Table_1_Remote sensing-based assessment of mangrove ecosystems in the Gulf Cooperation Council countries: a systematic review.pdf

Mangrove forests in the Gulf Cooperation Council (GCC) countries are facing multiple threats from natural and anthropogenic-driven land use change stressors, contributing to altered ecosystem conditions. Remote sensing tools can be used to monitor mangroves, measure mangrove forest-and-tree-level attributes and vegetation indices at different spatial and temporal scales that allow a detailed and comprehensive understanding of these important ecosystems. Using a systematic literature approach, we reviewed 58 remote sensing-based mangrove assessment articles published from 2010 through 2022. The main objectives of the study were to examine the extent of mangrove distribution and cover, and the remotely sensed data sources used to assess mangrove forest/tree attributes. The key importance of and threats to mangroves that were specific to the region were also examined. Mangrove distribution and cover were mainly estimated from satellite images (75.2%), using NDVI (Normalized Difference Vegetation Index) derived from Landsat (73.3%), IKONOS (15%), Sentinel (11.7%), WorldView (10%), QuickBird (8.3%), SPOT-5 (6.7%), MODIS (5%) and others (5%) such as PlanetScope. Remotely sensed data from aerial photographs/images (6.7%), LiDAR (Light Detection and Ranging) (5%) and UAV (Unmanned Aerial Vehicles)/Drones (3.3%) were the least used. Mangrove cover decreased in Saudi Arabia, Oman, Bahrain, and Kuwait between 1996 and 2020. However, mangrove cover increased appreciably in Qatar and remained relatively stable for the United Arab Emirates (UAE) over the same period, which was attributed to government conservation initiatives toward expanding mangrove afforestation and restoration through direct seeding and seedling planting. The reported country-level mangrove distribution and cover change results varied between studies due to the lack of a standardized methodology, differences in satellite imagery resolution and classification approaches used. There is a need for UAV-LiDAR ground truthing to validate country-and-local-level satellite data. Urban development-driven coastal land reclamation and pollution, climate change-driven temperature and sea level rise, drought and hypersalinity from extreme evaporation are serious threats to mangrove ecosystems. Thus, we encourage the prioritization of mangrove conservation and restoration schemes to support the achievement of related UN Sustainable Development Goals (13 climate action, 14 life below water, and 15 life on land) in the GCC countries.

海湾合作委员会（Gulf Cooperation Council, GCC）国家的红树林正面临自然与人为驱动的土地利用变化胁迫带来的多重威胁，导致生态系统状态发生改变。遥感技术可用于监测红树林，在不同时空尺度下获取红树林群落与单株树木的属性参数及植被指数，从而实现对这类重要生态系统的细致且全面的认知。本研究采用系统文献综述方法，梳理了2010年至2022年间发表的58篇基于遥感技术的红树林评估相关论文。本研究的主要目标为：考察红树林的分布范围与覆盖面积，以及用于评估红树林群落/树木属性的遥感数据源；同时探究该区域红树林所特有的关键重要性与威胁因素。红树林分布与覆盖面积主要通过卫星影像估算（占比75.2%），其中以源自Landsat（占比73.3%）、IKONOS（15%）、Sentinel（11.7%）、WorldView（10%）、QuickBird（8.3%）、SPOT-5（6.7%）、MODIS（5%）及其他（5%，如PlanetScope）的归一化差异植被指数（Normalized Difference Vegetation Index, NDVI）为主要手段。航空摄影/影像（6.7%）、激光雷达（Light Detection and Ranging, LiDAR，占比5%）与无人机（Unmanned Aerial Vehicles, UAV）/无人机（3.3%）类遥感数据的使用频次最低。1996年至2020年间，沙特阿拉伯、阿曼、巴林与科威特的红树林覆盖面积呈下降趋势。而卡塔尔的红树林覆盖面积则显著增长，同期阿拉伯联合酋长国（United Arab Emirates, UAE）的红树林覆盖面积相对稳定，这得益于该国政府通过直接播种与幼苗种植推广红树林造林与修复的保护举措。由于缺乏标准化方法、卫星影像分辨率及分类方法存在差异，不同研究报告的国家级红树林分布与覆盖变化结果存在分歧。现有研究需借助无人机-激光雷达地面验证来校准国家级与地方级的卫星遥感数据。城市开发驱动的滨海围垦与污染、气候变化引发的气温上升与海平面上升、极端蒸发导致的干旱与高盐度，均对红树林生态系统构成严重威胁。因此，本研究呼吁优先推进红树林保护与修复计划，助力海湾合作委员会国家实现相关联合国可持续发展目标（13 气候行动、14 水下生命、15 陆地生命）。