沿海地区红树林的长期动态和安全:利用Landsat和Sentinel-2数据的紧急遥感分析。

IF 4.9 3区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES
Wenyang Xu , Muhammad Haseeb , Xiangtian Zheng , Zainab Tahir , Syed Amer Mahmood , Mona S. Ramadan , M. Abdullah-Al-Wadud , Aqil Tariq
{"title":"沿海地区红树林的长期动态和安全:利用Landsat和Sentinel-2数据的紧急遥感分析。","authors":"Wenyang Xu ,&nbsp;Muhammad Haseeb ,&nbsp;Xiangtian Zheng ,&nbsp;Zainab Tahir ,&nbsp;Syed Amer Mahmood ,&nbsp;Mona S. Ramadan ,&nbsp;M. Abdullah-Al-Wadud ,&nbsp;Aqil Tariq","doi":"10.1016/j.marpolbul.2025.118789","DOIUrl":null,"url":null,"abstract":"<div><div>Mangroves are essential to coastal ecosystem health, providing natural defenses against erosion and serving as key habitats. This study investigates long-term mangrove cover and fragmentation trends in Pakistan's Indus Delta and Sandspit regions using Landsat imagery (1988–2024) and Sentinel-2 datasets (2019, 2024). Classification results show significant mangrove expansion, with Sandspit increasing from 10.22 km<sup>2</sup> in 1988 to 15.64 km<sup>2</sup> in 2024, and the Indus Delta expanding from 305.54 km<sup>2</sup> to 1002.82 km<sup>2</sup> over the same period. Sentinel-2 data showed slightly higher cover estimates, with values of 15.24 km<sup>2</sup> and 15.98 km<sup>2</sup> at Sandspit and 895.18 km<sup>2</sup> and 1009.76 km<sup>2</sup> for the Indus Delta in 2019 and 2024, respectively. Canopy density analysis from 1988 to 2024 categorized mangroves based on Normalized difference vegetation index (NDVI) values into sparse, moderate, and thick-density classes. NDVI thresholds (sparse: 0.1–0.3; moderate: 0.3–0.5; thick: &gt;0.5) were used to assess canopy density. Results indicated densification of mangrove forests and a shift from sparse to dense vegetation, reflecting ecological recovery. Classification accuracy exceeded 96 % with high kappa values (&gt;0.93). Due to field access limitations, accuracy assessments were conducted using visual validation via high-resolution Google Earth imagery. Fragmentation and transition analyses further revealed dynamic patterns and resilience of these ecosystems under environmental stressors. Comparative analysis of Landsat and Sentinel-2 data revealed high classification accuracy, with overall accuracies exceeding 96 % and kappa values above 0.93. The findings also provide actionable insights for national and provincial forest departments, supporting policy recommendations aimed at enhancing mitigation and adaptation strategies in response to landform changes and climate variability.</div></div>","PeriodicalId":18215,"journal":{"name":"Marine pollution bulletin","volume":"222 ","pages":"Article 118789"},"PeriodicalIF":4.9000,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Long-term mangrove dynamics and safety in coastal areas: An emergency Remote Sensing-based analysis using Landsat and Sentinel-2 Data\",\"authors\":\"Wenyang Xu ,&nbsp;Muhammad Haseeb ,&nbsp;Xiangtian Zheng ,&nbsp;Zainab Tahir ,&nbsp;Syed Amer Mahmood ,&nbsp;Mona S. Ramadan ,&nbsp;M. Abdullah-Al-Wadud ,&nbsp;Aqil Tariq\",\"doi\":\"10.1016/j.marpolbul.2025.118789\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Mangroves are essential to coastal ecosystem health, providing natural defenses against erosion and serving as key habitats. This study investigates long-term mangrove cover and fragmentation trends in Pakistan's Indus Delta and Sandspit regions using Landsat imagery (1988–2024) and Sentinel-2 datasets (2019, 2024). Classification results show significant mangrove expansion, with Sandspit increasing from 10.22 km<sup>2</sup> in 1988 to 15.64 km<sup>2</sup> in 2024, and the Indus Delta expanding from 305.54 km<sup>2</sup> to 1002.82 km<sup>2</sup> over the same period. Sentinel-2 data showed slightly higher cover estimates, with values of 15.24 km<sup>2</sup> and 15.98 km<sup>2</sup> at Sandspit and 895.18 km<sup>2</sup> and 1009.76 km<sup>2</sup> for the Indus Delta in 2019 and 2024, respectively. Canopy density analysis from 1988 to 2024 categorized mangroves based on Normalized difference vegetation index (NDVI) values into sparse, moderate, and thick-density classes. NDVI thresholds (sparse: 0.1–0.3; moderate: 0.3–0.5; thick: &gt;0.5) were used to assess canopy density. Results indicated densification of mangrove forests and a shift from sparse to dense vegetation, reflecting ecological recovery. Classification accuracy exceeded 96 % with high kappa values (&gt;0.93). Due to field access limitations, accuracy assessments were conducted using visual validation via high-resolution Google Earth imagery. Fragmentation and transition analyses further revealed dynamic patterns and resilience of these ecosystems under environmental stressors. Comparative analysis of Landsat and Sentinel-2 data revealed high classification accuracy, with overall accuracies exceeding 96 % and kappa values above 0.93. The findings also provide actionable insights for national and provincial forest departments, supporting policy recommendations aimed at enhancing mitigation and adaptation strategies in response to landform changes and climate variability.