CN101825702A - Method for adjusting and optimizing terrain by utilizing terrain adjusting vegetation index - Google Patents
Method for adjusting and optimizing terrain by utilizing terrain adjusting vegetation index Download PDFInfo
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Abstract
The invention relates to a method for adjusting and optimizing a terrain by utilizing a terrain adjusting vegetation index. The method is characterized in that waveband information of an optical remote sensing image and derived information thereof are used for optimizing; and the method comprises the steps of constructing a terrain adjusting vegetation index (TAVI), classifying images and optimizing matching, can accurately and quickly invert the vegetation index of complicated terrain mountain areas, provide an important means for drawing complicated terrain mountain area vegetation (forest), monitoring vegetation coverage, estimating forest coverage rate and inverting the leaf area index, can also provide important calculation parameters for estimating biophysical and biochemical parameters such as forest biomass, productivity, photosynthetic active radiation and absorption and the like, and has favorable practical value.
Description
Technical field
The present invention relates to a kind of landform and regulate the landform adjusting optimization method of vegetation index.
Background technology
The complex-terrain mountain area, because topographic relief has changed the distribution of solar radiation on the face of land, for same wave band, the radiance value of massif Schattenseite part is less than normal in the multispectral remote sensing image, and the radiance value of tailo part is bigger than normal, cause image information to distort, the vegetation index information distortion by corresponding wave band generates has had a strong impact on the accurate inverting of atural object vegetation information.The influence of topography becomes one of major obstacle of the accurate inverting of mountain area vegetation information remote sensing.
At present, Chang Gui disposal route is to carry out topographic correction earlier before calculating vegetation index.The method of topographic correction can be divided into two big classes, and a class is based on the topographic correction of dem data, mainly contains: (1) empirical statistics model, classic algorithm have cosine correction, C to proofread and correct, SCS proofreaies and correct, SCS+C proofreaies and correct, Proy proofreaies and correct etc.; (2) based on the physical model of radiation transfer theory, carry out topographic correction by the physical process of research light and face of land effect; (3) based on the landform radiant correction of statistical study, as the square matching algorithm.These methods all produce effect, but degree varies is also different to the improvement degree of vegetation information; Even more serious problem is that these conventional landform correcting method of lane all need the support of high accuracy DEM data.Because the introducing of dem data might be introduced new error, the renewal of dem data often lags behind the variation that actual landform brings because of nature, human factor again, particularly obtaining of high accuracy DEM data is restricted, and restricted the effect and the application of this type of landform correcting method of lane to a great extent.Another kind of landform correcting method of lane need not the support of dem data, and as adopting the method for wave band than model, because landform changes the difference that influences to different-waveband, so this model can only play the effect of constraining the influence of topography, and do not reach desirable topographic correction effect; The linear matching process of gray scale be because the sample of selecting can not be contained all images, and therefore the correction of only carrying out wave band with a linear function of this derivation has bigger limitation; Do not see correlative study and can improve mountain area vegetation index information inversion accuracy to the method for cloud, buildings shadow removal in the high-resolution remote sensing image of city.
At the deficiency of above-mentioned the whole bag of tricks, I have invented the building method (national patent application number 200910111688.X) of landform adjusting vegetation index (having another name called topographic correction vegetation index).The vegetation index that makes up according to this method need not the support of data such as DEM, just can effectively eliminate the influence of landform to vegetation information.For the key factor in this vegetation index---the optimized Algorithm of landform regulatory factor (having another name called the topographic correction factor) has proposed a kind of optimized Algorithm based on the ground investigation data among " building method of topographic correction vegetation index " (national patent application number 200910111688.X); Because this optimized Algorithm needs the support of ground investigation data or field study data, is subjected to certain restriction in the practical application.For this reason, design a kind of landform that does not rely on ground investigation data or field study data and regulate optimized Algorithm, landform is regulated vegetation index have important scientific meaning and economic worth with the businessization popularization in the successful Application of the accurate inverting of complex-terrain mountain area vegetation information.
Summary of the invention
The purpose of this invention is to provide a kind of landform and regulate the landform adjusting optimization method of vegetation index, it is inverting complex-terrain mountain area vegetation information accurately and rapidly, for complex-terrain mountain area vegetation (forest) drawing, vegetation coverage monitoring, afforestation rate assessment, leaf area index inverting provide important means, and can provide the important computations parameter for the estimation of biophysics such as forest biomass, yield-power, photosynthetically active radiation absorption and biochemical parameters.
Invention realizes by the following technical solutions: a kind of landform is regulated the landform of vegetation index and is regulated optimization method, it is characterized in that: utilize the band class information of optical remote sensing image self and derived information thereof to be optimized, may further comprise the steps:
(1) make up landform and regulate vegetation index TAVI, its computing formula is: TAVI=CVI+TAC*SVI; Wherein, CVI represents vegetation index commonly used, and SVI represents the shade vegetation index; TAC represents the landform regulatory factor, and the corresponding calculated formula is:
SVI=[MAX (B
r) – B
r]/B
rWherein, B
rRepresent red wave band data, MAX (B
r) maximal value of expression study area red wave band data.
