Development Status and Prospects of Hyperspectral Remote Sensing Technology in my country

Hyperspectral remote sensing technology  

Hyperspectral remote sensing is a technique that uses a narrow and continuous range of spectral channels to continuously image ground features. It is developed based on imaging and spectroscopy. Compared to ground-based radiometers, hyperspectral remote sensing acquires spectral measurements over a continuous spatial area, rather than at a single point, allowing for the simultaneous acquisition of both image and spectral information of the target. Compared to traditional remote sensing, hyperspectral resolution imaging spectrometers provide a very narrow imaging band for each pixel, achieving resolutions on the order of nanometers, with tens or even hundreds of spectral channels, often continuously connected.

Compared with traditional remote sensing, hyperspectral remote sensing can obtain more spectral spatial information and can provide a wider range of applications in Earth observation and environmental surveys. This is mainly reflected in the following aspects: the ability to distinguish and identify ground features is greatly improved, the number of imaging channels is greatly increased, and the transformation of remote sensing from qualitative analysis to quantitative or semi-quantitative analysis becomes possible.

Current Status of Hyperspectral Remote Sensing Technology Development in my country

my country's hyperspectral remote sensing technology started relatively late, but driven by the country's growing and urgent social and economic needs, both airborne and spaceborne remote sensing have gained unprecedented development opportunities and have developed rapidly.

2002.3.25

On March 25, 2002, the Shenzhou-3 spacecraft carried a medium-resolution imaging spectrometer independently developed by my country, making China the second country to send a hyperspectral payload into space, after the United States carried an imaging spectrometer on its Terra satellite in the Earth Observation System.

2007.10.24

On October 24, 2007, the Chang'e-1 lunar probe satellite was launched, and the imaging spectrometer was also put into lunar orbit as a major payload. This was my country's first space interferometric imaging spectrometer based on Fourier transform.

2008.9.6

The HJ-1A satellite was successfully launched on September 6, 2008, from the Taiyuan Satellite Launch Center along with the HJ-1B satellite in a "one rocket, two satellites" launch. It carries a hyperspectral imager and has been widely used in atmospheric monitoring, urban change monitoring, and marine applications.

2011.9.29

Launched on September 29, 2011, the Tiangong-1 target spacecraft carried a hyperspectral imager independently developed by my country. Utilizing the spectral data from Tiangong-1, significant applied research was conducted in areas such as land resources, oceanography, forestry, urban environmental monitoring, and hydrological and ecological monitoring, yielding a number of valuable application results.

2018.5

In May 2018, Gaofen-5 was successfully launched. It is my country's first hyperspectral comprehensive observation satellite, currently the most advanced hyperspectral detection satellite, and also the satellite with the most payloads, highest spectral resolution, and greatest development difficulty in the national "Gaofen Project." The satellite operates in geostationary orbit and is used to acquire hyperspectral resolution remote sensing data samples from the ultraviolet to long-wave infrared spectral bands.

2019.9

In September 2019, the five satellites of the "Zhuhai-1" 03 group were successfully launched into their predetermined orbits by a Long March-11 carrier rocket from the Jiuquan Satellite Launch Center. The 03 group includes four hyperspectral satellites and one 0.9m resolution video satellite. Six more hyperspectral satellites will be launched subsequently, forming a constellation of 10 hyperspectral satellites. This constellation can shorten the revisit cycle, improve the efficiency of dynamic observation, and enable rapid response in monitoring the Earth's surface environment.

2021.9

At 11:01 AM on September 7, 2021, the Taiyuan Satellite Launch Center in my country successfully launched the Gaofen-5 02 satellite into space using a Long March-4C carrier rocket. The satellite carries seven remote sensing instruments. Once operational, it will be used for national pollution reduction, environmental quality monitoring, atmospheric composition and climate change monitoring, and will conduct application demonstrations of hyperspectral remote sensing monitoring of pollutants, regional ambient air quality, atmospheric composition, and climate change.

Currently, China has successfully established and developed its own airborne and satellite remote sensing Earth observation system, which is widely used in the fields of resources and environment, playing an important role in land, vegetation and water resource surveys and management, geological and mineral resource surveys, and disaster monitoring.

Outlook for Hyperspectral Satellite Technology  

The detection band has been further broadened.：Temporal/spatial/spectral resolution further improved

In its early stages, the primary development goal of hyperspectral remote sensing technology was to improve spectral resolution to meet the needs of high-precision, quantitative remote sensing. With advancements in large-area, high-resolution detector technology, while continuing to improve spectral resolution, has begun to evolve towards higher spatial resolution.

Currently, various hyperspectral remote sensing satellite systems exist internationally, covering the detection bands from visible light to thermal infrared, with spectral resolution reaching the nanometer level and the number of bands increasing to hundreds. This significantly enhances the ability to acquire remote sensing information, enabling precise analysis of the solid and liquid chemical components of the Earth's surface. To further study gaseous components and atmospheric properties, the demand for even higher spectral resolution has become an unstoppable trend in the development of hyperspectral remote sensing.

On the other hand, in order to conduct remote sensing observations more accurately and quickly, and to obtain reliable and timely remote sensing data, The new characteristics of hyperspectral remote sensing technology—high spatial resolution, high spectral resolution, and high temporal resolution—are becoming increasingly apparent, enabling it to adapt to new application areas such as long-term weather forecasting, precision agricultural monitoring, quantitative land and marine resource surveys, and real-time battlefield environment analysis.

