A spectral-temporal constrained deep learning method for tree species mapping of plantation forests using time series Sentinel-2 imagery

首页 > 成果 > 详情

认领

导出

Link by DOI

反馈

作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Huang, Zehua;Zhong, Liheng;Zhao, Feng;Wu, Jin;Tang, Hao;...

通讯作者：

Meng, R;Zhao, F

作者机构：

[Meng, Ran; Lv, Zhengang; Zhou, Longfei; Meng, R; Huang, Zehua; Xu, Binyuan; Sun, Rui] Huazhong Agr Univ, Coll Resources & Environm, Wuhan 430070, Peoples R China.

[Zhong, Liheng] Ant Grp, Hangzhou 311121, Peoples R China.

[Zhao, Feng] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.

[Wu, Jin] Univ Hong Kong, Sch Biol Sci, Hong Kong, Peoples R China.

[Wu, Jin] Chinese Univ Hong Kong, State Key Lab Agrobiotechnol, Shatin, Hong Kong, Peoples R China.

通讯机构：

[Zhao, F ] C

[Meng, R ] H

Huazhong Agr Univ, Coll Resources & Environm, Wuhan 430070, Peoples R China.

Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.

HIT Artificial Intelligence Res Inst Co Ltd, Harbin, Heilongjiang, Peoples R China.

语种：

英文

关键词：

Tree species mapping;Key phenological stage;Transformer;Attention mechanism;Deep learning;Plantation forests

期刊：

ISPRS Journal of Photogrammetry and Remote Sensing

ISSN：

0924-2716

年：

2023

卷：

204

页码：

397-420

DOI：

10.1016/j.isprsjprs.2023.09.009

基金类别：

HZAU interdisciplinary sciences research fund [101510321040]; Fundamental Research Funds for the Central Universities, Beijing, China [2662022ZHYJ002]; HZAU research startup fund [11041810340, 11041810341]; National Natural Science Foundation of China [31922090, 41901382]; Innovation and Technology Fund of the HKSAR, China

机构署名：

本校为通讯机构

院系归属：

城市与环境科学学院

摘要：

Plantation forests provide critical ecosystem services and have experienced worldwide expansion during the past few decades. Accurate mapping of tree species through remote sensing is critical for managing plantation forests. The typical temporal behaviors and traits of tree species in satellite image time series (SITS) generate temporal and spectral features in multiple phenological stages that are critical to improve tree species mapping. However, the diverse input features, sequential relations and complex structures in SITS drastically increase the dimension and difficulty of spectral-temp...

反馈

产权有误：本人成果被他人认领

数据有误：数据基本信息有误

归属有误：成果的院系归属、机构署名归属有误

其他原因：

验证码：

看不清楚，换一个

确定

取消

成果认领

标题：

用户	作者	通讯作者	--
	请选择	请选择	--

确定

取消

A spectral-temporal constrained deep learning method for tree species mapping of plantation forests using time series Sentinel-2 imagery

反馈

成果认领

提示

该栏目需要登录且有访问权限才可以访问