Object-oriented unmanned aerial vehicle high-resolution image coal fire region land cover classification method

A classification method and object-oriented technology, applied in the direction of computer parts, instruments, characters and pattern recognition, etc., can solve the problems of low classification accuracy, difficulty in distinguishing features in coal fire areas, difficulty in land cover classification, etc., and achieve resolution The effect of high rate, uniform and rich color, and small seams

Active Publication Date: 2018-03-09
INST OF DISASTER PREVENTION
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Problems solved by technology

Dust pollution in mining areas and the impact of various surface disasters make the surface conditions of coal fire areas in mining areas extremely complicated. Some scholars have used traditional classification methods to carry out

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  • Object-oriented unmanned aerial vehicle high-resolution image coal fire region land cover classification method
  • Object-oriented unmanned aerial vehicle high-resolution image coal fire region land cover classification method
  • Object-oriented unmanned aerial vehicle high-resolution image coal fire region land cover classification method

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Embodiment Construction

[0033] The present invention will be further described below through specific embodiments and accompanying drawings. The embodiments of the present invention are for better understanding of the present invention by those skilled in the art, and do not limit the present invention in any way.

[0034] An object-oriented land cover classification method for coal fire areas with high-resolution UAV images, the specific steps are as follows:

[0035] 1) UAV image acquisition and data processing:

[0036] A four-rotor UAV is equipped with a SONY ILCE-6000 digital camera. The focal length of the digital camera is 20mm, the pixel size is 3.9μm, and the effective pixels are 24 million. There are 4 flight routes, and the flight altitude is 200m. 80% and 60%, a total of 62 true-color images were collected, and 5 aerial survey marker boards were placed in the survey area during the flight, and the center coordinates of the marker boards were measured by RTK as ground control points (GCP)...

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Abstract

The invention relates to the field of high-resolution remote sensing image land classification, in particular to an object-oriented unmanned aerial vehicle high-resolution image coal fire region landcover classification method. The method comprises the main steps that on the basis of coal fire region high-resolution color images collected by an unmanned aerial vehicle, homogenous objects are divided through an image multi-resolution segmentation algorithm to construct an expert knowledge base adopting spectral signatures, shape features, textural features and height information as main parts,and high-precision classification of a coal fire region is achieved by means of a rule set and the most adjacent classification method, wherein the classification precision is much higher than that of a traditional pixel-based classification method. The requirement for complex coal ire region land cover precise classification is met.

Description

technical field [0001] The invention relates to the field of land classification of high-resolution remote sensing images, in particular to an object-oriented method for classifying land cover in coal fire areas with high-resolution images of drones. Background technique [0002] Compared with satellite and airborne remote sensing equipment, UAV, as a new type of remote sensing platform, has the advantages of short flight time, low flight altitude, flexible and convenient operation, low acquisition cost, and high resolution of acquired images. It is a traditional aerial photogrammetry method. It is a beneficial supplement to the system, and is widely used in the fields of topographic map production, disaster emergency management, confirmation of rural land rights, and urban 3D modeling. [1,2] . High-resolution UAV images contain more accurate spatial position information, richer geometric information and texture information, and easier to identify attribute information of g...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/34G06K9/62
CPCG06V20/13G06V10/267G06F18/241G06F18/214
Inventor 李峰卫爱霞
Owner INST OF DISASTER PREVENTION
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