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Forest aboveground biomass estimation method based on Landsat time sequence modeling

A time series modeling and biomass technology, applied in the field of remote sensing inversion, can solve the problems of poor spatiotemporal continuity of data, susceptible to noise interference, poor estimation accuracy, etc. Effect

Active Publication Date: 2021-03-12
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0005] Aiming at the problems that the existing AGB estimation model based on single-temporal optical data has poor data temporal-spatial continuity, easy saturation, susceptible to noise interference, and poor estimation accuracy, the present invention Provides a forest AGB estimation method based on optical data time series modeling, and uses Landsat data as an example to explain the method

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  • Forest aboveground biomass estimation method based on Landsat time sequence modeling
  • Forest aboveground biomass estimation method based on Landsat time sequence modeling
  • Forest aboveground biomass estimation method based on Landsat time sequence modeling

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Embodiment Construction

[0027] Below in conjunction with specific embodiment and description accompanying drawing, the method for estimating aboveground biomass of forest based on time series Landsat provided by the present invention will be further described:

[0028] (1) Dataset introduction

[0029]The measured biomass data set is The Biomass Plot 142Library data, an on-site biomass inventory database compiled and published by TERN2. The database is mainly distributed across Australia and collects stem inventory data from federal, state and local government departments, universities, private companies and other institutions. The main spatial resolution is 0.05-1ha, the spatial coverage is 110.00to 155.001329E,-10.0 0to-45.000512N, and the spatial reference is WGS84. A total of 7771 points were collected for the sampling time after 2000, and an additional 5759 expansion points (with an AGB of 0 tons / ha) were added. The long-term series Landsat data set is obtained through the GEE platform, and th...

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Abstract

The invention discloses a forest aboveground biomass estimation method based on Landsat time sequence modeling, belongs to the technical field of remote sensing inversion, and particularly relates toa forest aboveground biomass estimation method. Aiming at the problems of poor data space-time continuity, easy saturation, easy noise interference, poor estimation precision and the like of an existing AGB estimation model based on single-temporal optical data, the invention provides the forest AGB estimation method based on optical data time sequence modeling, and takes Landsat data as an example to develop method description. According to the method, forest time sequence change parameters are innovatively introduced into AGB estimation, and a set of complete AGB estimation index system is constructed, so that the noise influence is effectively reduced, the saturation problem is relieved, the forest AGB estimation precision and universality based on optical data are improved, and technical support is provided for large-scale forest AGB estimation.

Description

technical field [0001] The invention belongs to the technical field of remote sensing inversion, in particular to a method for estimating aboveground biomass of forests. Background technique [0002] Forest aboveground biomass is an important parameter to characterize forest carbon storage. Accurate estimation of forest aboveground biomass is of great significance for in-depth research on forest succession, human activities, natural disturbance and climate change. The traditional aboveground biomass monitoring method is mainly realized by field measurement. Although this method has high precision, it is time-consuming, labor-intensive, and costly. The sampling is usually discrete and sparse, and it is difficult to cover a large area. As a new means of data acquisition, remote sensing technology has made it possible to monitor large-scale changes due to its advantages of wide coverage, short data acquisition cycle, low cost, and not limited by time and space. [0003] At pre...

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Application Information

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IPC IPC(8): G06F30/27G01S17/89G01S7/48G01N21/55G01N21/17
CPCG06F30/27G01S17/89G01S7/4802G01N21/17G01N21/55G01N2021/1793Y02A90/10
Inventor 何彬彬刘霞廖展芒
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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