Ms. Na Li Profile

Na Li

at AGRS

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Publications (5)

Proceedings Article | 18 December 2023 Paper

Mineral information recognition based on simulated high spatial resolution full spectrum remote sensing images

Na Li, Xinfeng Dong, Fuping Gan, Tongtong Li, Ruoheng Gao, Wei Bai

Proceedings Volume 12962, 1296202 (2023) https://doi.org/10.1117/12.3000827

KEYWORDS: Minerals, Remote sensing, Spatial resolution, Quartz

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Proceedings Article | 24 November 2021 Paper

Extraction of soil mineral information based on hyperspectral image

Na Li, Xinfeng Dong, Fuping Gan, Zhanchun Zou

Proceedings Volume 12064, 1206406 (2021) https://doi.org/10.1117/12.2601998

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Proceedings Article | 24 November 2021 Paper

Research on coal gangue recognition of GF-5 hyperspectral image

Xinfeng Dong, Na Li, Fuping Gan, Jinzhong Yang, Weiling Yao

Proceedings Volume 12064, 1206403 (2021) https://doi.org/10.1117/12.2599262

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Proceedings Article | 12 March 2021 Paper

Multi-period dynamic evaluation of soil loss in loess area

Yanni Ma, Yichuan Li, Xian Zhang, Junchuan Yu, Rongyuan Liu, Bokun Yan, Fuping Gan, Xinfeng Dong, Na Li, Yi Guo, Juan Bai

Proceedings Volume 11763, 117637S (2021) https://doi.org/10.1117/12.2587481

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The loess area is located in the middle and upper reaches of the Yellow River Basin. This area has a large area of ecologically sensitive areas and fragile areas, and it is the region with the most serious soil erosion in the country. A lot of loess is attached to the surface of the loess area, the vegetation is relatively sparse, and the seasonal rainfall is obvious. Therefore, the amount of soil erosion is large, which has a significant impact on the soil fertility of the loess area. At the same time, a large amount of soil erosion poses a huge challenge to environmental protection in the middle and lower reaches. Therefore, the problem of soil erosion is a key phenomenon that needs attention in the loess area. This paper takes the loess area of Tongwei-Zhuanglang area in Gansu Province as the research object, uses the multi-year remote sensing image classification data as the background (2000, 2005, 2010, 2015), combined with meteorological data (this data is released according to CRU The global 0.5° climate data set and the high-resolution climate data set for China released by CNERN were generated by the Delta spatial downscaling scheme in the Loess Plateau area), soil data, and soil parameter data (source 1 from the second soil census: 1 million Chinese soil maps), topographic data (DEM), vegetation coverage data, and the use of an improved universal soil loss equation (RULSE) model to carry out soil erosion in the region for many years (2000, 2005, 2010, 2015) Strength information extraction and classification. Contrast and analyze the degree of soil erosion in the area for many years, and evaluate the local soil erosion prevention measures. Studies have shown that from 2000, 2010, and 2015, the degree of soil loss gradually decreased, and the total amount of soil loss gradually decreased. However, due to the abnormally reduced precipitation in 2005, the soil erosion was generally low, which was an abnormal situation. Overall, soil erosion has continued to decrease in recent years, and the effects of soil and water conservation have been remarkable.

Proceedings Article | 12 March 2019 Paper

Progress and prospectives on engineering application of hyperspectral remote sensing for geology and mineral resources

Xinfeng Dong, Bokun Yan, Fuping Gan, Na Li

Proceedings Volume 11023, 110232Y (2019) https://doi.org/10.1117/12.2521828

KEYWORDS: Minerals, Remote sensing, Geology, Bidirectional reflectance transmission function, Atmospheric corrections, Iron, Data processing, Hematite

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