Method for repairing remote sensing vegetation index time sequence under influence of coastal zone tides

Abstract

The invention discloses a method for repairing a remote sensing vegetation index time sequence under the influence of coastal zone tides. The method is characterized in that the method comprises the steps: vegetation index time sequence and normalized difference water body index acquisition, tidal influence sample pixel acquisition, time sequence noise point identification, noise point numerical value restoration model construction and vegetation index time sequence restoration evaluation, wherein each sample pixel in an experimental area is traversed, vegetation index noise point correction amount is calculated by utilizing a noise point numerical value restoration model, and the sum of a vegetation index noise point numerical value and a corresponding vegetation index noise point correction amount numerical value are taken as a vegetation index correction value of a vegetation index noise point so as to obtain a restored vegetation index time sequence. The method has the advantages of being wide in application range, high in automation degree, high in robustness and suitable for different spatial resolutions.

Description

technical field [0001] The invention relates to a method for repairing the time series of vegetation index of remote sensing images, in particular to a method for repairing the time series of remote sensing vegetation index under the influence of coastal tides. Background technique [0002] In coastal areas where land and sea interact closely, vegetation (salt marshes, mangroves, seagrass, etc.) acts as an important carbon sink, and continuously promotes the "blue carbon" process of soil through spontaneous primary production and continuous tidal flat deposition. Remote sensing (Remote Sensing) provides large-scale and long-term vegetation dynamic observation techniques, which is helpful to monitor the primary productivity of coastal vegetation and dynamically and quantitatively evaluate changes in the carbon sequestration capacity of coastal ecosystems, which is of great significance. However, remote sensing of vegetation in the coastal zone is particularly complicated due ...

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Problems solved by technology

However, the development of the vegetation phenology cycle and the difference in tidal height at the time of imaging lead to constant changes in the relative difference between vegetation and seawater. The threshold selection method for a single period is relatively one-sided, and it is less accurate for drawing periodic tidal inundation frequencies spanning multiple periods. Difference

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