【目的】研究芦苇(Phragmites australis)湿地土地类型变化、监测覆被特征,为湿地保护和开发提供参考。【方法】基于2017—2023年9月扎龙湿地Sentinel-2遥感影像,制作了包含湖泊、芦苇地、建筑地、耕地、盐碱地5种土地类型的遥感影像数据集。通过视觉状态空间(visual state space model,Vmamba)联合注意力机制并结合水体指数NDWI生成水体掩膜对研究区进行信息提取,统计各土地类型的位置和面积变化信息。利用像元二分法提取植被覆盖度(fractional vegetation cover,FVC),计算叶面积指数(leaf area index,LAI)和生态质量指数(ecosystem quality index,EQI)。【结果】通过本研究提出的方法对研究区内分布信息进行提取,整体精度(overall accuracy,OA)为80.85%、平均交并比(mean intersection over union,MIoU)为71.59%,宏观平均F1值(macro-F1,MF1)为79.93%。2017—2023年,在扎龙湿地内湖泊、芦苇地的覆盖面积呈增加趋势;耕地、建筑地的覆盖面积呈减少趋势;盐碱地的覆盖面积呈波动趋势。植被覆盖度、生态质量指数先升高后降低,与中国气候公报内容基本一致。【结论】Vmamba联合注意力机制并结合水体掩膜的模型,在湿地信息提取方面效果良好,一定程度上提高土地利用分类与变化监测的精度。植被覆盖度、叶面积指数、生态质量指数的监测对湿地资源管理与可持续利用提供借鉴。

【Objective】This study aims to reveal the dynamic evolution patterns of reed wetland land types in Zhalong Wetland and quantify the spatiotemporal variations of their coverage characteristics, providing scientific basis for regional wetland ecological conservation and sustainable development.【Method】Based on Sentinel-2 multispectral remote sensing imagery from 2017 to September 2023 in Zhalong Wetland, a multi-temporal remote sensing dataset was constructed, containing five land categories: lake, reed bed, construction land, arable land, and saline-alkali land. An integrated classification approach combining the attention-based Vmamba model with NDWI water mask was proposed to extract spatial distributions and area changes of each land type. Meanwhile, the fractional vegetation cover (FVC) was inverted using the dimidiate pixel model, and leaf area index (LAI) and ecosystem quality index (EQI) were calculated.【Result】Classification results demonstrated that the overall accuracy (OA) of our algorithm was 80.85%, the mean intersection over union (MIoU) was 71.59%, and macro-F1 score (MF1) was 79.93%. During the study period, lake and reed bed areas in Zhalong Wetland showed expanding trends, while cultivated land and built-up land areas continuously decreased. Saline-alkali land area fluctuated dynamically. Both FVC and EQI exhibited a first-increasing-then-decreasing trend, which was generally consistent with the content of Chinese Climate Bulletin.【Conclusion】The proposed change-monitoring model integrating attention-based Vmamba and water mask demonstrates high applicability in wetland information extraction, significantly improving classification accuracy and dynamic monitoring precision. The collaborative monitoring results of FVC, LAI, and EQI provides reference for wetland resource management and sustainable utilization.