Forest Change Detection Service Based on Artificial Intelligence Learning Data


KIPS Transactions on Software and Data Engineering, Vol. 11, No. 8, pp. 347-354, Aug. 2022
https://doi.org/10.3745/KTSDE.2022.11.8.347,   PDF Download:
Keywords: Artificial intelligence, Learning Data, Forest Tree Species, Forest Change Detection, Aerial Photographs
Abstract

Since the era of the 4th industrial revolution has been ripe, the use of artificial intelligence(AI) based on massive data is beginning to be actively applied in various fields. However, as the process of analyzing forest species is carried out manually, many errors are occurring. Therefore, in this paper, about 60,000 pieces of AI learning data were automatically analyzed for pine, larch, conifer, and broadleaf trees of aerial photographs and pseudo images in the metropolitan area, and an AI model was developed to distinguish tree species. Through this, it is expected to increase in work efficiency by using the tree species division image as basic data when producing forest change detection and forest field topics.


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Cite this article
[IEEE Style]
H. Chung, J. Kim, S. Y. Ko, S. Chai, Y. Shin, "Forest Change Detection Service Based on Artificial Intelligence Learning Data," KIPS Transactions on Software and Data Engineering, vol. 11, no. 8, pp. 347-354, 2022. DOI: https://doi.org/10.3745/KTSDE.2022.11.8.347.

[ACM Style]
Hankun Chung, Jong-in Kim, Sun Young Ko, Seunggi Chai, and Youngtae Shin. 2022. Forest Change Detection Service Based on Artificial Intelligence Learning Data. KIPS Transactions on Software and Data Engineering, 11, 8, (2022), 347-354. DOI: https://doi.org/10.3745/KTSDE.2022.11.8.347.