Method for detecting spartina alterniflora distribution based on remote sensing big data and cloud platform

A technology of Spartina alterniflora and distribution method, which is applied in character and pattern recognition, instruments, calculation models, etc., can solve the problem that remote sensing technology cannot accurately detect the spatial and temporal distribution of Spartina alterniflora, and achieve improved accuracy and reliability, Accurate, repeatable and robust probing results

Active Publication Date: 2021-09-17
NORTHEAST INST OF GEOGRAPHY & AGRIECOLOGY C A S
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  • Application Information

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Problems solved by technology

[0004] In order to solve the problem that the existing remote sensing technology cannot accurately detect the temporal and spatial distribution of Spartina alterniflora, the present invention provides a method for detecting the distribution of Spartina alterniflora based on remote sensing big data and a cloud platform

Method used

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  • Method for detecting spartina alterniflora distribution based on remote sensing big data and cloud platform
  • Method for detecting spartina alterniflora distribution based on remote sensing big data and cloud platform
  • Method for detecting spartina alterniflora distribution based on remote sensing big data and cloud platform

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specific Embodiment approach 1

[0031] Specific implementation mode one: this implementation mode is based on remote sensing big data and cloud platform to detect the distribution method of Spartina alterniflora according to the following steps:

[0032] Step 1: Use the Google Earth Engine cloud platform to build a sample library: construct artificial sample points in the detection area, and merge them with the sample points collected in the wild to generate a sample library of Spartina alterniflora;

[0033] Step 2: On the Google Earth Engine cloud platform, construct the Sentinel-1 image set within the research time range, and filter out the VV and VH bands; then filter out the cloud cover less than 10% to get the Sentinel-2 image set, and filter out B2, B3, B4, B8, B11 and B12 bands;

[0034] Step 3: Use the ee.ImageCollection.median and ee.ImageCollection.clip commands to process the Sentinel-1 image set and Sentinel-2 image set in step 2 into two mean images with the study area as the boundary, and the ...

Embodiment 1

[0050] Embodiment 1 This embodiment is to use a specific implementation method to detect the spatial distribution of Spartina alterniflora in a rectangular range in the Yellow River Delta region in 2020, specifically combining figure 1 The flow chart is described in detail.

[0051] Step 1: Use the Google Earth Engine (GEE) cloud platform to build a sample library, which is to construct artificial sample points in the detection area, and merge them with the sample points collected in the wild to generate a sample library of Spartina alterniflora;

[0052] Step 2: On the Google Earth Engine cloud platform, construct the Sentinel-1 image set within the research time range (some areas of the Yellow River Delta in 2020), and filter out the VV and VH bands; then filter out the Sentinel images with cloud cover less than 10% -2 image set, simultaneously screen out the B2, B3, B4, B8, B11 and B12 bands; specifically: select the Sentinel-1SAR image in 2020 and the Sentinel-2MSI image f...

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Abstract

The invention relates to a method for detecting spartina alterniflora distribution, in particular to a method for detecting spartina alterniflora distribution based on remote sensing big data and a cloud platform. The method solves the problem that the precision of the existing remote sensing technology for identifying the spartina alterniflora is low, and realizes the spatio-temporal distribution detection of the spartina alterniflora from big data and a cloud platform. The method comprises the following steps: 1, generating a spartina alterniflora sample library; 2, generating two basic image sets; 3, fusing into a new basic feature image; 4, calculating seven parameters; 5, performing fusion to generate a new image; 6, modifying related segmentation parameters until a segmentation result is obtained; 7, obtaining a training sample and a verification sample; and 8, obtaining spatial distribution information of the spartina alterniflora. According to the invention, the problem of invasion space distribution of the spartina alterniflora is accurately and rapidly detected and obtained by applying the remote sensing technology, the detection result is accurate, the precision and credibility of remote sensing classification of the spartina alterniflora are improved, repeatability and robustness are achieved, and the method has extremely important significance for monitoring remote sensing mapping of the spartina alterniflora.

Description

technical field [0001] The invention relates to a method for detecting the distribution of Spartina alterniflora. Background technique [0002] Spartina alterniflora is a perennial grass plant that originated from the Atlantic coast of America and the Gulf of Mexico. Submerged and resistant to wind and waves, a single plant can reproduce nearly 100 plants per year. Therefore, many countries have widely introduced species according to their good reproductive ability and function of promoting siltation and land formation. Spartina alterniflora was introduced into my country in 1979 for wind protection and dike protection and increasing tidal flat vegetation distribution. With the continuous expansion of the Spartina alterniflora community, it quickly encroached on the niche of native native vegetation, resulting in a sharp decline in regional biodiversity and damage to the ecosystem. Therefore, quickly and accurately drawing the spatio-temporal distribution map of Spartina ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/34G06N3/00
CPCG06N3/006
Inventor 毛德华仇志强王宗明王铭贾明明
Owner NORTHEAST INST OF GEOGRAPHY & AGRIECOLOGY C A S
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