A method for hydrological information extraction from historical maps combining SAM large model and mathematical morphology

doi:10.11947/j.AGCS.2024.20230308

Abstract

Abstract:

Historical maps record rich historical geographic information, which can help understand the laws of historical movement and provide reference for contemporary development. Different from modern maps, remote sensing images and other data, the historical map has been preserved for a long time, and there are some problems such as small number of reservations and low image accuracy. Map symbols are also different from modern maps, so the information is difficult to be extracted efficiently. Aiming at this problem, this study proposes an intelligent method for extracting hydrological information from historical maps based on the experimental data of topographic map of ditches and channels along the Yellow River in Ningxia province. Firstly, the datasets are constructed by clustering and mathematical morphology methods combined with symbolic syntax. Then, the general large model SAM structure is improved and the weight is optimized by transfer learning. Finally, the historical map hydrological information is automatically extracted by improved SAM. Comparing the experimental results with other models, it shows that the extraction results of this method have clear boundaries, complete contours, and the highest accuracy and accuracy. At the same time, the extraction results are compared with the current situation of the hydrological in the region. It is found that most of the rivers and ditches in history are now diverted, offset or disappeared, and the lake area is greatly reduced. The method in this paper is improved based on the SAM general large model, which verifies the availability of the large model in the map field and provides a new idea for map information extraction.

Key words: historical map, extraction of hydrology, fuzzy C-means, mathematical morphology, SAM general large model

CLC Number:

P283

Fei ZHAO, Zhaozheng LI, Quan GAN, Zuyu GAO, Zhanchu WANG, Qingyun DU, Zhensheng WANG, Yang SHEN, Wei PAN. A method for hydrological information extraction from historical maps combining SAM large model and mathematical morphology[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(4): 761-772.

Figures/Tables 13

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标签类别	数量	占比/（%）
沟渠	186	88.57
河流	59	28.10
浅湖	151	71.90
深湖	33	15.71
地图印章	15	7.14
文字注记	210	100.00
等高线	210	100.00
道路	91	43.30
居民地	118	56.19

模型	准确率	IoU	精度	F₁值
U-Net	84.31	61.62	62.32	76.48
原始SAM	89.68	76.65	84.70	84.40
改进SAM	94.13	83.25	91.18	90.86