Automatic 10 m Forest Cover Mapping in 2020 at China's Han River Basin by Fusing ESA Sentinel-1/Sentinel-2 Land Cover and Sentinel-2 near Real-Time Forest Cover Possibility

被引:5
作者
Wang, Xia [1 ]
Zhang, Yihang [2 ]
Zhang, Kerong [1 ,3 ]
机构
[1] Chinese Acad Sci, Key Lab Aquat Bot & Watershed Ecol, Wuhan Bot Garden, Wuhan 430074, Peoples R China
[2] Chinese Acad Sci, Innovat Acad Precis Measurement Sci & Technol, Key Lab Monitoring & Estimate Environm & Disaster, Wuhan 430071, Peoples R China
[3] Chinese Acad Sci & Hubei Prov, Danjiangkou Wetland Ecosyst Field Sci Observat & R, Wuhan 430074, Peoples R China
来源
FORESTS | 2023年 / 14卷 / 06期
基金
中国国家自然科学基金;
关键词
forest cover; Sentinel-2; Sentinel-1; Dynamic World; Han River Basin; SOUTHEAST-ASIA; TREE COVER; MODIS NDVI; SERIES; MAPS; IMAGERY; CLASSIFICATION; ACCURACY; RIPARIAN; IKONOS;
D O I
10.3390/f14061133
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Given the increasingly fragmented forest landscapes, it is necessary to map forest cover with fine spatial resolution in a large area. The European Space Agency (ESA) released the 10 m global land cover map in 2020 based on Sentinel-1 and Sentinel-2 images, and Dynamic World provides near real-time possibilities of many land cover classes based on Sentinel-2 images, but they are not designed particularly for forest cover. In this research, we aimed to develop a method to automatically estimate an accurate 10 m forest cover map in 2020 by fusing the ESA forest cover map and Dynamic World near real-time forest cover possibilities. The proposed method includes three main steps: (1) generating stable forest samples, (2) determining the threshold T and (3) producing the fused forest cover map. China's Han River Basin, dominated by complex subtropical forests, was used as the study site to validate the performance of the proposed method. The results show that the proposed method could produce a forest cover map with the best overall accuracy of 98.02% & PLUSMN; 1.20% and more accurate spatial details compared to using only one of the two data sources. The proposed method is thus superior in mapping forest cover in complex forest landscapes.
引用
收藏
页数:14
相关论文
共 49 条
  • [1] Forest classification of Southeast Asia using NOAA AVHRR data
    Achard, F
    Estreguil, C
    [J]. REMOTE SENSING OF ENVIRONMENT, 1995, 54 (03) : 198 - 208
  • [2] Forest Land Cover Mapping at a Regional Scale Using Multi-Temporal Sentinel-2 Imagery and RF Models
    Alonso, Laura
    Picos, Juan
    Armesto, Julia
    [J]. REMOTE SENSING, 2021, 13 (12)
  • [3] Dynamic World, Near real-time global 10 m land use land cover mapping
    Brown, Christopher F.
    Brumby, Steven P.
    Guzder-Williams, Brookie
    Birch, Tanya
    Hyde, Samantha Brooks
    Mazzariello, Joseph
    Czerwinski, Wanda
    Pasquarella, Valerie J.
    Haertel, Robert
    Ilyushchenko, Simon
    Schwehr, Kurt
    Weisse, Mikaela
    Stolle, Fred
    Hanson, Craig
    Guinan, Oliver
    Moore, Rebecca
    Tait, Alexander M.
    [J]. SCIENTIFIC DATA, 2022, 9 (01)
  • [4] Timeliness in forest change monitoring: A new assessment framework demonstrated using Sentinel-1 and a continuous change detection algorithm
    Bullock, Eric L.
    Healey, Sean P.
    Yang, Zhiqiang
    Houborg, Rasmus
    Gorelick, Noel
    Tang, Xiaojing
    Andrianirina, Carole
    [J]. REMOTE SENSING OF ENVIRONMENT, 2022, 276
  • [5] Large Uncertainty on Forest Area Change in the Early 21st Century among Widely Used Global Land Cover Datasets
    Chen, He
    Zeng, Zhenzhong
    Wu, Jie
    Peng, Liqing
    Lakshmi, Venkataraman
    Yang, Hong
    Liu, Junguo
    [J]. REMOTE SENSING, 2020, 12 (21) : 1 - 18
  • [6] A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter
    Chen, J
    Jönsson, P
    Tamura, M
    Gu, ZH
    Matsushita, B
    Eklundh, L
    [J]. REMOTE SENSING OF ENVIRONMENT, 2004, 91 (3-4) : 332 - 344
  • [7] A comparison of forest cover maps in Mainland Southeast Asia from multiple sources: PALSAR, MERIS, MODIS and FRA
    Dong, Jinwei
    Xiao, Xiangming
    Sheldon, Sage
    Biradar, Chandrashekhar
    Nguyen Dinh Duong
    Hazarika, Manzul
    [J]. REMOTE SENSING OF ENVIRONMENT, 2012, 127 : 60 - 73
  • [8] Mapping Annual Global Forest Gain From 1983 to 2021 With Landsat Imagery
    Du, Zhenrong
    Yu, Le
    Yang, Jianyu
    Coomes, David
    Kanniah, Kasturi
    Fu, Haohuan
    Gong, Peng
    [J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2023, 16 : 4195 - 4204
  • [9] Near-real time forest change detection using PlanetScope imagery
    Francini, Saverio
    McRoberts, Ronald E.
    Giannetti, Francesca
    Mencucci, Marco
    Marchetti, Marco
    Mugnozza, Giuseppe Scarascia
    Chirici, Gherardo
    [J]. EUROPEAN JOURNAL OF REMOTE SENSING, 2020, 53 (01) : 233 - 244
  • [10] Forest Cover Mapping Based on a Combination of Aerial Images and Sentinel-2 Satellite Data Compared to National Forest Inventory Data
    Ganz, Selina
    Adler, Petra
    Kaendler, Gerald
    [J]. FORESTS, 2020, 11 (12): : 1 - 20