(2) select the sample district: check the remote sensing image quality, select a certain size planar zone in the complex-terrain mountain area, guarantee sample district image " noise " disturb minimum, to have the strong influence of topography, an area enough big;
(3) image classification: use conventional not supervised classification the vegetation in the sample district remote sensing image is divided into Schattenseite and tailo two big classes;
(4) optimization of matching: the design cycle program, make TAC since 0,0.001 to be the interval, increase progressively successively, investigate the maximal value M of Schattenseite part TAVI simultaneously
TAVI the moonMaximal value M with tailo part TAVI
The TAVI sun, work as M
TAVI the moonWith M
The TAVI sunEquate or during approximately equal, withdraw from circulation, determine that finally TAC optimizes the result; If when TAC tires out when increasing to 5 M
TAVI the moonWith M
The TAVI sunAlso do not satisfy condition, then return step (2), reselect the sample district, repeating step (2) is to step (4), until M
TAVI the moonWith M
The TAVI sunSatisfy and equate or close condition.
The present invention has following advantage:
The first, the topographic correction effect is remarkable.The landform regulatory factor that this optimization method is determined, the assurance landform is regulated vegetation index can effectively eliminate the interference of the influence of topography to vegetation information.Regulate the linear regression analysis of vegetation index and solar incident angle cosine value by the landform of this method being determined in experiment sample district, show that landform that this method is determined regulates the related coefficient and the equation of linear regression slope of vegetation index and solar incident angle cosine value and can reduce to minimum, obviously be better than other vegetation index commonly used, and more excellent than common atmospheric correction or topographic correction effect.
The second, demand data is few, and cost is low.This optimization method only needs the self-contained wave band data of remote sensing image, need not the support of ground investigation data or on-the-spot investigation data etc., and data cost and time cost are realized minimizing.
The 3rd, flow process is simple, and is workable.This optimization method mainly just can be determined the optimization result of landform regulatory factor by " selecting the sample district ", " image classification " and " optimization of matching " three steps, flow process is simple, and operation easily helps landform to regulate the business application and the popularization of vegetation index.
Description of drawings
Fig. 1 is a techniqueflow synoptic diagram of the present invention.
Embodiment
As shown in Figure 1, the invention provides the landform adjusting optimization method that a kind of landform is regulated vegetation index, it is characterized in that: utilize the band class information of optical remote sensing image self and derived information thereof to be optimized, may further comprise the steps:
(1) make up landform and regulate vegetation index TAVI: the basic calculating formula that landform is regulated vegetation index is as follows
TAVI=CVI+TAC*SVI
Wherein, CVI represents vegetation index commonly used, as normalized differential vegetation index NDVI, ratio vegetation index RVI etc.; SVI represents the shade vegetation index; TAC represents the landform regulatory factor, and corresponding concrete computing formula is as follows:
NDVI=(B
nir-B
r)/(B
nir+B
r)
RVI=B
nir/B
r?
SVI=[MAX(B
r)–B
r]/B
r?
Wherein, B
NirExpression near-infrared band data, B
rRepresent red wave band data, MAX (B
r) represent that the maximal value of the red wave band data of study area (is noted that: in present embodiment here, the remote sensing image wave band data all with apparent reflectance as experimental data, unless otherwise noted, vegetation index hereinafter calculates all based on apparent reflectance).
(2) select the sample district: check the remote sensing image quality, select a certain size planar zone in the complex-terrain mountain area, guarantee that sample district image " noise " disturbs minimum, has the strong influence of topography, area enough big (preferable area is greater than 10 square kilometres) here;
(3) image classification: use conventional not supervised classification the vegetation in the sample district remote sensing image is divided into Schattenseite and tailo two big classes, as maximum likelihood method or fuzzy clustering method etc.;
(4) optimization of matching: according to formula TAVI=CVI+TAC*SVI, design TAVI optimizes loop program: make TAC since 0,0.001 to be the interval, increase progressively successively, investigate the maximal value M of Schattenseite part TAVI simultaneously
TAVI the moonMaximal value M with tailo part TAVI
The TAVI sun, work as M
TAVI the moonWith M
The TAVI sunEquate or during approximately equal, withdraw from circulation, determine that finally TAC optimizes the result; If when TAC tires out when increasing to 5 M
TAVI the moonWith M
The TAVI sunAlso do not satisfy condition, then return step (2), reselect the sample district, repeating step (2) is to step (4), until M
TAVI the moonWith M
The TAVI sunSatisfy and equate or close condition.
The above only is preferred embodiment of the present invention, and all equalizations of being done according to the present patent application claim change and modify, and all should belong to covering scope of the present invention.
Claims (3)
1. the landform of a landform adjusting vegetation index is regulated optimization method, it is characterized in that: utilize the band class information of optical remote sensing image self and derived information thereof to be optimized, may further comprise the steps:
(1) make up landform and regulate vegetation index TAVI, its computing formula is: TAVI=CVI+TAC*SVI; Wherein, CVI represents vegetation index commonly used, and SVI represents the shade vegetation index; TAC represents the landform regulatory factor, and the corresponding calculated formula is:
SVI=[MAX (B
r) – B
r]/B
rWherein, B
rRepresent red wave band data, MAX (B
r) maximal value of expression study area red wave band data.
