Improving agricultural field parcel delineation with a dual branch spatiotemporal fusion network by integrating multimodal satellite data

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成果类型：

期刊论文

作者：

Cai, Zhiwen;Hu, Qiong;Zhang, Xinyu;Yang, Jingya;Wei, Haodong;...

通讯作者：

Hu, Q

作者机构：

[Xu, Baodong; Shi, Zhihua; Cai, Zhiwen] Huazhong Agr Univ, Coll Resources & Environm, Wuhan 430070, Peoples R China.

[Hu, Q; Hu, Qiong; Yang, Jingya] Cent China Normal Univ, Coll Urban & Environm Sci, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Hubei, Peoples R China.

[Zhang, Xinyu; You, Liangzhi; Wei, Haodong] Huazhong Agr Univ, Macro Agr Res Inst, Coll Plant Sci & Technol, Wuhan 430070, Peoples R China.

[Li, Wenjuan; Yang, Jingya] Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, State Key Lab Efficient Utilizat Arid & Semi arid, Beijing 100081, Peoples R China.

[Zeng, Yelu] China Agr Univ, Coll Land Sci & Technol, Beijing 100083, Peoples R China.

通讯机构：

[Hu, Q ] C

Cent China Normal Univ, Coll Urban & Environm Sci, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Hubei, Peoples R China.

语种：

英文

关键词：

Agricultural field parcel delineation Deep learning Multimodal satellite data Spatiotemporal fusion Spatial transferability

期刊：

ISPRS Journal of Photogrammetry and Remote Sensing

ISSN：

0924-2716

年：

2023

卷：

205

页码：

34-49

DOI：

10.1016/j.isprsjprs.2023.09.021

基金类别：

National Key Research and Development Program of China [2022YFB3903502]; National Natural Science Foundation of China [42271399, 42271360]; Young Elite Scientists Sponsorship Program by CAST [2020QNRC001]; Fundamental Research Funds for the Central Universities [2662021JC013, CCNU22QN018]

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：

Accurate spatial information for agricultural field parcels is important for agricultural production management and understanding agro-industrialization and intensification. However, traditional remote sensing methods that rely on single-modal or single-date data struggle to identify heterogeneous field parcels, particularly in regions dominated by smallholder farming systems. To address this challenge, we proposed a Dual branch Spatiotemporal Fusion Network (DSTFNet) that integrated very high-resolution (VHR) images and medium-resolution satellite image time series (MRSITS) to extract agricul...

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Improving agricultural field parcel delineation with a dual branch spatiotemporal fusion network by integrating multimodal satellite data

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