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In the past fifty years, satellite remote sensing has gradually developed into one of the most effective tools for measuring the Earth at the local, regional, and global spatial scales.
Remote sensing satellites have non-destructive characteristics for observing the Earth and can quickly monitor the atmosphere, the Earth's surface, and the ocean mixed layer. Additionally, satellite instruments can observe toxic or hazardous environments without putting personnel or equipment in danger. Large-scale continuous satellite observation supplements detailed ground observation data and provides unprecedented quantitative monitoring of volume and content elements for theoretical modeling and data assimilation.
Currently, many important industry applications rely on satellite data:
Atmospheric observation can be used for weather forecasting, environmental pollution monitoring, climate change, etc.
Ocean surface remote sensing is used for coastal dynamic monitoring, sea surface temperature and salinity, marine ecosystem and carbon biomass, sea level change, marine transportation and fisheries, shallow water flow and bathymetric surveying, etc.
Satellite remote sensing over land is used for mining resource exploration, water and drought monitoring, soil moisture, vegetation, forest logging, forest fires, agricultural monitoring, urban planning, etc.
Finally, social science work for global crisis investigation also benefits from remote sensing data sets, which can be used for target visualization, classifying the human environment, and then linking these observed results to various socio-economic data sets, and so on.
In addition, satellite remote sensing provides an effective tool for collecting Earth science information, such as:
Global terrain;
Atmospheric profiles of trace gases such as temperature, water vapor, and carbon dioxide;
Mineral and chemical compositions of the Earth's surface and atmosphere;
Properties of the cryosphere including ice, sea ice, glaciers, and melting pools;
Particles and electromagnetic properties of the thermosphere, ionosphere, and magnetosphere.
In the early stages of observation satellite development, satellite sensor design often had high target specificity.
For example, in the 1970s, a series of instruments were launched: land satellites and advanced very high resolution radiometers (AVHRR) were used to monitor land surfaces and clouds, total ozone mapping spectrometers (TOMS) were used to observe total column ozone, and high-resolution infrared radiation detectors (HIRS) were used for weather forecasting and climate monitoring. These satellites deployed specific data for each target subject and received recognition from respective academic fields.
As a result, these projects were extended for several years to obtain data records with significant climate significance, and professional organizations continuously improved technology and coordinated operations for new missions based on accumulated experience.
Between 1990 and 2010, the positive results of these missions encouraged countries and institutions to organize the design and launch of increasingly advanced satellites and instruments with wider observation ranges.
All of these previous efforts provided valuable knowledge that helped establish an understanding of the true value, limitations, and potential of satellite remote sensing. In fact, the elastic development of space remote sensing technology and the prosperity of spatial informatics have created unprecedented situations, and the limitations of hardware, data collection, and processing have been greatly weakened, with the ability to develop and deploy more advanced satellite sensor designs.
In addition, the scientific community has obtained a large amount of satellite data, accumulated rich experience in managing and analyzing data, has a realistic understanding of the achievements that can be made using existing satellite data sets, and has mastered the necessary steps to improve the practicality of satellite data in the future.
On the other hand, the space industry is also aware that the fundamental challenge of remote sensing observation will never end. For example, the separation of signal and noise to retrieve a specific set of geophysical variables and accurate instrument calibration is an ongoing challenge; technological advances have improved the information content of observations, but data is never sufficient to uniquely describe all Earth physics parameters of interest; as science progresses, the list of observable objects needed continues to grow.
Therefore, satellite remote sensing is still a fundamentally indeterminate problem that requires appropriate definition and restraint through theoretical models, prior knowledge, and auxiliary observations. These are important considerations in designing new scientific objectives.