使用谷歌地球引擎云计算平台评估墨西哥西北部的红树林
Luis Valderrama-Landeros1, Carlos Troche-Souza1, José A Alcántara-Maya1
1Coordinación de Geomática, Comisión Nacional Para el Conocimiento y Uso de la Biodiversidad, Tlalpan, Ciudad de México, Mexico.
PloS one
|December 5, 2024
概括
遥感和谷歌地球引擎绘制了墨西哥的地图.
科学领域:
- 遥感和地理空间分析
- 生态与保护生物学 生态与保护生物学
- 气候变化科学 气候变化科学
背景情况:
- 红树林是重要的生态系统,但使用传统的实地调查具有挑战性.
- 太空遥感提供了一个解决方案,但往往需要大量的手工处理.
- 云计算平台越来越多地被用于大规模的红树林绘图和保护.
研究的目的:
- 分析红色红树林 (Rhizophora mangle) 和其他关键红树林物种的空间分布和变化率 (收益/损失).
- 评估2015年至2020年间墨西哥西北海岸沿线的红树林动态.
- 评估基于云的远程传感对于红树林监测的有效性.
主要方法:
- 利用来自Sentinel-2的双月复合红树林识别指数 (CMRI) 数据.
- 使用谷歌地球引擎云计算平台处理的数据.
- 2015年和2020年的分类红树林面积,计算面积变化和分类准确度.
主要成果:
- 2020年,研究区域的红树林面积达到42,865公 (红树林) 和139,602公 (其他物种).
- 在2015年至2020年期间,观察到1,817公的净减少.
- 分类准确度很高:2015年为90%,2020年为92%.
结论:
- 使用CMRI的基于云的遥感为大规模的红树林监测提供了一种有效的方法.
- 水产养殖的扩张和风是该地区红树林丧失的重要驱动因素.
- 调查结果支持国家为蓝色碳,红树林恢复和气候变化减缓战略的努力.
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