The cross time and space features in remote sensing applications

J. X. Lu; W. L. Song; W. Qu; J. E. Fu; Z. G. Pang

doi:10.1117/12.2204738

6 August 2015 The cross time and space features in remote sensing applications

J. X. Lu, W. L. Song, W. Qu, J. E. Fu, Z. G. Pang

Proceedings Volume 9669, Remote Sensing of the Environment: 19th National Symposium on Remote Sensing of China; 96690J (2015) https://doi.org/10.1117/12.2204738
Event: Remote Sensing of the Environment: 19th National Symposium on Remote Sensing of China, 2014, Xian City, China

Abstract

Remote sensing is one subject of the modern geomatics, with a high priority for practical applications in which cross time and space analysis is one of its significant features. Object recognition and/or parameter retrieval are normally the first step in remote sensing applications, whereas cross time and space change analysis of those surface objects and/or parameters will make remote sensing applications more valuable. Based on a short review on the historic evolution of remote sensing and its current classification system, the cross time and space features commonly existing in remote sensing applications were discussed. The paper, aiming at improving remote sensing applications and promoting development of the remote sensing subject from a new vision, proposed a methodology based subject classification approach for remote sensing and then suggest to establish the theory of cross time and space remote sensing applications. The authors believe that such a new cross time and space concept meets the demand for new theories and new ideas from remote sensing subject and is of practical help to future remote sensing applications.

Citation Download Citation

J. X. Lu, W. L. Song, W. Qu, J. E. Fu, and Z. G. Pang "The cross time and space features in remote sensing applications", Proc. SPIE 9669, Remote Sensing of the Environment: 19th National Symposium on Remote Sensing of China, 96690J (6 August 2015); https://doi.org/10.1117/12.2204738

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KEYWORDS

Remote sensing

Data modeling

Process modeling

Geographic information systems

Photography

Sensors

Data acquisition

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