智慧农业导刊2025，Vol.5Issue(6)：16-21,26,7.DOI:10.20028/j.zhnydk.2025.06.003
基于高分卫星影像与深度学习的广东省台山市互花米草识别
摘要
Abstract
In view of the problems of large workload,high cost,and low efficiency of the traditional field survey method of Spartina alterniflora,this research is based on remote sensing technology to explore methods suitable for the survey of Spartina alterniflora at the forestry grassroots level.Based on high-resolution satellite images,the study used the deep learning tools integrated in ArcGIS Pro software to semantically segment the coastal zone of Taishan City invaded by Spartina alterniflora,and quickly identify the sketch spots of Spartina alterniflora without prior knowledge of programming.The test set results show that both U-Net and DeepLabV3 models can achieve good classification accuracy of Spartina alterniflora on the Beijing-2 image with higher spatial resolution.Accuracy is 97.24%and 97.72%respectively,and F1 Score is 0.68 and 0.79 respectively.The comprehensive performance of DeepLabV3 model is better;both of them perform poorly on PlanetScope satellite images.Set up appropriate buffers for classification results and improve Recall,which is more instructive for actual operations.This research method has high accuracy in identifying Spartina alterniflora and is easy to popularize.It can effectively improve the efficiency of Spartina alterniflora investigation and provide data support for Spartina alterniflora management work.关键词
深度学习/卫星影像/互花米草/入侵植物/ArcGIS Pro/航拍Key words
deep learning/satellite images/Spartina alterniflora/invasive plant/ArcGIS Pro/aerial photography分类
林学引用本文复制引用
陈湛昊,郭茂涛,孙思,彭逸生..基于高分卫星影像与深度学习的广东省台山市互花米草识别[J].智慧农业导刊,2025,5(6):16-21,26,7.基金项目
联合国环境署"南中国海"项目(S1-32GFL-000631,SB-009056) （S1-32GFL-000631,SB-009056）
广东省林业科技创新项目(2022KJCX019) （2022KJCX019）
台山市林业外来入侵物种普查项目(20230217) （20230217）
