The widespread application of hyperspectral remote sensing technology in my country

 Supporting the national strategies of "carbon peaking" and "carbon neutrality"  

In recent years, "carbon peaking" and "carbon neutrality" have become buzzwords concerning national welfare and people's livelihood. my country will strive to reach peak carbon dioxide emissions before 2030 and endeavor to achieve carbon neutrality before 2060. "Emission reduction and carbon sink increase" are the core of achieving the goals of "carbon peaking" and "carbon neutrality" and must be carried out in tandem, strengthening my country's carbon emission and carbon sink accounting work based on carbon monitoring data. Therefore, using hyperspectral satellites for global carbon dioxide monitoring has become an important means and is a recognized measure that can obtain quantitative and highly accurate carbon flux information at intercontinental, regional and local scales.

△my country successfully launched its carbon satellite TanSat in 2016.

It will become the third greenhouse gas satellite in the world to monitor global atmospheric carbon dioxide concentrations.

Developing a carbon monitoring satellite industry can provide more refined spatial resolution carbon monitoring data, enabling more continuous local monitoring and more precise spatial positioning of regional monitoring, which is beneficial for clarifying the source and sink attributions of critical areas. Simultaneously, combined with high-resolution remote sensing imagery, it can be used to conduct regional-level carbon neutrality capacity assessments of forests, urban buildings, and road surfaces.

Furthermore, developing regional carbon satellite capabilities can greatly enhance the region's scientific and technological reputation, help create an innovative technological brand, and provide impetus for the region's high-tech development.

Geological survey  

Satellite remote sensing hyperspectral imagery boasts high spectral resolution, spectral integration, and advantages such as large comprehensive information volume, high monitoring frequency, and wide coverage. It can accurately and in detail reflect the texture characteristics of geology and mineral resources, and can provide important basis and clues for mineral resource surveys.

High spatial resolution remote sensing data can be used to generate a single map of mineral resources across the country. This can be used not only to conduct surveys on the current status of mineral resource development and utilization, mine environmental monitoring, and mineral resource planning, but also to analyze and obtain objective data on mineral resource development. This provides important technical support and decision-making basis for mining administration departments in mineral resource planning, rectification of mineral resource development order, and management of the mine geological environment.

Furthermore, based on mineral identification and fine mineral identification, and according to the laws of mineral symbiotic association and the indicative role of the geological significance of minerals themselves, the intrinsic relationship between various geological factors can be intuitively inverted, which can improve the efficiency of hyperspectral analysis and problem-solving in geological applications.

 Forest health monitoring  

△ Forest cover map identified from hyperspectral visible and near-infrared data from Tiangong-1

Forest health monitoring mainly includes monitoring tree growth conditions and pest and disease monitoring. Traditional methods of monitoring tree health involve manual on-site surveys, requiring significant manpower and time investment, and often only obtaining data in a point-like manner, making it difficult to cover the overall health of the entire forest. However... Monitoring forest health through hyperspectral satellite remote sensing has significant advantages such as strong periodicity and wide coverage. Based on its "map-spectrum integration" feature, it can effectively identify forest pest and disease information by comparing spectral reflectance.

△The red area indicates the trees identified as being affected by pests and diseases.

Trees affected by pests and diseases will exhibit abnormalities in spectral reflectance and temperature, causing changes in the absorption and reflection characteristics of leaves in the visible and near-infrared bands. Therefore, based on data collected by hyperspectral remote sensing satellites, differences in spectral reflectance and structural anomalies can be identified through image enhancement processing and information extraction techniques, thereby enabling the monitoring of the health status of trees.

Emergency disaster monitoring  

△Interpreted satellite remote sensing image of the forest fire in Muli County, Liangshan Prefecture, Sichuan Province, April 1, 2020

In recent years, fires and explosions have occurred frequently in urban and forest areas, causing extremely serious losses, such as the Tianjin Port explosion, the Shenyang natural gas explosion, and the forest fire in the Liangshan Yi Autonomous Prefecture of Sichuan. Regarding fire monitoring... Satellite remote sensing can overcome the difficulties of scheduling in time and space, providing decision-making data for emergency relief and disaster relief.For example, in 2020, the National Satellite Remote Sensing Application Center of the Ministry of Natural Resources made full use of the three-star networking capability of the 2-meter/8-meter optical satellite constellation to continuously track the development of the forest fire in Muli County, Liangshan Prefecture, Sichuan Province from March 30 to April 1, generating a remote sensing image interpretation map of the forest fire. The monitoring results were submitted to the front line of emergency command.

△ Hyperspectral image from the "Environment-1" satellite

In response to the meteorological environment, Small satellite constellations can collect remote sensing images of the troposphere.It can monitor and forecast severe weather events such as typhoons, plum rains, and cloud clusters, while also conducting real-time assessments and early warnings of ocean wave information. It can also obtain information on flooding during the rainy season via satellite, providing data support for policies related to water supply, water management, flood control, and drainage.

