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Currently, most sunlight-induced chlorophyll fluorescence (SIF) data are in discrete point form with sparse spatial coverage.
We used a hyperspectral instrument with a spectral resolution of 0.48 nm to conduct imaging high-resolution chlorophyll fluorescence exploration, hoping to fill the gap in the current satellite platform for sunlight-induced chlorophyll fluorescence with higher spatial resolution.

When spring arrives, it brings beautiful flowers and vibrant colors, but also some discomfort and allergy symptoms. These symptoms may be caused by pollen, tiny particles composed of the male reproductive cells of plants that can be dispersed by wind, insects, or other animals to pollinate other plants. Pollen exists in the air and may enter our respiratory tract, potentially affecting our health.

Ecosystems play a vital role in the exchange of water, energy, and greenhouse gases among soil, vegetation, and atmosphere. The ability to detect changes in ecosystem processes such as carbon sequestration, nutrient cycling, net primary productivity, and litter decomposition is an essential component of defining global biogeochemical cycles and identifying climate change. In forest ecosystem models, these processes are associated with canopy biochemical content, particularly nitrogen, lignin, and cellulose concentrations.

Driven by both global climate change and the "dual carbon" goal, hyperspectral technology, with its unique spectral resolution, has become a core technology in carbon monitoring. By capturing continuous and detailed spectral information of ground objects, hyperspectral technology can not only accurately quantify greenhouse gas emissions but also support carbon sink assessment and ecological governance, providing a scientific basis for global climate governance. The following analysis examines the key role of hyperspectral technology in dual carbon monitoring from multiple dimensions, including technical principles, application scenarios, technological breakthroughs, and future challenges.

In Lanzhou, Gansu Province, some newly reclaimed plots of land in Lanzhou New Area showed significant differences in yield in the fourth quarter of 2024, with some plots exhibiting significantly poorer growth, even though the variety, seeding rate, slope, and irrigation water source were all the same. Therefore, the farm hopes to use remote sensing to analyze the growth of different plots and assess the reasons for the differences in growth in order to make improvements in subsequent management.

In the previous series comparing satellite hyperspectral data in geological mapping, the research data, methods, and techniques were introduced. This section will introduce the relevant research results.

The absorption characteristics in the near-infrared region of the spectrum (1000–2500 nm) are a function of the bending and stretching vibrations of biochemical bonds (e.g., between hydrogen and carbon atoms and nitrogen and oxygen atoms) and their harmonics and overtones. In the visible region, chlorophyll and carotenoids produce strong absorption due to electronic energy transitions. Different methods exist for retrieving leaf and canopy characteristics from reflectance measurements.

Recently, DeepSeek has rapidly gained popularity for its outstanding AI performance, sparking heated discussions not only in China but also attracting widespread international attention and igniting a new wave of exploration in the business world. Let's take a look at DeepSeek's predictions regarding the future development trends of the commercial aerospace hyperspectral industry. (Please note that these predictions are not guaranteed to be accurate and are for reference only.)

Time-series-based fine crop classification methods analyze significant changes in crop spectral characteristics, vegetation indices (such as NDVI), and moisture indices (such as NDWI) throughout the entire growth cycle, and combine this with advanced classification models to achieve refined classification of crop types. This method is effectively adaptable to agricultural scenarios with complex crop types and wide geographical areas, and has significant application value, especially in crop planting area statistics and regional agricultural monitoring.

In the previous article, "Comparison of Satellite Hyperspectral Data in Geological Mapping (Methods Part 1)" (published on December 5, 2024), we introduced the registration of data from different sensors in the study area, spectral unmixing, spectral abundance, and spectral index. This section continues to introduce the relevant research techniques.