|Table of Contents|

Extraction of Dead Trees from Shelter-Forest Based onUAV Multispectral and SOLO Model(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2022年01期
Page:
46-51
Research Field:
机器学习
Publishing date:

Info

Title:
Extraction of Dead Trees from Shelter-Forest Based onUAV Multispectral and SOLO Model
Author(s):
Wang Xuewen1; 2; Zhao Qingzhan1; 2; Long Xuefeng1; 2; Hu Bin1; 2
(1.College of Information Science and Technology,Shihezi University,Shihezi 832003,China)(2.Geospatial Information Engineering Research Center,Xinjiang Production and Construction Corps,Shihezi 832003,China)
Keywords:
UAV multispectral image; optimal exponential factor; sample generation; SOLO model; dead tree extraction of shelterbelt
PACS:
TP391
DOI:
10.3969/j.issn.1672-1292.2022.01.007
Abstract:
Aiming at the decline of three-north shelter-forest caused by low mixed proportion of tree species,insufficient irrigation,uneven spatial distribution and frequent occurrence of diseases and pests,a method of extracting dead trees based on SOLO generated by UAV multi-spectral band under few-shot is proposed in this paper. The UAV is equipped with a Micro MCA12 Snap multispectral camera to obtain high spatial resolution images,derive and labele samples of multispectral visible bands(band 5,band 3,band 1). Based on the selected top 10 band combinations according to the best exponential factor,the dataset is expanded,and finally dead trees of shelter-forest are extracted based on the instance segmentation SOLO model. The experimental results show that with the addition of health tree samples,the SOLO model AP based on ResNet-101+FPN is increased from 61.3% to 63.8%,and the combined ResNet-50+FPN AP is increased from 60.7% to 63.6%. At the same time,the effectiveness of this sample enhancement method is further verified.

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Last Update: 2022-03-15