CN105279738A - Coping method of shadow problem in vegetation parameter estimation, based on remote sensing images - Google Patents
Coping method of shadow problem in vegetation parameter estimation, based on remote sensing images Download PDFInfo
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- CN105279738A CN105279738A CN201510415135.9A CN201510415135A CN105279738A CN 105279738 A CN105279738 A CN 105279738A CN 201510415135 A CN201510415135 A CN 201510415135A CN 105279738 A CN105279738 A CN 105279738A
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Abstract
The invention discloses a method for coping with a shadow problem caused by landform fluctuating and cloud clusters in vegetation parameter estimation, based on remote sensing images. The method comprises the steps of: firstly carrying out atmosphere correction on the remote sensing images, then selecting spectrum wave bands sensitive to target parameters, and finally taking the spectrum wave bands to a correction formula y=(b1-b2)/(b1+b2) so as to obtain normalized vegetation indexes after final correction. The adopted correction formula is simple linear operation of two wave bands of remote sensing data, the complexity is low, the calculation speed is substantially improved, and the batch processing of remote sensing images is facilitated. From a correction result, the effect is substantial, the shadow problem is relieved to a certain degree, and the sensitivity to the target parameters is maintained, so that the technical method provided by the invention for relieving the shadow problem caused by landform fluctuating and cloud clusters is simple and applicable.
Description
Technical field
The invention belongs to remote sensing technology field, relate to a kind of countermeasure for shadow problem in the estimation of remote sensing image vegetation parameter.
Background technology
Vegetation biological chemistry-biophysical parameters, as leaf area index, chlorophyll, leaf water content, canopy water cut, biomass etc. to reaction vegetation growth status, material and energy exchanging rate between estimation low level air and vegetation, understand crop moisture and force degree, assess forest and Grassland fire risk probability of happening etc. there is important indicative function.These important vegetation parameters have sensitivity in various degree on the different spectral band of vegetation, as leaf area index shows comparatively strong reflection characteristic at near-infrared band, it is then comparatively strong reflection characteristic that chlorophyll reveals stronger absorption characteristic at green wave band at red frequency-range table, and canopy water cut has stronger absorbent properties at short infrared wave band.Meanwhile, remote sensing image data also has multidate, many spatial resolutions and ageing feature, make to utilize these data can on space large scale, multidate rapid extraction target component, be that science decision information timely improves in relevant industries department.But the shade that topographic relief and part cloud cluster are formed can cause remote sensing images uncontinuity spatially or obtain the target component estimated value of mistake, hinders the further application of remote sensing technology.
Summary of the invention
The object of the invention aims to provide shadow problem caused by mesorelief fluctuating and cloud cluster is estimated in the reply of a kind of simple and fast method based on remote sensing image data vegetation parameter, and the remote sensing image space uncontinuity that alleviation shade causes and target component are by the problem misestimated.
The present invention solves the problems of the technologies described above taked technical scheme: first, does atmospheric correction to remote sensing image, and DN value is converted to Reflectivity for Growing Season; Secondly, the spectral band to target vegetation parameter sensitivity (absorbing or reflection characteristic) is chosen; Finally, bring two wave band reflectivity any in upper step into following formula, y=(b1-b2)/(b1+b2), wherein, b1, b2 be not for repeating wave band to responsive any two of vegetation, be specially green light band (500-600nm), red spectral band (600-700nm), near-infrared band (760-900nm) and short infrared wave band (1500-2400nm), y is the index after the normalization finally obtained, and its span is between-1 to 1.The index utilizing the technical program finally to obtain can ensure its sensitivity to target vegetation parameter, can alleviate again the shadow problem caused by topographic relief and cloud cluster to a certain extent.
Further, remote sensing image refers in particular to the remote sensing image data in vegetative coverage region.
Further, b1 and b2 must be the Reflectivity for Growing Season image data after atmospheric correction.
Be further, b1 and b2 must be the spectral band to target component sensitivity (absorbing or reflection characteristic), is specially green light band (500-600nm), red spectral band (600-700nm), near-infrared band (760-900nm) and short infrared wave band (1500-2400nm).
Further, the span of y is between-1 to 1.
Beneficial effect of the present invention: even if original remote sensing image data also cannot alleviate through atmospheric correction the shadow problem that topographic relief and cloud cluster cause.The normalization index that method provided by the present invention finally obtains can ensure its sensitivity to target component, can alleviate again the impact of shade to a certain extent.Meanwhile, the method simple and fast, is easy to operation, can be used for alleviating the remote sensing image shadow problem within the scope of large scale, ensures remote sensing image data continuity spatially and improves the effect of estimation precision of target component on the whole.
Accompanying drawing explanation
Accompanying drawing 1 is for original image and utilize this patent method to correct rear remote sensing image contrast effect
Embodiment
Below in conjunction with accompanying drawing and embodiment, the present invention is described further.
