Mapping wetland using the object-based stacked generalization method based on multi-temporal optical and SAR data

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成果类型：

期刊论文

作者：

Cai, Yaotong;Li, Xinyu;Zhang, Meng*;Lin, Hui*

通讯作者：

Zhang, Meng;Lin, Hui

作者机构：

[Li, Xinyu; Zhang, Meng; Lin, Hui; Cai, Yaotong] Cent South Univ Forestry & Technol, Res Ctr Forestry Remote Sensing & Informat Engn, Changsha 410004, Hunan, Peoples R China.

[Li, Xinyu; Zhang, Meng; Cai, Yaotong; Lin, Hui] Key Lab Forestry Remote Sensing Based Big Data &, Changsha 410004, Hunan, Peoples R China.

[Li, Xinyu; Zhang, Meng; Cai, Yaotong; Lin, Hui] Key Lab State Forestry & Grassland Adm Forest Res, Changsha 410004, Hunan, Peoples R China.

[Li, Xinyu] Hunan First Normal Univ, Sch Informat Sci & Engn, Changsha 410205, Peoples R China.

通讯机构：

[Zhang, M; Lin, H] C

Cent South Univ Forestry & Technol, Res Ctr Forestry Remote Sensing & Informat Engn, Changsha 410004, Hunan, Peoples R China.

语种：

英文

关键词：

Wetland;Classification;Sentinel-1/2;Multi-Temporal;Object-Based;Stacked generalization

期刊：

International Journal of Applied Earth Observation and Geoinformation

ISSN：

1569-8432

年：

2020

卷：

页码：

102164

DOI：

10.1016/j.jag.2020.102164

基金类别：

Our deepest gratitude goes to the editor and anonymous reviewers for their careful work and thoughtful suggestions that have helped improve this manuscript. This study was funded by the National Natural Science Foundation of China ( 41901385 ), the Forestry Remote Sensing Application System based on GF satellites (Phase 2) ( 21-Y30B02-9001-19/22 ), and in part by the China Postdoctoral Science Foundation ( 2019M652815 ).

机构署名：

本校为第一且通讯机构

院系归属：

林学院

摘要：

Wetland ecosystems have experienced dramatic challenges in the past few decades due to natural and human factors. Wetland maps are essential for the conservation and management of terrestrial ecosystems. This study is to obtain an accurate wetland map using an object-based stacked generalization (Stacking) method on the basis of multi-temporal Sentinel-1 and Sentinel-2 data. Firstly, the Robust Adaptive Spatial Temporal Fusion Model (RASTFM) is used to get time series Sentinel-2 NDVI, from which the vegetation phenology variables are derived by...

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Mapping wetland using the object-based stacked generalization method based on multi-temporal optical and SAR data

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