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Automatic window ergodic SEVI regulatory factor optimization algorithm

An adjustment factor, automatic optimization technology, applied in the direction of electromagnetic wave re-radiation, using re-radiation, measuring devices, etc., can solve the problems of limiting the automation level of terrain shadows, unfavorable promotion and application, etc., to achieve the minimization of data cost and time cost, and can Strong operability and obvious effect

Active Publication Date: 2018-12-18
FUZHOU UNIV
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Problems solved by technology

However, the first two optimization algorithms both need to classify remote sensing images, and the "optimization and matching" algorithm also needs the support of ground data; the third method, although it does not require image classification, requires manual selection of sample areas, which has great inconsistencies. Stability; in addition, these three methods are easy to fall into the local optimal solution rather than the global optimal solution, which limits the automation level of terrain shadow removal vegetation index application, which is not conducive to popularization and application

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  • Automatic window ergodic SEVI regulatory factor optimization algorithm
  • Automatic window ergodic SEVI regulatory factor optimization algorithm

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[0035] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0036] Please refer to figure 1 , the present invention provides a kind of SEVI adjusting factor automatic optimization algorithm of window traversal, and it comprises the following steps:

[0037] Step S1: Window selection: observe the mountain distribution on a remote sensing image, judge the slope length of the mountain through the shady and sunny slopes, and select the maximum slope length to determine the calculation window parameter K. Combining practicability and computational efficiency, referring to the 30-meter spatial resolution of Landsat images, the window parameter K can choose 50, 100, 150, 200, etc. to represent the window size on the image.

[0038] Step S2: Calculation of vegetation index: Calculate the shadow elimination vegetation index, ratio vegetation index and shadow vegetation index based on the apparent reflectance data of the...

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Abstract

The invention relates to an automatic window ergodic SEVI regulatory factor optimization algorithm. The automatic window ergodic SEVI regulatory factor optimization algorithm comprises the following steps of window selection, vegetation index calculation, correlation coefficient calculation, single window optimization solution, window ergodic and global (full view) optimal solution. According to the automatic window ergodic SEVI regulatory factor optimization algorithm, DEM data assistance, remote sensing image classification and artificial designation of a calculation sample area are not required, instability of artificial selection of the sample area is avoided, the automation level of SEVI calculation is improved, and the automatic window ergodic SEVI regulatory factor optimization algorithm has important scientific significance and economic value for accurate inversion of remote sensing vegetation information in complex terrain mountainous areas and elimination of interference of topographic umbrae and falling shadows.

Description

technical field [0001] The invention relates to a SEVI adjustment factor automatic optimization algorithm for window traversal. Background technique [0002] There are three main optimization methods for the terrain adjustment factor f(△) in the existing terrain shadow elimination vegetation index TAVI: "matching optimization method (national patent number 200910111688X)", "extreme value optimization method (national patent number 201010180895.3)" and " Correlation coefficient method (national patent number 2015108077580)". [0003] The calculation steps of the "matching optimization" algorithm are: (1) image classification, dividing the shady and sunny slopes of the mountain in remote sensing images, and selecting typical sample areas; (2) target recognition, using ground survey data, field survey data, aerial photography Data or high-resolution image data from Google Earth to verify the homogeneity of the vegetation on the shady and sunny slopes, and identify the parts of...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S17/89
CPCG01S17/89
Inventor 江洪柳晓农王森
Owner FUZHOU UNIV
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