Data fusion of the third national land resource survey and the geographical conditions monitoring based on regression analysis

Meiqi Li; Tao Shen; Jun Zheng; Junjun He; Qi Bai; Lele Chu; Baolin Shi

doi:10.1117/12.2668174

23 February 2023 Data fusion of the third national land resource survey and the geographical conditions monitoring based on regression analysis

Meiqi Li, Tao Shen, Jun Zheng, Junjun He, Qi Bai, Lele Chu, Baolin Shi

Author Affiliations +

Proceedings Volume 12551, Fourth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2022); 125510B (2023) https://doi.org/10.1117/12.2668174
Event: Fourth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2022), 2022, Changchun, China

Abstract

Aiming at the application of the geographical conditions monitoring data in the results of the third national land resource survey, this paper proposes a comparison and fusion model of the third national land resource survey and the geographical conditions monitoring based on regression analysis. This study analyses the reasons for the differences between the two groups of data, and formulates the fusion rules, and takes Jieshou city as the study area to carry out experiments. We randomly selected sample areas for fusion experiments to obtain statistical data, consider the relationship between the fused cultivated land area (Y) and the cultivated land overlapping area ( x₁ ), and the cultivated land difference area ( x₂ ), and established a regression equation. The model can solve the problem of the difference between the data of the third national land resource survey and the geographical conditions monitoring, and realize the effective integration of cultivated land types. Based on the regression analysis method, the regression equation of cultivated land area after the integration of Jieshou city is obtained. The model proposed in this paper can not only effectively connect the third national land resource survey data with the geographical conditions monitoring data, but also scientifically and accurately predict the area of cultivated land in Jieshou city. The research results can provide technical support for the distribution of cultivated land quality monitoring points, land environmental protection, land management, etc.

Citation Download Citation

Meiqi Li, Tao Shen, Jun Zheng, Junjun He, Qi Bai, Lele Chu, and Baolin Shi "Data fusion of the third national land resource survey and the geographical conditions monitoring based on regression analysis", Proc. SPIE 12551, Fourth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2022), 125510B (23 February 2023); https://doi.org/10.1117/12.2668174

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KEYWORDS

Data fusion

Data modeling

Analytical research

Statistical analysis

Error analysis

Image fusion

Statistical modeling

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