Detecting annual anthropogenic encroachment on intertidal vegetation using full Landsat time-series in Fujian, China

被引:3
|
作者
Wu, Wenting [1 ]
Zhi, Chao [1 ]
Chen, Chunpeng [2 ]
Tian, Bo [2 ]
Chen, Zuoqi [1 ]
Su, Hua [1 ]
机构
[1] Fuzhou Univ, Natl & Local Joint Engn Res Ctr Satellite Geospati, Key Lab Spatial Data Min, Informat Sharing Minist Educ, Fuzhou, Peoples R China
[2] East China Normal Univ, State Key Lab Estuarine & Coastal Res, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
Intertidal vegetation; human activities; change detection; condition assessment; full Landsat time-series; TIDAL FLATS; INDEX; RECLAMATION; IMAGERY; STATE; DISTURBANCE; LANDTRENDR; MANAGEMENT; MANGROVES; RECOVERY;
D O I
10.1080/15481603.2022.2158521
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Intertidal vegetation plays an essential role in habitat provision for waterbirds but suffers great losses due to human activities. However, it is challenging in tracking the human-driven loss and degradation of intertidal vegetation due to rapid urbanization in a high temporal resolution. In this study, a methodological framework based on full Landsat time-series (FLTS) is proposed to detect the year of change (YOC) of intertidal vegetation converted to impervious surfaces (ISs) and artificial ponds (APs), and the condition of the remaining intertidal vegetation was also assessed by FLTS, in the Fujian province, a subtropical coastal area lying in southeast China. The accuracies of the YOC detection of intertidal vegetation converted to IS and AP were 91.84% and 72.73%, with mean absolute errors of 0.26 and 1.06, respectively. The total areas of intertidal vegetation encroached by IS and AP were 31.68 km(2) and 23.85 km(2), respectively. Most ISs were developed later than 2010, and most APs were developed earlier than 2005, which are highly related to the implementation of local policies for economic development. The remaining intertidal vegetation in growing, stable, and degraded conditions were 43.05%, 56.38%, and 0.57%, respectively. The results indicated that areas of intertidal vegetation were reclaimed for anthropogenic uses at a considerable rate, although the intertidal vegetation still increased owing to natural development after the establishment of natural reserves. The study demonstrates that the FLTS has capacities in monitoring the dynamics in coastal zones solely for its dense earth observations.
引用
收藏
页码:2266 / 2282
页数:17
相关论文
共 50 条
  • [11] Integration of Landsat time-series vegetation indices improves consistency of change detection
    Zhou, Mingxing
    Li, Dengqiu
    Liao, Kuo
    Lu, Dengsheng
    INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2023, 16 (01) : 1276 - 1299
  • [12] Tracking vegetation degradation and recovery in multiple mining areas in Beijing, China, based on time-series Landsat imagery
    Han, Yue
    Ke, Yinghai
    Zhu, Lijuan
    Feng, Hui
    Zhang, Qun
    Sun, Zhao
    Zhu, Lin
    GISCIENCE & REMOTE SENSING, 2021, 58 (08) : 1477 - 1496
  • [13] Monitoring of Vegetation Disturbance around Protected Areas in Central Tanzania Using Landsat Time-Series Data
    Komba, Atupelye W.
    Watanabe, Teiji
    Kaneko, Masami
    Chand, Mohan Bahadur
    REMOTE SENSING, 2021, 13 (09)
  • [14] Classification mapping of salt marsh vegetation by flexible monthly NDVI time-series using Landsat imagery
    Sun, Chao
    Fagherazzi, Sergio
    Liu, Yongxue
    ESTUARINE COASTAL AND SHELF SCIENCE, 2018, 213 : 61 - 80
  • [15] Detecting Vegetation Change in Response to Confining Elephants in Forests Using MODIS Time-Series and BFAST
    Morrison, Jacqueline
    Higginbottom, Thomas P.
    Symeonakis, Elias
    Jones, Martin J.
    Omengo, Fred
    Walker, Susan L.
    Cain, Bradley
    REMOTE SENSING, 2018, 10 (07)
  • [16] Annual continuous fields of woody vegetation structure in the Lower Mekong region from 2000-2017 Landsat time-series
    Potapov, P.
    Tyukavina, A.
    Turubanova, S.
    Talero, Y.
    Hernandez-Serna, A.
    Hansen, M. C.
    Saah, D.
    Tenneson, K.
    Poortinga, A.
    Aekakkararungroj, A.
    Chishtie, F.
    Towashiraporn, P.
    Bhandari, B.
    Aung, K. S.
    Nguyen, Q. H.
    REMOTE SENSING OF ENVIRONMENT, 2019, 232
  • [17] Characterising spatiotemporal vegetation variations using LANDSAT time-series and Hurst exponent index in the Mekong River Delta
    Tran, Thuong, V
    Tran, Duy X.
    Ho Nguyen
    Latorre-Carmona, Pedro
    Myint, Soe W.
    LAND DEGRADATION & DEVELOPMENT, 2021, 32 (13) : 3507 - 3523
  • [18] Tracking annual changes in the distribution and composition of saltmarsh vegetation on the Jiangsu coast of China using Landsat time series-based phenological parameters
    Sun, Chao
    Li, Jialin
    Liu, Yongchao
    Zhao, Saishuai
    Zheng, Jiahao
    Zhang, Shu
    REMOTE SENSING OF ENVIRONMENT, 2023, 284
  • [19] Time-series analysis of satellite imagery for detecting vegetation cover changes in Indonesia
    Takuro Furusawa
    Takuya Koera
    Rikson Siburian
    Agung Wicaksono
    Kazunari Matsudaira
    Yoshinori Ishioka
    Scientific Reports, 13
  • [20] Using annual time-series of Landsat images to assess the effects of forest restitution in post-socialist Romania
    Griffiths, Patrick
    Kuemmerle, Tobias
    Kennedy, Robert E.
    Abrudan, Ioan V.
    Knorn, Jan
    Hostert, Patrick
    REMOTE SENSING OF ENVIRONMENT, 2012, 118 : 199 - 214