Page 109 - 《渔业研究》2025年第6期
P. 109
800 渔 业 研 究 第 47 卷
了 Res-PGAUnet 模型在实际应用中的潜力,为养 tion of irrigation ponds from high-resolution tile images
殖空间信息的精准监测与渔业可持续发展提供了可 [J]. Journal of Space Technology and Engineering, 2025,
靠的技术支撑。未来可补充更丰富的目标和负样本 2(4): 93 − 100.
以增强模型泛化能力,进一步提升复杂场景下的提 [ 9 ] 袁鑫,张丽,宋茜茜,等. 海南岛海水池塘养殖遥感
取鲁棒性。 监测与时空变化分析 [J]. 海洋学研究,2020,38(1) :
59 − 67.
Yuan X, Zhang L, Song X X, et al. Remote sensing mon-
参考文献(References) :
[ 1 ] 盛德志,邢前国,刘海龙,等. 基于混合像元分解的 itoring and spatial-temporal change analysis of aquacul-
池塘养殖动态遥感监测 [J]. 自然资源遥感,2022, ture ponds in coastal area Hainan Island[J]. Journal of
34(4) :53 − 59. Marine Sciences, 2020, 38(1): 59 − 67.
Sheng D Z, Xing Q G, Liu H L, et al. Remote sensing [10] 刘炜,王聪华,赵尔平,等. 基于分层分级的遥感图
monitoring of the spatio-temporal changes in pond aqua- 像植被分类方法 [J]. 中国矿业大学学报,2016,45(4):
culture based on mixed pixel decomposition[J]. Remote 828 − 835.
Sensing for Natural Resources, 2022, 34(4): 53 − 59. Liu W, Wang C H, Zhao E P, et al. Vegetation classifica-
[ 2 ] Duan Y Q, Li X, Zhang L P, et al. Mapping national- tion of remote sensing image based on hierarchical clus-
scale aquaculture ponds based on the Google Earth En- tering analysis[J]. Journal of China University of Min-
gine in the Chinese coastal zone[J]. Aquaculture, 2020, ing & Technology, 2016, 45(4): 828 − 835.
520: 734666. [11] Ronneberger O, Fischer P, Brox T. U-Net: convolutional
[ 3 ] Peng Y, Sengupta D, Duan Y Q, et al. Accurate map- networks for biomedical image segmentation[C]//Spring-
ping of Chinese coastal aquaculture ponds using bio- er. Proceedings of the 18th International Conference on
physical parameters based on sentinel-2 time series im- Medical Image Computing and Computer-Assisted Inter-
ages[J]. Marine Pollution Bulletin, 2022, 181: 113901. vention. Munich: Springer, 2015: 234 − 241.
[ 4 ] Zeng Z, Wang D, Tan W X, et al. Extracting aquacul- [12] Badrinarayanan V, Kendall A, Cipolla R. SegNet: a deep
ture ponds from natural water surfaces around inland convolutional encoder-decoder architecture for image seg-
lakes on medium resolution multispectral images[J]. In- mentation[J]. IEEE Transactions on Pattern Analysis
ternational Journal of Applied Earth Observation and and Machine Intelligence, 2017, 39(12): 2481 − 2495.
Geoinformation, 2019, 80: 13 − 25. [13] Chen L C, Zhu Y K, Papandreou G, et al. Encoder-de-
[ 5 ] Sun Z, Luo J H, Yang J Z C, et al. Nation-scale mapping coder with atrous separable convolution for semantic im-
of coastal aquaculture ponds with sentinel-1 SAR data age segmentation[C]//Springer. Proceedings of the 15th
using google earth engine[J]. Remote Sensing, 2020, European Conference on Computer Vision. Munich: Spr-
12(18): 3086. inger, 2018: 833 − 851.
[ 6 ] Hou Y X, Zhao G, Chen X H, et al. Improving satellite [14] 刘继鹏,王常颖,初佳兰. 基于 U-Net 的国产高分卫
retrieval of coastal aquaculture pond by adding water 星影像海水养殖区分类提取方法 [J]. 海洋环境科学,
quality parameters[J]. Remote Sensing, 2022, 14(14): 2023,42(3) :471 − 482.
3306. Liu J P, Wang C Y, Chu J L. Classification and extrac-
[ 7 ] 徐京萍,赵建华,张丰收,等. 面向对象的池塘养殖用 tion method of mariculture area from domestic high-res-
海信息提取 [J]. 国土资源遥感,2013,25(1):82 − 85. olution satellite images based on U-Net model[J]. Mar-
Xu J P, Zhao J H, Zhang F S, et al. Object-oriented in- ine Environmental Science, 2023, 42(3): 471 − 482.
formation extraction of pond aquaculture[J]. Remote [15] 王心哲,邓棋文,王际潮,等. 深度语义分割 MRF
Sensing for Land & Resources, 2013, 25(1): 82 − 85. 模型的海洋筏式养殖信息提取 [J]. 山东大学学报
[ 8 ] 王磊,李响,张文亚,等. 面向对象的高分辨率瓦片 (工学版) ,2022,52(2) :89 − 98.
影像灌溉池塘提取 [J]. 航天技术与工程学报,2025, Wang X Z, Deng Q W, Wang J C, et al. Deep semantic
2(4) :93 − 100. segmentation MRF model for information extraction of
Wang L, Li X, Zhang W Y, et al. Object-oriented extrac- marine floating raft aquaculture[J]. Journal of Shandong