  Ocean remote sensing  

△Thematic map of chlorophyll a concentration in water quality monitoring in Zhuhai City

Ocean remote sensing is one of the key technologies that led to significant advancements in marine science in the late 20th century. Its main purpose is to understand, study, develop, utilize, and protect marine resources, thus possessing immense strategic importance. With the development of science and technology, hyperspectral remote sensing has become a cutting-edge field in ocean remote sensing.

Medium resolution imaging spectrometers have become an effective tool for detecting ocean color and temperature due to their many advantages, such as wide spectral coverage, high resolution, and multiple spectral bands. It can be used not only to detect chlorophyll concentration, suspended sediment content, certain pollutants and surface water temperature in seawater, but also to detect sea ice, coastal zones and other similar phenomena.

Among them, sea surface temperature and chlorophyll concentration are fundamental elements of the marine ecological environment. Their distribution reflects the aggregation area and living environment of marine phytoplankton. They can also be used to indirectly monitor or forecast the spatiotemporal distribution of resources such as ocean fishing grounds and ocean water quality. Hyperspectral remote sensing satellites can acquire sea surface images over a wide area and in all weather conditions. Through the interpretation and analysis of these images, sea surface temperature and ocean color parameters can be effectively obtained, providing data support for relevant departments such as marine environmental monitoring and marine fisheries.This is of great significance for sea surface temperature forecasting and marine fishing ground environmental monitoring.

Agricultural remote sensing  

△Fine classification of crops based on hyperspectral satellite remote sensing data

Modern hyperspectral remote sensing technology has developed rapidly, enabling it to provide various Earth observation data dynamically, quickly, accurately, and promptly. Precision agriculture demands precision in production and resource utilization, and accuracy in management and development. Hyperspectral remote sensing has been applied in agricultural research and technology in the following ways:

1. A study on the relationship between individual crop growth and crop leaf spectra;

2. Use multi-temporal hyperspectral data to extract spectral features for identification and classification of different vegetation and crops;

3. Estimate the biophysical parameters of vegetation, such as leaf area index, biomass, total nitrogen, and total phosphorus.

4. Research on remote sensing information models;

5. Use vegetation indices for land cover analysis or dynamic monitoring of crop growth;

6. Monitoring crop growth.

△Disease stress: the yellower the skin, the more severe the disease; the greener the skin, the milder the disease.

The development of hyperspectral remote sensing in precision agriculture has many trends. Novel remote sensing technologies for precision agriculture remain a major research focus. This also requires the design and establishment of basic agricultural information systems, GIS-supported crop symptom extraction and agricultural diagnostic systems, and MIS-supported decision support system models.

Urban monitoring  

The combination of hyperspectral and high spatial resolution remote sensing data allows for the detailed differentiation of urban features and man-made targets. Remote sensing satellites can capture radiation sources on the Earth's surface at night, such as nighttime lights and fires, observing the brightness of the Earth's surface at night. This brightness primarily originates from human activities, such as residential areas, industrial areas, and even fishing boat lighting, as well as fires. This brightness can be quantified to measure the level of human activity, and is widely used in national economic and security fields.

In addition, satellite remote sensing imagery is characterized by its objectivity, accuracy, and timeliness, providing a systematic and effective high-tech means for urban planning, construction, and law enforcement. It can play an important role in urban planning, construction, and management, and can achieve good results in monitoring illegal construction.Based on satellite remote sensing imagery, change patches of specific objects can be extracted to enable early detection, prevention, and handling of illegal land use and illegal construction, particularly on the tops of existing buildings and urban and rural streets. This also enables enforcement with maps, which helps improve enforcement efficiency and reduce enforcement costs. On the other hand, high-resolution satellite imagery can be used for monthly continuous monitoring of post-approval land projects, monitoring their construction status throughout the entire process.

International Trade and Data Finance  

Key industrial parks, ports, and airports around the world are important carriers and platforms for global free trade. Observing their "growth" from the perspective of satellite remote sensing big data can reveal the vibrant scene of global trade. Satellite imagery and big data can reveal new information about global trade in various commodities (including minerals, metals, energy, electricity, carbon emissions, etc.), uncovering the information hidden beneath the satellite imagery layer to support certain trade and investment activities.

Military applications  

Hyperspectral imagery, due to its rich ground information, has been applied to the military field from the very beginning. Practical applications have demonstrated that this spectral imaging technology has high military value, and therefore the trend of using this remote sensor on military satellites is growing rapidly.In military reconnaissance and camouflage identification, it can automatically detect targets from camouflaged objects by using an imaging spectrometer based on the different spectral characteristics of the target and the camouflage material. In investigating weapons production, the hyperspectral imager can not only detect the spectral characteristics and existence of targets, but also analyze their material composition. It can collect smoke generated in factories, directly identify its material composition, and determine the weapons produced in the factory, especially offensive weapons.

Currently, hyperspectral data processing modules and software are becoming increasingly operational and commercialized. As an emerging technology based on the fusion of spectroscopy and remote sensing, hyperspectral remote sensing technology is demonstrating unlimited possibilities and vitality in the development of the digital economy.It is believed that with the further development of hyperspectral preprocessing and information extraction technologies, future hyperspectral technology will have more diverse application modes, directly providing users with a wide range of information products and meeting the needs of users at more levels.

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