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A peat swamp information extraction method based on envisat ASAR, Landsat TM and DEM data

A technology of information extraction and data, which is applied in the directions of instruments, character and pattern recognition, scene recognition, etc., can solve problems such as the difficulty in distinguishing peat bogs from other types of swamps, and achieve the effect of overcoming omission and misclassification

Active Publication Date: 2017-11-28
NORTHEAST INST OF GEOGRAPHY & AGRIECOLOGY C A S
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to solve the problem that it is difficult to distinguish peat swamps from other swamp types using traditional medium and low resolution optical remote sensing images, and propose a peat swamp information extraction method based on ENVISAT ASAR, Landsat TM and DEM data

Method used

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  • A peat swamp information extraction method based on envisat ASAR, Landsat TM and DEM data
  • A peat swamp information extraction method based on envisat ASAR, Landsat TM and DEM data
  • A peat swamp information extraction method based on envisat ASAR, Landsat TM and DEM data

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specific Embodiment approach 1

[0028] Embodiment 1: A peat swamp information extraction method based on ENVISAT ASAR, Landsat TM and DEM data in this embodiment is specifically prepared according to the following steps:

[0029] Step 1: Preprocessing the Landsat TM data;

[0030] Step 2: Preprocessing the ENVISAT ASAR data;

[0031] Step 3: Resample the ENVISAT ASAR data preprocessed in Step 2 in ArcGIS. The resampled ENVISAT ASAR data has the same grid size as the Landsat TM data processed in Step 1;

[0032] Step 4: Based on the preprocessed Landsat TM data, compare the preprocessed Landsat TM data and the resampled ENVISAT ASAR data in the ArcGIS software, and use the function of adding control points provided by the Georeferencing module of the ArcGIS software Select the control points on the preprocessed Landsat TM data, and register the resampled ENVISAT ASAR data according to the control point space to obtain the ENVISAT ASAR image;

[0033] Step 5: Use the Aspect command in Surface Analysis under ...

specific Embodiment approach 2

[0046] Specific implementation mode two: the difference between this implementation mode and specific implementation mode one is: in step one, LandsatTM data is carried out to the preprocessing process as follows:

[0047] (1) Within the distribution range of the peat bog, determine the track number of the Landsat TM data of the peat bog, and download the Landsat TM data covering the distribution range of the peat bog according to the track number;

[0048] (2) In order to eliminate terrain distortion, the Landsat TM data is orthorectified by using the DEM data of the corresponding area of ​​the Landsat TM data to obtain the Landsat TM data after orthorectification;

[0049] (3) In order to eliminate geometric distortion, use terrain data, select ground control points in ERDAS software, and perform geometric fine correction on Landsat TM data after orthorectification to obtain preprocessed Landsat TM data. Other steps and parameters are the same as those in Embodiment 1.

specific Embodiment approach 3

[0050] Specific implementation mode three: the difference between this implementation mode and specific implementation mode one or two is: in step 2, ENVISAT ASAR data is carried out preprocessing process:

[0051] (1) Within the coverage of the Landsat TM data range, download the ENVISAT ASAR fine image first-level data (ENVISAT ASAR APP Level 1B data) used in the test (the polarization mode is HH and HV);

[0052] (2) Carry out radiometric calibration on ENVISAT ASAR fine image first-level data, that is, convert the DN value of ENVISAT ASAR fine image first-level data into backscatter coefficient (in dB), and obtain radiometrically corrected ENVISAT ASAR data; its radiometric calibration The formula is as follows:

[0053]

[0054] in, is the backscatter coefficient of the pixel in row i and column j; DN ij is the original intensity value of the pixel in row i and column j; θ ij is the radar wave incidence angle of the i-th row and j-th column pixel; K is the absolute...

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Abstract

A peat swamp information extraction method based on ENVISAT ASAR, Landsat TM and DEM data, the invention relates to a peat swamp information extraction method. The invention solves the problem that traditional methods are difficult to distinguish peat bogs from other types of swamps. The method uses 1 to preprocess Landsat TM data; 2 to preprocess ENVISAT ASAR data; 3 to resample ENVISAT ASAR data; 4 to obtain ENVISAT ASAR images; 5 to obtain Slope data; 6. Extract the backscatter coefficient; 7. Determine the best polarization mode band of ENVISAT ASAR image; 8. Obtain the segmentation unit; 9. Extract characteristic parameters; 10. Determine the best classification band; Vector file; 13 steps to make a peat bog map. The invention is applied to the field of peat swamp information extraction.

Description

technical field [0001] The invention relates to an information extraction method, in particular to a peat swamp information extraction method. Background technique [0002] Peat swamp is one of the main types of wetlands, which plays an important role in maintaining regional ecological balance and sustainable development. In addition, due to the huge carbon storage in peat swamps, accounting for about 1 / 3 of the global terrestrial carbon pool, equivalent to 75% of the carbon content in the atmosphere, peat swamps play a pivotal role in global climate change and ecosystem balance status. In recent years, experts and scholars at home and abroad have used different remote sensing image data to study the spatial information extraction of wetland types such as herbaceous wetlands, forest wetlands, and coastal mangrove wetlands. Relatively small. [0003] Optical remote sensing data has the advantages and characteristics of rich spectral information, high cost performance, easy...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/46
CPCG06V20/13
Inventor 路春燕王宗明毛德华
Owner NORTHEAST INST OF GEOGRAPHY & AGRIECOLOGY C A S
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