首页 >  , Vol. , Issue () : -

摘要

全文摘要次数: 147 全文下载次数: 477
引用本文:

DOI:

10.11834/jrs.20211033

收稿日期:

2021-01-19

修改日期:

2021-06-28

PDF Free   EndNote   BibTeX
1990-2020年粤港澳大湾区红树林动态变化遥感监测
袁艺馨1, 温庆可2, 徐进勇2, 王晨3, 赵晓丽2, 刘朔2, 解睿2
1.①中国科学院空天信息创新研究院 国家遥感应用工程技术研究中心 ②中国科学院大学;2.中国科学院空天信息创新研究院 国家遥感应用工程技术研究中心;3.生态环境部卫星环境应用中心 水生态环境遥感部
摘要:

粤港澳大湾区规划建设成为国际竞争力一流湾区和世界级城市群,资源集约利用、生态环境优美是国际湾区全面建成的重要方面之一。粤港澳大湾区拥有丰富的滨海红树林湿地,在消浪减风、保护生物多样性、净化海水及固碳等方面发挥重要生态作用。湾区红树林经历过人类开发活动的破坏,也受到了湿地保护政策指引下的良好恢复,但由于调查手段不一及监测时效性限制,目前仍缺乏标准一致的数据以科学客观地阐明粤港澳大湾区红树林湿地的历史变化与最新现状。本文利用现状监测和动态更新相结合的方法,构建了1990-2020年期间共计4个时段标准一致、前后可比的红树林分布与变化数据库;利用高性能云计算Google Earth Engine平台(GEE),提出了一种红树林现状快速更新方法。研究表明:(1)利用GEE平台可快速提取红树林初步分类结果作为动态更新的参考底图,大大提高了目视解译动态更新方法的速度,为红树林高效管理提供及时的数据支持。(2)粤港澳大湾区过去三十年的红树林面积净增长10.21km2,红树林总体得到了较好的恢复和保护, 但是在1990-2000年期间,红树林是净减少的时期,净减少4.60km2,主要是被新增养殖坑塘、人工用地占用;2000年以来,粤港澳大湾区红树林面积持续增加,红树林公园和自然保护区的建设对红树林存量面积起到了积极作用。(3)虽然红树林自然分布多见于潮间带,但是粤港澳大湾区2010年之后通过建设红树林公园恢复的红树林,有向内陆方向延伸建设的态势。

Remote sensing monitoring of mangrove forest changes from 1990 to 2020 in the Guangdong-Hong Kong-Macao Greater Bay Area
Abstract:

The Guangdong-Hong Kong-Macao Greater Bay Area is currently under the development of a competitively international bay area and a world-class city cluster. One of the important aspects of such a comprehensive development goal is efficient and eco-friendly resources usage. The coastal mangrove wetlands are abundant in this area where mangrove plays an important ecological role in reducing waves and wind, protecting biodiversity, purifying sea, and sequestering carbon. The mangrove forests in the Bay Area have been destructed in the early years caused by human activities and afterwards been well restored under the guidance of the wetland protection policy. However, to scientifically and objectively clarify the historical changes and the latest status quo of mangrove wetlands at the regional scale, a consistent and standard dataset is still lacking due to the inconsistent investigation methods and the limitation of the timely monitoring. By utilizing status quo monitoring combined with dynamic updating method, the constructed database in this paper is standard, consistent, and scientifically comparable among different years. In specific, a dynamic updating method based on a high-performance cloud computing platform, Google Earth Engine (GEE), has been proposed in the last time period updating, which largely improves the updating efficiency. Using satellite remote sensing images, this paper constructs a long-term serial of mangrove distributions in 1990, 2000, 2010, 2018, and 2020. In addition, mangrove changes between these four time periods were also quantified. Our results showed that: (1) An efficient mangrove dynamic updating method is available by utilizing the GEE platform, which makes timely and constant mangrove database construction and yearly updating is feasible at a regional scale. The timely database will contribute to the efficient management of mangrove by the corresponding department. (2) Over the past three decades, the mangroves forests in the Guangdong-Hong Kong-Macao Greater Bay Area have been well restored and protected. The total area of mangrove forests has increased by 10.21 km2 from 1990 to 2020. However, during 1990-2000, the area has decreased by 4.60 km2 due to the occupation of newly-built fish/shrimp ponds and artificial construction. Since 2000, the mangrove area has increased steadily thanks to the construction of mangrove parks and nature reserves. (3) Although the natural growing mangrove forests are mostly found in the intertidal zones, the newly planted mangroves restored as mangrove parks have a tendency of extending inland slightly after 2010.

本文暂时没有被引用!

欢迎关注学报微信

遥感学报交流群 分享按钮