A dynamic preparation method for intelligent interpretation samples based on GlobeLand30

doi:10.14088/j.cnki.issn0439-8114.2023.09.026

HUBEI AGRICULTURAL SCIENCES ›› 2023, Vol. 62 ›› Issue (9): 142-150.doi: 10.14088/j.cnki.issn0439-8114.2023.09.026

• Information Engineering • Previous Articles Next Articles

A dynamic preparation method for intelligent interpretation samples based on GlobeLand30

CHEN Jing^1,2, HE Xiang-yu³, CHEN Jian-sheng¹, CHEN Jing-bo¹, DENG Yu-peng^1,2, ZHANG Xue-hua⁴

1. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China;
2. School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 101400, China;
3. Engineering Quality Supervision Center of Logistics Support Department of the Military Commission, Beijing 100142, China;
4. National Disaster Reduction Center of the Ministry of Emergency Management, Beijing 100124, China

Received:2022-01-29 Online:2023-09-25 Published:2023-10-24

Abstract

Abstract: A dynamic preparation method for intelligent interpretation samples based on Landsat-8 image similarity was studied from the perspective of image feature similarity. Three sample set selection methods were constructed, including spectral similarity, texture similarity, and spatial proximity.Based on the same U-Net+EfficientNet-B3 semantic segmentation network, the impact of sample sets prepared from selected sample images under three measures on overall classification accuracy was compared. The results indicated that selecting sample images from historical achievement data for model training was an effective method to improve classification accuracy;among the three sample image selection strategies, spatial proximity could obtain the classification results with the highest accuracy and the lowest variance;incorrect labels in historical achievement data could lead to a decrease in the accuracy of intelligent models.

Key words: GlobeLand30, intelligent interpretation samples, dynamic preparation method, semantic segmentation, dataset, Landsat-8, image similarity

CLC Number:

TP751

CHEN Jing, HE Xiang-yu, CHEN Jian-sheng, CHEN Jing-bo, DENG Yu-peng, ZHANG Xue-hua. A dynamic preparation method for intelligent interpretation samples based on GlobeLand30[J]. HUBEI AGRICULTURAL SCIENCES, 2023, 62(9): 142-150.

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A dynamic preparation method for intelligent interpretation samples based on GlobeLand30

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