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LAI inversion method and device

An inversion and node technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as discontinuous time series of LAI products, LAI products cannot meet application requirements, etc., and achieve the effect of improving accuracy

Inactive Publication Date: 2019-07-09
BEIJING NORMAL UNIVERSITY
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Problems solved by technology

However, most of this method uses observation data with the same or similar spatial resolution. Although different remote sensing information is fully utilized, the LAI products obtained by inversion still cannot meet the application requirements of different spatial scales, and most of the fused data are For observation data in the same time phase, LAI products are still discontinuous in time series

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Embodiment Construction

[0016] In order to make the object, technical solution and advantages of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0017] Hereinafter, embodiments of the present invention will be described with reference to the drawings. It should be understood, however, that these descriptions are illustrative only and are not intended to limit the scope of the present invention. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concept of the present invention.

[0018] The terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting of the invention. The words "a", "an" and "the" used herein shall also include the meanings of "plurality" and "multiple", unless the context clearly indicates otherwise. In addition, ...

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Abstract

The invention discloses an LAI inversion method and an LAI inversion device. The method comprises the following steps: obtaining LAI model forecast values under a low resolution scale and a high resolution scale by utilizing an LAI multi-year mean value of low resolution image pixels obtained from a GLASS LAI product and surface reflectance data with high resolution obtained from a land satellitesensor; obtaining an LAI forecast value of each node in the set multi-scale tree model according to the LAI model forecast values under the low-resolution scale and the high-resolution scale; and according to the LAI forecast values corresponding to the nodes and the acquired multi-source satellite observation data, updating the state vector set matrix of each node by adopting a set multi-scale filtering technology, and acquiring the LAI inversion values of the image pixels under each spatial resolution by utilizing the updated state vector set matrix of the nodes. According to the method, LAIinversion values with complete spatial distribution and continuous time sequence under multiple spatial resolutions can be obtained through inversion, and the precision of the LAI inversion values isimproved.

Description

technical field [0001] The invention relates to the technical field of remote sensing information extraction, in particular to an LAI inversion method and device. Background technique [0002] Leaf Area Index (LAI) is an important parameter to describe vegetation canopy, which has a great influence on the research of plant biophysical process, global climate change, ecological model and material energy cycle. At present, in order to meet the LAI application requirements of time series and different spatial scales, the LAI is estimated mainly by fusing the satellite observation data of multiple sensors into the surface parameter remote sensing inversion process. [0003] Estimating LAI by fusing satellite observation data from multiple sensors into the remote sensing inversion process of surface parameters mainly refers to: using observation data with different remote sensing information obtained from different satellite sensors at the same time in the target area to assist e...

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/20
Inventor 詹旭琛肖志强
Owner BEIJING NORMAL UNIVERSITY
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