سابِق|تال

Research progress and trend of high-resolution remote sensing imagery intelligent interpretation

  • role： First author第一作者
  • Affiliation：

    National Quality Inspection and Testing Center for Surveying and Mapping Products State, Beijing 100830, China

  • Email：zhangjx@casm.ac.cn
  • Introduction：张继贤，1965年生，男，研究员，研究方向为摄影测量与遥感。E-mail：zhangjx@casm.ac.cn
ZHANG Jixian1,  
  • role： Corresponding author通信作者
  • Affiliation：

    Chinese Academy of Surveying and Mapping, Beijing 100830, China

  • Email：guhy@casm.ac.cn
  • Introduction：顾海燕，1982年生，女，副研究员，研究方向为遥感智能解译。E-mail：guhy@casm.ac.cn
GU Haiyan2*,  
  • Affiliation：

    Chinese Academy of Surveying and Mapping, Beijing 100830, China

YANG Yi2,  
  • Affiliation：

    National Quality Inspection and Testing Center for Surveying and Mapping Products State, Beijing 100830, China

ZHANG He1,  
  • Affiliation：

    Chinese Academy of Surveying and Mapping, Beijing 100830, China

LI Haitao2

ملخص

Remote sensing imagery interpretation is a continuously developing research direction. With the ever-changing needs of remote sensing applications, the rapid development of high-resolution remote sensing data, the accumulation of geographic knowledge, and the development of artificial intelligence, automated and intelligent classification technology should be urgently developed. This paper aims at the development of intelligent interpretation. First, the research progress is elaborated from three aspects: interpretation unit, classification method, and interpretation recognition. Then, a geographic scene-level overall framework for intelligent understanding of remote sensing imagery is presented. The framework includes geographic knowledge map construction, deep convolutional neural network model construction, and the semantic classification method based on geographic knowledge graph and deep learning model. The preliminary test results are provided. Lastly, the important development trend of intelligent understanding is projected. A geographic knowledge graph can realize formal description and reasoning calculation of geographic knowledge and improve the learning capability and the utilization rate of prior knowledge. Classification and related semantic information can also be obtained, which is helpful for in-depth cognition of geographic scenes. This study looks forward to expanding the ideas and methods for intelligent interpretation of remote sensing images and improving its fineness and intelligence. Intelligent interpretation can understand geospatial capabilities intelligently and promote in-depth transformation of data, information, knowledge, and intelligence.

مفهوم

intelligent interpretation;deep learning;geographic knowledge graph;high-resolution remote sensing imagery

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