The Essence and Fundamental Issues of Remote Sensing Science: A Systematic Study of Three Characteristics and Five Effects

The Essence and Fundamental Issues of Remote Sensing Science: A Systematic Study of Three Characteristics and Five EffectsOn March 5th, the Chinese Academy of Sciences (CAS) website announced the publication of a paper titled "The Essence and Fundamental Issues of Remote Sensing Science" by researcher Zhang Bing from the Aerospace Information Research Institute of CAS, in the Journal of Remote Sensing. Starting from the physical foundations of remote sensing science, the paper systematically summarizes the basic laws governing the interaction between objects and electromagnetic waves

The Essence and Fundamental Issues of Remote Sensing Science: A Systematic Study of Three Characteristics and Five Effects

• On March 5th, the Chinese Academy of Sciences (CAS) website announced the publication of a paper titled "The Essence and Fundamental Issues of Remote Sensing Science" by researcher Zhang Bing from the Aerospace Information Research Institute of CAS, in the Journal of Remote Sensing. Starting from the physical foundations of remote sensing science, the paper systematically summarizes the basic laws governing the interaction between objects and electromagnetic waves. Based on this, it proposes three characteristics and five effects of remote sensing science. This article, from a methodological perspective, presents for the first time a systematic framework for fundamental theoretical research in remote sensing science, providing crucial theoretical support for the innovative development and application of remote sensing technology.

Since the 1960s, remote sensing science and technology have flourished, becoming core technological tools for Earth system science research and spatial information applications. In recent years, the rise of artificial intelligence, particularly deep learning, has profoundly changed the paradigm of remote sensing data analysis and application, driving the rapid development of data-driven remote sensing research. In this new era, full of both opportunities and challenges, it is particularly important and urgent to delve into the essence and fundamental issues of remote sensing science. Researcher Zhang Bing's work directly addresses this crucial scientific question.

The core of the article lies in the in-depth discussion of the three characteristics and five effects of remote sensing science. This theoretical framework is not a simple summary of existing knowledge, but a deep exploration and systematic generalization of remote sensing physical mechanisms. The article argues that the three characteristics of remote sensing science are inherent manifestations of the physical and chemical properties of objects on the electromagnetic spectrum. These three characteristics profoundly reflect the essential features of the interaction between objects and electromagnetic waves.

These three characteristics are:

1. Radiation Characteristics: This refers to the overall radiation intensity of an object across a wide electromagnetic spectrum (e.g., visible light, infrared, microwave). Different objects have different radiation characteristics, providing an important basis for remote sensing object identification. For example, the radiation intensity of asphalt pavement is usually higher than that of vegetation, allowing us to distinguish between these two types of objects using remote sensing imagery. The strength of radiation characteristics is not only related to the physical and chemical properties of the object itself but is also affected by various factors such as solar radiation intensity, atmospheric conditions, and surface temperature.

2. Spectral Characteristics: Spectral characteristics refer to the differences in an object's ability to reflect or emit electromagnetic waves of different wavelengths. This difference can be described by a spectral curve, which is an important basis for remote sensing image analysis and object identification. Different objects have different spectral characteristics; for example, healthy vegetation has high reflectance in the near-infrared band, while withered vegetation has lower reflectance. This spectral difference is an important basis for remote sensing identification of different vegetation types. Spectral characteristics are also affected by various factors such as the internal structure, water content, and chemical composition of the object.

3. Temporal Characteristics: Temporal characteristics refer to the changes in the electromagnetic radiation or reflection characteristics of an object over different time periods. This change reflects the dynamic process of the object over time. For example, the growth and development process of crops will cause significant changes in their spectral characteristics, providing important information for crop growth monitoring. Temporal characteristics are also affected by seasonal changes, climatic conditions, and human activities. Studying temporal characteristics helps us better understand the dynamic changes of objects and provides a basis for predicting future changes.

In addition to the three characteristics, the article systematically elaborates on the five effects of remote sensing science. These effects describe the expression of remote sensing features of objects formed by various observation modes and conditions during the remote sensing imaging process. These five effects are interconnected and jointly affect the quality of remote sensing images and the accuracy of information extraction.

These five effects are:

1. Scale Effect: The scale effect refers to the influence of the spatial resolution of a remote sensing image on the expression of object features. Different spatial resolutions will present different levels of object detail. High-resolution images can display more detailed information, while low-resolution images can only display larger object units. The scale effect is an important consideration in remote sensing image interpretation and information extraction, requiring the selection of appropriate spatial resolution based on different application needs.

2. Atmospheric Effect: The atmospheric effect refers to the influence of the atmosphere on the propagation of electromagnetic waves. Gases and aerosols in the atmosphere absorb, scatter, and attenuate electromagnetic waves, affecting the quality of remote sensing images. Atmospheric effects can cause image blurring and distortion, requiring atmospheric correction to obtain high-quality remote sensing images. The complexity of atmospheric effects makes its correction a significant challenge in remote sensing data processing.

3. Angle Effect: The angle effect refers to the influence of the observation angle on the expression of object features. Different observation angles will cause changes in the spectral and geometric characteristics of objects. The angle effect is caused by factors such as the sun's illumination angle and observation angle, affecting the brightness and contrast of remote sensing images, and requiring corresponding corrections in image processing. A deep understanding of the angle effect is beneficial for improving the quality and accuracy of remote sensing images.

4. Proximity Effect: The proximity effect refers to the influence of the surrounding environment on the expression of object features. The remote sensing characteristics of an object depend not only on the nature of the object itself but also on the surrounding environment. For example, the remote sensing characteristics of a field will be affected by surrounding vegetation and soil. The proximity effect can cause image confusion, requiring corresponding processing during image processing. The complexity of the proximity effect requires more refined models to describe the interaction between objects.

5. Transmission Effect: The transmission effect refers to the influence of the remote sensor imaging mechanism on the expression of object features. Different remote sensors have different imaging mechanisms, which will affect the way object features are expressed. For example, different sensors have different sensitivities to different wavebands, which will affect the spectral information of remote sensing images. The transmission effect is caused by the characteristics of the remote sensor itself and various factors during the imaging process. Understanding the transmission effect is crucial for the correct interpretation of remote sensing data.

Researcher Zhang Bing's work systematically summarizes and elaborates on the three characteristics and five effects of remote sensing science, providing directional guidance for the acquisition, processing, and application of remote sensing data and laying a systematic and standardized foundation for the future innovative development of remote sensing science. This article has not only significant theoretical significance but also important practical guiding significance, promoting the further development of remote sensing science and technology. The publication of this research result marks significant progress in China's fundamental theoretical research in remote sensing science.

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