Study on automatic identification of tower base construction based on satellite image

Jianmin Qi; Yongjun Qiu; Yikang Huang; Gaojian Fu; Leijuan Li; Xin Liu; Panpan Song

doi:10.1117/12.2670302

1 June 2023 Study on automatic identification of tower base construction based on satellite image

Jianmin Qi, Yongjun Qiu, Yikang Huang, Gaojian Fu, Leijuan Li, Xin Liu, Panpan Song

Proceedings Volume 12625, International Conference on Mathematics, Modeling, and Computer Science (MMCS2022); 126251K (2023) https://doi.org/10.1117/12.2670302
Event: International Conference on Mathematics, Modeling and Computer Science (MMCS2022),, 2022, Wuhan, China

Abstract

In order to better research area of construction project construction disturbance and soil erosion situation, research scholars in view of the high voltage power transmission and transformation project of route planning, site supervision, puts forward the satellite image as the core of Kentucky construction automatic identification method, it not only can help the project construction and supervision staff to grasp more information data, can also provide effective basis for project construction management. Therefore, this article studies in the construction status quo, on the basis of understanding the current monitoring system design based on high voltage transmission line images, automatic gain disturbance area of construction project, and using convolution neural network algorithm and high score 2 satellite remote sensing image, the analysis of fast automatic recognition of high pressure disturbance area card machine and application method. The final results show that both of them can quickly identify the construction labor area, and the actual data obtained are consistent. Compared with the actual measured value of the disturbance area, the maximum value of the relative error can reach 11.77%, and the minimum value can reach 1.20%.

Citation Download Citation

Jianmin Qi, Yongjun Qiu, Yikang Huang, Gaojian Fu, Leijuan Li, Xin Liu, and Panpan Song "Study on automatic identification of tower base construction based on satellite image", Proc. SPIE 12625, International Conference on Mathematics, Modeling, and Computer Science (MMCS2022), 126251K (1 June 2023); https://doi.org/10.1117/12.2670302

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KEYWORDS

Satellite imaging

Satellites

Convolutional neural networks

Earth observing sensors

Remote sensing

Evolutionary algorithms

Error analysis

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