Mapping of land-based aquaculture regions in Southeast Asia and its Spatiotemporal change from 1990 to 2020 using time-series remote sensing data

被引:6
作者
Zhang, Junyao [1 ,2 ]
Yang, Xiaomei [1 ,2 ]
Wang, Zhihua [1 ,2 ]
Liu, Yueming [1 ,2 ]
Liu, Xiaoliang [1 ,2 ]
Ding, Yaxin [1 ]
机构
[1] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
基金
国家重点研发计划;
关键词
Aquaculture; Spatiotemporal change; Google Earth Engine; Remote sensing monitoring; Southeast Asia; SURFACE-WATER; INDEX;
D O I
10.1016/j.jag.2023.103518
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Aquaculture, a crucial component of global food production, faces sustainability challenges due to increased competition for natural resources, environmental pollution, and subpar management practices. Understanding spatial-temporal changes in aquaculture distribution can offer insights into guiding its scientific and sustainable development. While Southeast Asia constitutes a key player in global aquaculture, there exists a significant gap in long-term remote sensing monitoring of aquaculture changes at a sub-continental scale. To fill this gap, this study introduces a workflow for aquaculture extraction that combines both automated and manual methods, based on water and edge frequency detection. By using time series of Landsat images and Sentinel-2 images on the GEE platform, we extracted spatial distribution data of aquaculture in Southeast Asia for five periods from 1990 to 2020. This data, boasting an accuracy exceeding 89.53% and peaking at 95.49%, laid the foundation for investigating the spatial distribution patterns, temporal-spatial changes, and area center changes of aquaculture across the study periods. The results showed that the period of aquaculture rapid expansion was concentrated in the first two decades, followed by a gradual decline in the expansion rate, and a consistent northwestward movement of the area center. The spatial distribution pattern of aquaculture in Southeast Asia gradually changed from "Indonesia and the other producers each account for 40% and 60%" to "Vietnam, Indonesia and the other producers each account for 40%, 30%, and 30%".
引用
收藏
页数:15
相关论文
共 58 条
  • [11] FAO, 2018, STATE WORLD FISHERIE, DOI [10.1016/j.cub.2018.09.028, DOI 10.1016/J.CUB.2018.09.028]
  • [12] FAO, 2016, STATE WORLD FISHERIE
  • [13] FAO/FishCode Review, 2004, NAT C RESP FISH VIET, V9
  • [14] Harnessing Machine Learning Techniques for Mapping Aquaculture Waterbodies in Bangladesh
    Ferriby, Hannah
    Nejadhashemi, Amir Pouyan
    Hernandez-Suarez, Juan Sebastian
    Moore, Nathan
    Kpodo, Josue
    Kropp, Ian
    Eeswaran, Rasu
    Belton, Ben
    Haque, Mohammad Mahfujul
    [J]. REMOTE SENSING, 2021, 13 (23)
  • [15] Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery
    Feyisa, Gudina L.
    Meilby, Henrik
    Fensholt, Rasmus
    Proud, Simon R.
    [J]. REMOTE SENSING OF ENVIRONMENT, 2014, 140 : 23 - 35
  • [16] A new satellite-derived dataset for marine aquaculture areas in China's coastal region
    Fu, Yongyong
    Deng, Jinsong
    Wang, Hongquan
    Comber, Alexis
    Yang, Wu
    Wu, Wenqiang
    You, Shixue
    Lin, Yi
    Wang, Ke
    [J]. EARTH SYSTEM SCIENCE DATA, 2021, 13 (04) : 1829 - 1842
  • [17] Climate change adaptation in aquaculture
    Galappaththi, Eranga K.
    Ichien, Stephanie T.
    Hyman, Amanda A.
    Aubrac, Charlotte J.
    Ford, James D.
    [J]. REVIEWS IN AQUACULTURE, 2020, 12 (04) : 2160 - 2176
  • [18] NDWI - A normalized difference water index for remote sensing of vegetation liquid water from space
    Gao, BC
    [J]. REMOTE SENSING OF ENVIRONMENT, 1996, 58 (03) : 257 - 266
  • [19] Climate change hot-spots
    Giorgi, F
    [J]. GEOPHYSICAL RESEARCH LETTERS, 2006, 33 (08)
  • [20] On the dependency of GCM-based regional surface climate change projections on model biases, resolution and climate sensitivity
    Giorgi, Filippo
    Raffaele, Francesca
    [J]. CLIMATE DYNAMICS, 2022, 58 (9-10) : 2843 - 2862