(2) select the sample district: check the remote sensing image quality, select a certain size planar zone in the complex-terrain mountain area, guarantee sample district image " noise " disturb minimum, to have the strong influence of topography, an area enough big;
(3) image classification: use conventional not supervised classification the vegetation in the sample district remote sensing image is divided into Schattenseite and tailo two big classes;
(4) optimization of matching: the design cycle program, make TAC since 0,0.001 to be the interval, increase progressively successively, investigate the maximal value M of Schattenseite part TAVI simultaneously
TAVI the moonMaximal value M with tailo part TAVI
The TAVI sun, work as M
TAVI the moonWith M
The TAVI sunEquate or during approximately equal, withdraw from circulation, determine that finally TAC optimizes the result; If when TAC tires out when increasing to 5 M
TAVI the moonWith M
The TAVI sunAlso do not satisfy condition, then return step (2), reselect the sample district, repeating step (2) is to step (4), until M
TAVI the moonWith M
The TAVI sunSatisfy and equate or close condition.
2. landform according to claim 1 is regulated the landform of vegetation index and is regulated optimization method, and it is characterized in that: the vegetation index CVI commonly used in the described step (1) comprises normalized differential vegetation index NDVI, ratio vegetation index RVI; The corresponding calculated formula is:
NDVI=(B
Nir-B
r)/(B
Nir+ B
r); RVI=B
Nir/ B
rWherein, B
NirExpression near-infrared band data.
3. landform according to claim 1 is regulated the landform of vegetation index and is regulated optimization method, and it is characterized in that: the sample district area of described step (2) is greater than 10 square kilometres.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105389538A (en) * | 2015-10-09 | 2016-03-09 | 南京大学 | Method for estimating forest leaf-area index based on point cloud hemisphere slice |
| CN105487066A (en) * | 2015-11-20 | 2016-04-13 | 福州大学 | Novel optimization algorithm of TAVI topography adjusting factor |
| CN106324614A (en) * | 2016-08-10 | 2017-01-11 | 福州大学 | New TAVI combination algorithm |
| WO2018028191A1 (en) * | 2016-08-10 | 2018-02-15 | 福州大学 | Tavi calculation method based on waveband ration model and solar elevation angle |
| CN107730502A (en) * | 2017-11-15 | 2018-02-23 | 福州大学 | A kind of algorithm on the s factors in new TAVI models |
| CN109086661A (en) * | 2018-06-14 | 2018-12-25 | 中科禾信遥感科技（苏州）有限公司 | A kind of crops relative radiometric normalization method and device |
| CN113553549A (en) * | 2021-07-26 | 2021-10-26 | 中国科学院西北生态环境资源研究院 | Method and device for inversion of plant coverage, electronic equipment and storage medium |
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Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105389538A (en) * | 2015-10-09 | 2016-03-09 | 南京大学 | Method for estimating forest leaf-area index based on point cloud hemisphere slice |
| CN105389538B (en) * | 2015-10-09 | 2018-07-13 | 南京大学 | A method of based on a cloud hemisphere slice estimation Forest Leaf Area Index |
| CN105487066A (en) * | 2015-11-20 | 2016-04-13 | 福州大学 | Novel optimization algorithm of TAVI topography adjusting factor |
| CN105487066B (en) * | 2015-11-20 | 2018-02-09 | 福州大学 | A kind of new TAVI landform regulatory factor optimized algorithm |
| CN106324614A (en) * | 2016-08-10 | 2017-01-11 | 福州大学 | New TAVI combination algorithm |
| WO2018028191A1 (en) * | 2016-08-10 | 2018-02-15 | 福州大学 | Tavi calculation method based on waveband ration model and solar elevation angle |
| US10527542B2 (en) | 2016-08-10 | 2020-01-07 | Fuzhou University | Method of calculating TAVI based on a band ratio model and solar altitude angle |
| CN107730502A (en) * | 2017-11-15 | 2018-02-23 | 福州大学 | A kind of algorithm on the s factors in new TAVI models |
| CN109086661A (en) * | 2018-06-14 | 2018-12-25 | 中科禾信遥感科技（苏州）有限公司 | A kind of crops relative radiometric normalization method and device |
| CN109086661B (en) * | 2018-06-14 | 2019-05-03 | 中科禾信遥感科技（苏州）有限公司 | A kind of crops relative radiometric normalization method and device |
| CN113553549A (en) * | 2021-07-26 | 2021-10-26 | 中国科学院西北生态环境资源研究院 | Method and device for inversion of plant coverage, electronic equipment and storage medium |
| CN113553549B (en) * | 2021-07-26 | 2023-04-14 | 中国科学院西北生态环境资源研究院 | Method and device for inversion of coverage degree of planting, electronic equipment and storage medium |
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