frac{S-1}{\mathrm{Var}\left(S\right)}& S>0;\\ 0& S=0;\\ \frac{S+1}{\mathrm{Var}\left(S\right)}& S<0.\end{array}\right.$

6. steppe vegetation as claimed in claim 5 covers the remote sensing Quantitative Monitoring method that space-time dynamic changes, and it is characterized in that, among the described step S6, the process of the space-time dynamic variation tendency that the quantitative examination steppe vegetation covers specifically comprises the steps:

Step S601: judge described statistical test value Z _SThe trend significant change;

Step S602: if Z _SBe positive number, and Z _S＞Z _1-α/2, show that then steppe vegetation is coated with significant ascendant trend, if Zs is a negative, and Z _S＞Z _1-α/2, show that then steppe vegetation is coated with significant downtrending, if | Z _S|≤Z _1-α/2, show that then steppe vegetation covers no change trend.

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