Fig. 1 (a) is Landsat8 True color synthesis figure.As can be seen from the figure, the shadow problem that massif and cloud cluster cause is very serious, can cause this survey region remote sensing image spatially discontinuous undoubtedly or occur that even more serious parameter misestimates problem as direct by this image data estimation target component.This patent method is now utilized to do following process: first to do atmospheric correction to this width image and DN value is converted to apparent reflectance.Conventional atmospheric correction software has ENVI to carry FLAASH module and 6S atmospheric correction models, and the two input parameter is similar, and can carry meta file and local weather station distributing data from remotely-sensed data and obtain.Secondly, target wave band is chosen.The estimation vegetation parameter generally red wave band of normal use (band4), near-infrared band (band5) and short infrared wave band (band6).Also select this three wave band as calibration object in this example.Finally, selected wave band image data is brought in y=(b1-b2)/(b1+b2), obtain final normalization index.As shown in Fig. 1 (b) and (c), the shade obtained after calibrated in remote sensing image obtains great alleviation, and especially (b) figure is more obvious to the alleviation of shade; Meanwhile, after this method ensure that correction, image is to the high sensitive of vegetation.As can be seen here, the shadow problem utilizing this patent effectively can alleviate topographic relief and cloud cluster to cause.
The updating formula that this patent alleviation remote sensing image top shadow method adopts is the simple linear computing of remotely-sensed data two wave bands, and complexity is low, greatly can improve computation rate, is convenient to the batch processing of remote sensing image.From correction result, its Be very effective, alleviates shadow problem to a certain extent, and keeps the susceptibility to target component.Therefore, the shadow problem that the technical method that this patent provides causes for alleviation topographic relief and cloud cluster is simple and practical.
Claims (6)
1., based on the countermeasure of shadow problem in the estimation of remote sensing image vegetation parameter, it is characterized in that comprising the following steps: first, atmospheric correction is done to remote sensing image, DN value is converted to Reflectivity for Growing Season; Secondly, the spectral band to target vegetation parameter sensitivity (absorbing or reflection characteristic) is chosen; Finally, two wave band reflectivity any in upper step are brought into following formula, y=(b1-b2)/(b1+b2), wherein, b1 is any two and does not repeat wave band, and y is the index after the normalization finally obtained, and its span is between-1 to 1.
2. as claimed in claim 1, it is characterized in that: remote sensing image refers in particular to the remote sensing image data in vegetative coverage region.
3. as claimed in claim 1, it is characterized in that: updating formula used is y=(b1-b2)/(b1+b2).
4. as claimed in claim 1, it is characterized in that b1 and b2 must for the Reflectivity for Growing Season image data after atmospheric correction.
5. as claimed in claim 1, it is characterized in that: b1 and b2 for the spectral band to target vegetation parameter sensitivity (absorbing or reflection characteristic), must be specially green light band (500-600nm), red spectral band (600-700nm), near-infrared band (760-900nm) and short infrared wave band (1500-2400nm).
6. as claimed in claim 1, it is characterized in that: the span of y is between-1 to 1.
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| CN107909607A (en) * | 2017-12-11 | 2018-04-13 | 河北省科学院地理科学研究所 | A kind of year regional vegetation coverage computational methods |
| CN108051371A (en) * | 2017-12-01 | 2018-05-18 | 河北省科学院地理科学研究所 | A kind of shadow extraction method of ecology-oriented environment parameter remote-sensing inversion |
| CN108230310A (en) * | 2018-01-03 | 2018-06-29 | 电子科技大学 | A kind of method that non-fire space-time data is extracted based on semivariable function |
| CN110321774A (en) * | 2019-04-04 | 2019-10-11 | 平安科技（深圳）有限公司 | Crops evaluation methods for disaster condition, device, equipment and computer readable storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108051371A (en) * | 2017-12-01 | 2018-05-18 | 河北省科学院地理科学研究所 | A kind of shadow extraction method of ecology-oriented environment parameter remote-sensing inversion |
| CN108051371B (en) * | 2017-12-01 | 2018-10-02 | 河北省科学院地理科学研究所 | A kind of shadow extraction method of ecology-oriented environment parameter remote-sensing inversion |
| CN107909607A (en) * | 2017-12-11 | 2018-04-13 | 河北省科学院地理科学研究所 | A kind of year regional vegetation coverage computational methods |
| CN108230310A (en) * | 2018-01-03 | 2018-06-29 | 电子科技大学 | A kind of method that non-fire space-time data is extracted based on semivariable function |
| CN108230310B (en) * | 2018-01-03 | 2021-12-17 | 电子科技大学 | Method for extracting non-fire spatio-temporal data based on semi-variogram |
| CN110321774A (en) * | 2019-04-04 | 2019-10-11 | 平安科技（深圳）有限公司 | Crops evaluation methods for disaster condition, device, equipment and computer readable storage medium |
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