Open AccessAutomatic Analysis And Intelligent Information Extraction Of Remote Sensing Big Data
Author(s) -
Ge Li,
Jiajun Li
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1616/1/012003
Subject(s) - big data , computer science , information extraction , extraction (chemistry) , data science , data extraction , data mining , remote sensing , information retrieval , geography , medline , political science , chromatography , chemistry , law
Aiming at the problems of low analysis accuracy, incomplete information extraction and low quality of traditional remote sensing data automatic analysis and extraction methods, a new remote sensing big data automatic analysis and intelligent information extraction method is proposed. Automatic analysis of remote sensing big data is realized through the expression, retrieval and understanding of remote sensing big data, and intelligent information extraction is carried out on the basis of automatic analysis of remote sensing big data. According to the procedures of remote sensing data mining, data preprocessing, feature acquisition, target recognition and evaluation, intelligent information extraction can be realized by utilizing the good learnability of convolutional neural network. In order to verify that the proposed method is superior to the traditional method, six different experimental areas are used as experimental objects, and a comparative experiment is designed. Experimental results: The proposed method automatically analyzes and extracts the remote sensing data, which is superior to the traditional method in terms of integrity, correctness and quality.