Bulletin of Surveying and Mapping ›› 2023, Vol. 0 ›› Issue (1): 39-44.doi: 10.13474/j.cnki.11-2246.2023.0007

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Forest land extraction based on Beijing No.2 and geographical national conditions data

DU Lindan1,2, DONG Chun2, ZHAO Rong2, ZHANG Yu2, KANG Xiaochen2   

  1. 1. School of Geomatics, Liaoning Technical University, Fuxin 123000, China;
    2. Chinese Academy of Surveying and Mapping, Beijing 100036, China
  • Received:2022-02-14 Published:2023-02-08

Abstract: The forest land in the geographic national conditions data does not include trees or single-row forests with a field area of less than 400 m2. If we only use the forest land data of geographical conditions to calculate the regional forest coverage rate, there will be a large error in the statistical results of the forest land in the area with large surrounding trees. For the above problems, in order to accurately extract the forest land cover and spatial extent in the region, a forest land extraction method based on the Beijing No.2 high-resolution remote sensing image is proposed in this paper by using the geographical and national land cover data. Firstly, according to the spectral characteristics of remote sensing images, the land types are divided according to vegetation, roads, railways and construction land, and the remote sensing images are used to extract samples of each type, and the maximum likelihood classification is used to extract the vegetation coverage for the samples that have passed the separable test. Then, with the help of the geographical and national land cover data, the overlay analysis was used to eliminate the misclassification and misclassification, and obtain the regional forest land coverage rate and spatial distribution. The results show that: ① The forest land coverage rate in the study area is 20.3%, which has not yet met the needs of a new round of forest land planning in Beijing. ② The forest land area in the geographic and national conditions data accounts for 54.03% of the total extracted forest land area, indicating that the use of this method in some areas is not enough. It is necessary to supplement the geographical conditions of forest land data. The experimental result is based on the visual comparison with remote sensing images combined with the field survey results, and it is believed that the spatial distribution of the extracted forest land is basically consistent with the actual distribution. The research provides a new method for the application of geographic and national conditions. The results can assist the regional green development planning and help to construct a scientific ecological spatial pattern.

Key words: forest land extraction, geographical national conditions monitoring, maximum likelihood classification, overlay analysis, Beijing No.2

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