Identify and map coastal aquaculture ponds and their drainage and impoundment dynamics

IF 7.6 Q1 REMOTE SENSING
Duanrui Wang , Dehua Mao , Ming Wang , Xiangming Xiao , Chi-Yeung Choi , Chunlin Huang , Zongming Wang
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引用次数: 0

Abstract

Sustainable management of coastal aquaculture ponds could achieve win-win between food and economic benefits and ecological conservation including waterbird. In this study, 5790 Harmonized Landsat and Sentinel-2 images from July 2021 to June 2022 and 498 Sentinel-1 images from July 2021, August 2021, and June 2022 as supplementary data were collected to calculate multiple water indices. Based on Otsu algorithm to distinguish between water and non-water region and Savitzky-Golay filtering to optimize time series, coastal aquaculture ponds were identified using the SNIC. Furthermore, their drainage and impoundment phases were determined using the Dynamic Time Warping-Kmeans++ method. Finally, a new 30-m resolution dataset at the national scale of China was generated with an overall accuracy greater than 90 % for both the pond map and the drainage and impoundment phases. Our observations revealed that the total area was 7919.53 km2, with the largest pond area in Shandong Province. Among the coastal aquaculture ponds, 27.95 % were seasonal aquaculture ponds, 70.32 % were yearlong aquaculture ponds, and 1.49 % were abandoned aquaculture ponds. Drainage start dates, end dates, and durations were calculated based on abrupt changes in the water proportion time series. Drainage start dates were concentrated from September to December, while drainage end dates were from January to April. Drainage durations of coastal aquaculture ponds ranged from two weeks to six months, with Shanghai Municipality having the longest drainage durations and Taiwan Province having the shortest drainage durations. The findings could provide scientific support for modifying the drainage and impoundment phases of coastal aquaculture ponds to achieve the win–win goal of improving economic development and protecting waterbirds or improving offshore water quality.
确定并绘制沿海水产养殖池塘及其排水和蓄水动态图
沿海水产养殖池塘的可持续管理可实现粮食和经济效益与包括水鸟在内的生态保护之间的双赢。本研究收集了 2021 年 7 月至 2022 年 6 月的 5790 幅大地遥感卫星和哨兵-2 号协调影像,以及 2021 年 7 月、2021 年 8 月和 2022 年 6 月的 498 幅哨兵-1 号影像作为补充数据,计算了多个水域指数。利用大津算法区分水域和非水域区域,并利用萨维茨基-戈莱滤波法优化时间序列,利用 SNIC 识别了沿海水产养殖池塘。此外,还利用动态时间经线-均值++方法确定了其排水和蓄水阶段。最后,生成了中国全国尺度的 30 米分辨率新数据集,其池塘图和排水与蓄水阶段的总体精度均超过 90%。我们的观测结果显示,全国水产养殖池塘总面积为 7919.53 平方公里,其中山东省池塘面积最大。在沿海养殖池塘中,27.95%为季节性养殖池塘,70.32%为常年养殖池塘,1.49%为废弃养殖池塘。排水开始日期、结束日期和持续时间是根据水比例时间序列的突然变化计算得出的。排水开始日期集中在 9 月至 12 月,排水结束日期为 1 月至 4 月。沿海养殖池塘的排水持续时间从两周到六个月不等,其中上海市的排水持续时间最长,台湾省的排水持续时间最短。研究结果可为修改沿海养殖池塘的排水和蓄水阶段提供科学支持,以实现改善经济发展和保护水鸟或改善近海水质的双赢目标。
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来源期刊
International journal of applied earth observation and geoinformation : ITC journal
International journal of applied earth observation and geoinformation : ITC journal Global and Planetary Change, Management, Monitoring, Policy and Law, Earth-Surface Processes, Computers in Earth Sciences
CiteScore
12.00
自引率
0.00%
发文量
0
审稿时长
77 days
期刊介绍: The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.
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