</div></div>\",\"PeriodicalId\":18215,\"journal\":{\"name\":\"Marine pollution bulletin\",\"volume\":\"222 \",\"pages\":\"Article 118789\"},\"PeriodicalIF\":4.9000,\"publicationDate\":\"2025-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Marine pollution bulletin\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0025326X25012652\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Marine pollution bulletin","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0025326X25012652","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

红树林对沿海生态系统的健康至关重要,提供了抵御侵蚀的天然屏障,并作为重要的栖息地。本研究利用Landsat图像(1988-2024年)和Sentinel-2数据集(2019年、2024年)调查了巴基斯坦印度河三角洲和沙口地区红树林的长期覆盖和破碎化趋势。分类结果表明,红树林扩张显著,沙嘴从1988年的10.22 km2增加到2024年的15.64 km2,印度河三角洲同期从305.54 km2扩大到1002.82 km2。Sentinel-2数据显示,2019年和2024年,沙嘴和印度河三角洲分别为15.24 km2和15.98 km2和895.18 km2和1009.76 km2,覆盖估算值略高。1988 - 2024年林冠密度分析基于归一化植被指数(NDVI)将红树林划分为稀疏、中等和厚密度三类。NDVI阈值(稀疏:0.1-0.3,中等:0.3-0.5,厚:> -0.5)用于评价冠层密度。结果表明,红树林的密度增加,植被由稀疏向茂密转变,反映了生态恢复。分类准确率超过96%,kappa值高(>.93)。由于实地访问的限制,使用高分辨率谷歌地球图像进行视觉验证进行准确性评估。破碎化和过渡分析进一步揭示了这些生态系统在环境压力下的动态模式和恢复力。Landsat和Sentinel-2数据的分类精度较高,总体精度超过96%,kappa值在0.93以上。调查结果还为国家和省级森林部门提供了可行的见解,支持旨在加强缓解和适应战略以应对地形变化和气候变率的政策建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Long-term mangrove dynamics and safety in coastal areas: An emergency Remote Sensing-based analysis using Landsat and Sentinel-2 Data
Mangroves are essential to coastal ecosystem health, providing natural defenses against erosion and serving as key habitats. This study investigates long-term mangrove cover and fragmentation trends in Pakistan's Indus Delta and Sandspit regions using Landsat imagery (1988–2024) and Sentinel-2 datasets (2019, 2024). Classification results show significant mangrove expansion, with Sandspit increasing from 10.22 km2 in 1988 to 15.64 km2 in 2024, and the Indus Delta expanding from 305.54 km2 to 1002.82 km2 over the same period. Sentinel-2 data showed slightly higher cover estimates, with values of 15.24 km2 and 15.98 km2 at Sandspit and 895.18 km2 and 1009.76 km2 for the Indus Delta in 2019 and 2024, respectively. Canopy density analysis from 1988 to 2024 categorized mangroves based on Normalized difference vegetation index (NDVI) values into sparse, moderate, and thick-density classes. NDVI thresholds (sparse: 0.1–0.3; moderate: 0.3–0.5; thick: >0.5) were used to assess canopy density. Results indicated densification of mangrove forests and a shift from sparse to dense vegetation, reflecting ecological recovery. Classification accuracy exceeded 96 % with high kappa values (>0.93). Due to field access limitations, accuracy assessments were conducted using visual validation via high-resolution Google Earth imagery. Fragmentation and transition analyses further revealed dynamic patterns and resilience of these ecosystems under environmental stressors. Comparative analysis of Landsat and Sentinel-2 data revealed high classification accuracy, with overall accuracies exceeding 96 % and kappa values above 0.93. The findings also provide actionable insights for national and provincial forest departments, supporting policy recommendations aimed at enhancing mitigation and adaptation strategies in response to landform changes and climate variability.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Marine pollution bulletin
Marine pollution bulletin 环境科学-海洋与淡水生物学
CiteScore
10.20
自引率
15.50%
发文量
1077
审稿时长
68 days
期刊介绍: Marine Pollution Bulletin is concerned with the rational use of maritime and marine resources in estuaries, the seas and oceans, as well as with documenting marine pollution and introducing new forms of measurement and analysis. A wide range of topics are discussed as news, comment, reviews and research reports, not only on effluent disposal and pollution control, but also on the management, economic aspects and protection of the marine environment in general.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信