Development of hyperspectral imaging remote sensing technology
- Vol. 25, Issue 1, Pages: 439-459(2021)
Published: 07 January 2021
DOI: 10.11834/jrs.20210283
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Published: 07 January 2021 ,
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刘银年.2021.高光谱成像遥感载荷技术的现状与发展.遥感学报,25(1): 439-459
Liu Y N. 2021. Development of hyperspectral imaging remote sensing technology. National Remote Sensing Bulletin, 25(1):439-459
高光谱成像技术可同时获取地物的几何、辐射和光谱信息,集相机、辐射计和光谱仪能力于一体,相比光学空间二维成像,可对地物进行空间和光谱三维成像,在一定的空间分辨率下,获取宽谱段范围内地物独特的连续特征光谱,对地物的精细分类和识别具有突出的优势,目前已成为对地遥感的重要前沿技术手段,在自然资源调查、生态环境监测、农林牧渔、海洋与海岸带监测等领域发挥着越来越重要的作用。随着高光谱遥感应用的深入研究,对高光谱成像遥感仪器的光谱范围、幅宽、光谱分辨率、空间分辨率、时间分辨率与定标精度等指标提出了新的要求。同时满足这些相互制约的参数指标,是国内外高光谱载荷研制中一直难以突破的技术难点。本文主要对国内外的高光谱成像遥感载荷技术进行了综述,介绍了国内外典型的机载、星载高光谱成像遥感仪器,以及近年来发射、正在研制和计划发展的星载高光谱成像载荷,并分析了这些载荷的技术方案、性能指标和应用效果;介绍了声光调谐(AOTF)、液晶调谐(LCTF)、法布里—珀罗调谐(FPTF),渐变式(LVF)和阶跃式(ISF)光楔滤光片,压缩感知光谱成像等新型分光技术,并分析了它们各自的技术优缺点以及应用于高光谱成像的可行性和现状;最后展望了高光谱成像载荷技术的发展趋势。
Hyperspectral remote sensing technology can acquire an object’s geometric
radiation
and spectral information. This technology is an important technique in Earth observations and is increasingly becoming important in applications of natural resource survey
environment and disaster monitoring
precision agriculture
oceans and costal monitoring
and urban planning. In the past decades
several advanced hyperspectral imaging systems from airborne (e.g.
AVIRIS
Hymap
OMIS
and PHI) to spaceborne (e.g.
EO-1/Hyperion and PROBA/CHRIS) platforms have been designed
built
and operated globally. On the one hand
airborne hyperspectral imager has been developed into commercial operation stage. Examples of international companies that develop airborne systems are Spectra Vista Corporation of America
Specim of Finland
and ITRES Research of Canada. On the other hand
GF-5/AHSI
which is a pioneer in Chinese spaceborne hyperspectral imager
has first realized wide spectrum
wide swath width
and high detection sensitivity. It marks a new era ever since the appearance of EO-1/Hyperion in 2000.
In the future
the outlook for hyperspectral remote sensing technique is as follows:
(1) The development of large-scale plane array detector
optical machining detection
and signal processing has improved not only the spectral resolution but also the spatial resolution and swath width of hyperspectral imaging. Hyperspectral imager’s spectrum range will cover from UV to LWIR to obtain more abundant spectral information of ground objects
all-day reflectance
and emission spectral characteristics. In addition
the integrated calibration methods of laboratory
in-orbit
and the Earth
the Sun
the Moon
the cold air
and the stars are becoming increasingly abundant and refined to ensure the application efficiency of hyperspectral imager at higher performance. The hyperspectral imaging technology with super wide width and higher resolution also puts forward higher requirements for the further development of large-scale detectors and large-aperture optics with wide working band range.
(2) The development of information
imaging
and optical processing technology has introduced new beam splitting technologies and developed the core beam splitting elements from the mature dispersion and interference type to the diversified direction. Many novel optical splitting schemes
such as Acousto-optic Tunable Filter (AOTF)
Liquid Crystal Tunable Filter (LCTF)
Linear Variable Filter (LVF)
Integrated Stepwise Filter (ISF)
Tunable Fabry-Perot Filter (TFPF) and computational spectral imaging system based on compressed sensing
are available at present. These spectroscopic image methods are still in the stage of laboratory experiments. An increasing attention has also been paid to the chip-level hyperspectral spectroscopy
which combines light splitting with photoelectric conversion.
(3) With the advances in the “artificial intelligence
” machine learning data process
such as neural network and deep learning
has become a trend with hyperspectral imaging to construct an ‘intelligent’ hyperspectral remote sensing satellite system. This technology will integrate the ability of automatic optimization of onboard load parameters and automatic real-time processing of onboard data and product generation. Meanwhile
the amount of remote sensing data obtained is explosively growing with the increase in resolution and information dimensions of hyperspectral imaging instruments. “Big data” feature is significant. Data transmission is an important issue in successfully using the effective data mining and information extraction and improving the efficiency of data compression in the future.
(4) The development of small UAV and micro-nano satellite technology has developed hyperspectral imaging toward a low-cost
flexible
integrated
and real-time technology. At present
the light and small hyperspectral imaging technology based on small UAV is greatly demanded and valuable in the fields of agricultural
forestry diseases and insect pests’ detection
target search
and rescue and relief. Micro-nano satellites have low cost and short development cycle and can conduct complex space remote sensing tasks. The combination of hyperspectral imaging and micro-nano satellite technologies will promote the integration of multi-functional structure and space exploration payload. Lightweight
integrated
and systematized hyperspectral remote sensing with space networking and all-time detection will play an important role in the future. It will provide the possibility for hyperspectral remote sensing satellites to enter the commercial field.
Many new principles
schemes
and technologies are being implemented and applied in hyperspectral imaging. The integrated acquisition and processing ability of multiple information is also greatly enhanced. The hyperspectral load is gradually developing in the direction of large field of view
large relative aperture
high resolution
and high quantification. The cost of hyperspectral remote sensing technology will be greatly reduced with its continuous development and maturity. The commercial application of this technology will also be an important direction of future development.
遥感高光谱成像遥感载荷技术宽谱宽幅高分辨率
remote sensinghyperspectral imagingremote sensing payloadwide spectrumwide swath widthhigh resolution
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