New principles and new solutions are constantly being proposed.：The types of hyperspectral remote sensing technologies have been further enriched.

With the development and advancement of information technology, imaging technology, and optical processing technology, various new hyperspectral remote sensing technologies and solutions are emerging in an endless stream. Their core spectroscopic elements are evolving from mature dispersive and interferometric types to a more diversified approach. Currently, various spectroscopic principle schemes have emerged, including rotating filter type, acousto-optic tuned filter type, liquid crystal tuned filter type, and computational tomography type.

In recent years, snapshot imaging spectroscopy has developed rapidly. It can acquire complete three-dimensional image spectral data within a single exposure time, showing great promise for real-time detection. Encoded aperture imaging spectroscopy is a novel snapshot imaging spectroscopy technique that applies compressed sensing theory to imaging spectrometers. It uses coded patterns to modulate spatial information of all wavelengths, records an intensity map of the target's spatial and spectral information mixed and encoded on an area array detector, and finally extracts spatial and spectral information from the intensity map using a multi-scale reconstruction algorithm. Three-dimensional imaging spectroscopy utilizes an image segmentation element composed of multiple long strip mirrors with different tilt angles to cut the target image into images at different angles. These images are then transmitted to a lens array via a dispersive prism, thus obtaining dispersive spectra of images at different angles on a large area array detector. This technique is also a snapshot imaging spectroscopy technique.

Integrated acquisition of multi-dimensional information including images, spectra, and polarization

Hyperspectral remote sensing technology can achieve integrated acquisition of spectral and image information of targets, meeting the needs for detecting the chemical composition and morphological features of ground objects. However, in some other application scenarios, such as observing the surface characteristics of targets, identifying and tracking hidden targets, and detecting aerosols, especially for distant targets made of the same materials (such as satellites and missiles), imaging spectroscopy technology will lose its detection function. In these cases, polarization information detection can play a crucial role.

Polarization information has a significant ability to identify the corner features and surface roughness of a target, and can better describe the scattering and reflection characteristics of a substance. Introducing polarization information into hyperspectral remote sensing technology enables the integrated acquisition of multi-dimensional information such as images, spectra, and polarization, providing more scientific, accurate, and comprehensive detection technologies and methods for target detection, identification, and confirmation.In the process of target detection and cognition, images, spectra, and polarization states of the same target can provide complementary multivariate information, helping to analyze the target's rich physicochemical properties, thereby achieving a more comprehensive, accurate, and scientific understanding of the target. It has important applications in atmospheric sounding, water quality monitoring, target identification, and military reconnaissance. Conducting research on the integrated acquisition of image, spectral, and polarization multivariate information and the application of polarization hyperspectral remote sensing technology is currently an important direction for the development of hyperspectral remote sensing technology.

The era of intelligent hyperspectral remote sensing and big data is coming.

Current hyperspectral remote sensing satellites are primarily controlled from the ground. Massive amounts of hyperspectral remote sensing data are stored and compressed onboard before being transmitted back to ground receiving stations. Finally, ground-based data processing yields remote sensing products. Furthermore, satellite parameters are fixed and cannot be flexibly adjusted. With the advent of the "artificial intelligence" era, combining neural networks, machine learning, and other technologies with hyperspectral remote sensing to build "intelligent" hyperspectral remote sensing satellite systems—capable of automatic calibration and optimization of onboard hyperspectral imaging payload parameters, real-time processing of onboard data, and product generation—has become the future trend. "Intelligent" hyperspectral remote sensing satellites will possess intelligent information perception capabilities and adaptive adjustment capabilities, enabling them to generate high-quality data in real time according to user needs.

Meanwhile, as the resolution of hyperspectral imaging remote sensing instruments increases and the dimensions of information acquired increase, the amount of remote sensing data acquired is also growing explosively, exhibiting significant "big data" characteristics. How to effectively mine and extract information from hyperspectral remote sensing data, and improve data compression and data transmission efficiency are important issues that need to be addressed in the future of hyperspectral remote sensing.

Miniaturization and Lightweighting of Hyperspectral Remote Sensing Payloads

With the development of small unmanned aerial vehicle (UAV) remote sensing technology and micro/nano satellite technology, hyperspectral remote sensing is also developing towards lower cost, greater flexibility, integration, and stronger real-time performance. Currently, lightweight hyperspectral remote sensing technology based on small UAVs holds immense application potential and value in areas such as agricultural and forestry pest and disease observation, optical sorting of large cargo, security monitoring, target search, and disaster relief. Meanwhile, micro/nano satellites offer advantages such as low cost, high flexibility, low power consumption, and short development cycles, enabling them to conduct more complex space exploration missions.

The combination of hyperspectral remote sensing and micro/nano satellite technology will promote the innovative development of integrated multifunctional structures and comprehensive space exploration payloads.This will play a significant role in promoting the lightweight, integrated, and systematic development of future hyperspectral remote sensing, enabling space networking and all-weather real-time detection.

In recent years, the development of hyperspectral remote sensing technology has seen the implementation and application of many new principles, schemes, and technologies. The structure of hyperspectral imaging remote sensing instruments has become more rational and simpler, and their integrated acquisition capabilities for multi-source information have been greatly enhanced. They are gradually developing towards larger field of view, higher throughput, smaller size, static display, and higher resolution. Simultaneously, with the maturation of hyperspectral remote sensing technology, its cost will be significantly reduced, and the commercialization of hyperspectral remote sensing data products will be an important direction for future development.

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