2015-2019年海南岛1m红树林变化数据集

红树林是具有重要的生态及生态经济服务价值的海岸带湿地生态系统。由于自然因素和人类活动的影响，红树林又是全球最脆弱的生态系统之一。红树林的监测是一项需要长久开展的工作。遥感技术的发展为红树林监测提供了一种高效便利的手段。本研究利用2015、2017和2019年共计3期国产高分2号（GF-2）数据，采用高斯径向基核函数，惩罚因子为100，Gamma函数为0.022的支持向量基方法，并结合野外调查资料，获取了2015–2019年3期海南岛红树林变化数据集。本数据集总体分类精度大于99%，数据量为58.7 MB。本数据集可作为红树林时空变化分析的基础数据，也能为红树林湿地生态系统恢复、保护和管理提供决策支持，为海南省生态环境监管提供数据支持。

Mangroves are coastal wetland ecosystems with significant ecological and eco-economic service values. Affected by natural factors and human activities, mangroves are also among the most vulnerable ecosystems globally. Mangrove monitoring is a long-term and sustained task. The advancement of remote sensing technology has provided an efficient and convenient approach for mangrove monitoring. This study utilized three phases of domestic Gaofen-2 (GF-2) satellite data acquired in 2015, 2017 and 2019, adopted the support vector machine (SVM) method with a Gaussian radial basis function kernel, a penalty parameter of 100, and a gamma parameter of 0.022, combined with field survey data, to obtain the three-phase mangrove change dataset for Hainan Island covering the period 2015–2019. The overall classification accuracy of this dataset exceeds 99%, with a total data volume of 58.7 MB. This dataset can serve as fundamental data for spatiotemporal change analysis of mangroves, provide decision-making support for the restoration, protection and management of mangrove wetland ecosystems, and supply data support for ecological and environmental supervision in Hainan Province.

搜集汇总

背景与挑战

背景概述

该数据集是基于2015、2017和2019年国产GF-2遥感影像，结合野外调查数据生成的海南岛红树林变化矢量数据集，空间分辨率为1米，时间跨度为2015至2019年。数据集采用支持向量基方法处理，总体分类精度超过99%，数据量为58.7 MB，主要用于分析红树林时空动态变化，并为红树林湿地生态系统的保护、恢复和管理以及海南省生态环境监管提供科学数据支持。