| 基于Landsat时间序列遥感影像的若尔盖高原湿地演变特征及其驱动因子定量分析 |
| 摘要点击 88 全文点击 3 投稿时间：2024-06-19 修订日期：2024-08-16 |
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| 中文关键词 高寒湿地 谷歌地球引擎（GEE） 长时间序列 景观格局 地理探测器 若尔盖 |
| 英文关键词 alpine wetland Google Earth Engine （GEE） long time series landscape pattern geographical detector Ruoergai |
| DOI 10.13227/j.hjkx.20250739 |
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| 中文摘要 |
| 若尔盖湿地作为我国最大的高海拔沼泽湿地，对碳循环和气候调节有着不可替代的作用. 但受全球变暖和人为因素影响，若尔盖湿地遭受了严重退化. 基于谷歌地球引擎（GEE）遥感云平台和时间序列的Landsat影像，利用随机森林算法绘制了1990~2020年若尔盖湿地精细分类图，并基于转移矩阵和景观格局指数分析湿地的时空变化规律和变化趋势，进而利用地理探测器定量分析湿地分布的影响因子. 研究表明：①1990~2020年湿地平均总面积达3 910 km2，若尔盖湿地以沼泽草甸和湿草甸为主，两者平均面积之和占湿地面积的83.13%. 1990~2010年，若尔盖湿地面积呈减少趋势，2010~2020年间湿地面积略有回升. ②1990~2020年，湿地面积减少主要体现为湿草甸退化成高寒草地. 不同湿地类型之间也存在转变情况，主要体现为沼泽草甸和湿草甸两者的转换. ③1990~2010年，湿地景观趋于破碎化和复杂化，聚集度下降. 2010~2020年，湿地破碎度有所降低，湿地景观变得集中. ④坡度、气温和坡向是影响湿地分布的主要自然因素. 同时，人口密度逐渐成为影响湿地分布的一个显著社会经济因素. 研究结果可为若尔盖湿地保护规划提供科学支撑，为该地区生态保护和高质量发展服务. |
| 英文摘要 |
| The Ruoergai Wetland， China's largest high-altitude marsh， plays a crucial role in the carbon cycle and climate management. However， the Ruoergai Wetland has experienced significant damage as a result of human activity and global warming. Based on the Google Earth Engine （GEE） cloud platform and time-series Landsat images， a random forest algorithm was applied to produce a detailed classification map of the Ruoergai wetlands from 1990 to 2020. Through the transfer matrix and landscape pattern index， the spatiotemporal change law and change trend of wetlands were analyzed. Then， the influencing factors of wetland distribution were quantitatively analyzed using geographic detector. The results showed that： ① The total wetland area averaged 3 910 km2 from 1990 to 2020， dominated by marshy and wet meadows， accounting for 83.13% of the total wetland area. From 1990 to 2010， the wetland area of Ruoergai showed a decreasing trend， and from 2010 to 2020， the wetland area increased slightly. ② From 1990 to 2020， the decrease in wetland area was mainly reflected in the degradation of wet meadows into alpine grassland. There were also changes among different wetland types， which were mainly reflected in the conversion of marsh meadows and wet meadows. ③ From 1990 to 2010， the wetland landscape tended to be fragmented and complicated， and the aggregation degree decreased. From 2010 to 2020， wetland fragmentation decreased， and the wetland landscape became more concentrated. ④ Slope， temperature， and aspect were the main natural factors affecting wetland distribution. At the same time， population density has gradually become a significant social and economic factor affecting wetland distribution. The results can provide scientific support for the wetland protection planning of Ruoergai and serve for the ecological preservation and high-level development of the area. |
