Remote sensing imaging principle-based earth surface vegetation distribution recognition method

Abstract

The invention relates to a remote sensing imaging principle-based earth surface vegetation distribution recognition method, which comprises the steps of performing region detection through a sensor, obtaining a remote sensing image, and segmenting the remote sensing image to obtain sub-image information; finding a sub-image convergence point of each piece of sub-image information by utilizing filtering processing, and determining sub-image features; utilizing the sub-image features to establish a network model, training the network model of each sub-image, and uploading a training result to acloud server; after the sub-image network models are trained, combining the sub-image network models to obtain a network model of the remote sensing image; analyzing the distribution areas of different vegetations according to the network model of the remote sensing image, establishing the distribution characteristics of different vegetations, and uploading the distribution area characteristics ofdifferent vegetations through a gateway; analyzing the characteristic index weights of different vegetations in the region, obtaining vegetation distribution information, and obtaining result information; and displaying the result information in a predetermined manner.

Description

technical field [0001] The invention relates to the field of surface vegetation identification or big data processing, in particular to a method for identifying the distribution of surface vegetation based on the principle of remote sensing imaging. Background technique [0002] At present, remote sensing technology has been widely used in agriculture, forestry, surveying and mapping, meteorology, transportation, land and resources exploration and other fields. A technology that detects and receives information from a target object from a distance through instruments or sensors, and identifies the attributes and distribution of objects through information transmission and analysis. [0003] Blockchain (Blockchain) is an important concept of Bitcoin. It is essentially a decentralized database. At the same time, as the underlying technology of Bitcoin, it is a series of data blocks generated using cryptographic methods. The data block contains a batch of Bitcoin network trans...

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Problems solved by technology

[0003] Blockchain (Blockchain) is an important concept of Bitcoin. It is essentially a decentralized database. At the same time, as the underlying technology of Bitcoin, it is a series of data blocks associated with cryptographic methods. Each The data block contains a batch of bitcoin network transaction information, which is used to verify the validity of the information (anti-counterfeiting) and generate the next block, combining blockchain technology with remote sensing imaging for regional surface vegetation identification and monitoring, It can realize the efficiency of detection and the security of monitoring data. During the monitoring process, the data transmission is automatically identified and transmitted through the Internet of Things to ensure the rapidity of data transmission. Most of the distribution of solar panels in the existing detection area is through unmanned monitoring. In the process of aerial photography, due to the influence of factors such as pixels or weather, the quality of the shooting picture is relatively high, and the error is relatively large. In order to be able to accurately analyze the distribution area and distribution characteristics of the surface vegetation, we carried out For regional detection, in order to better carry out regional planning, and analysis of vegetation distribution or vegetation growth characteristics, it is necessary to develop a matching system for detection and accurately obtain the distribution of solar panels, but in the detection process, how to Realizing accurate detection and how to process the detection results during the detection process are urgent problems to be solved

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