乌梁素海水生植物生物量遥感估算

doi:10.13474/j.cnki.11-2246.2025.0909

摘要/Abstract

摘要： 水生植物在河流湖泊的生态平衡和水质净化中具有不可替代的重要性,生物量作为水生植物的重要生物理化指标,不仅是初级生产力的重要体现,还在评估水体中氮、磷储量及固碳量方面起到关键作用。针对乌梁素海复杂湖泊植被环境下水生植物生物量难以全面实地调查,并充分考虑挺水植物与沉水植物的光谱响应差异的问题,本文提出了一种结合遥感数据与实地调查数据的生物量估算模型,即结合Landsat 8影像和32个实地样点数据,基于ENVI和Matlab软件,采用偏最小二乘法构建乌梁素海水生植物生物量反演模型,并对其精度进行了评估。结果显示,挺水植物和沉水植物生物量反演模型的估算精度分别达92.93%和79.80%,这表明偏最小二乘回归模型适用于小样本条件下水生植物生物量的反演,在复杂湖泊植被环境中可以表现出良好的精度。乌梁素海在2023年6月和9月水生植物总生物量分别为78.16×10⁴和79.19×10⁴ t,挺水植物占比分别为78.03%和76.82%。相较于2023年6月,乌梁素海在9月挺水植物面积减少,平均单位面积生物量增长、空间分布无明显变化;沉水植物生物量则呈现明显增长,面积增加,接近1988年历史最高值(102.06 km²)。本文为乌梁素海后续湖泊生态管理、健康评估、水质修复等提供了科学依据。

关键词: 乌梁素海, 水生植物, 生物量反演建模, 偏最小二乘回归, 植被指数

Abstract: Aquatic vegetation plays an irreplaceable role in the ecological balance and water purification of rivers and lakes.Biomass,as an important biophysicochemical indicator of aquatic vegetation,not only reflects primary productivity but also plays a key role in assessing nitrogen and phosphorus reserves and carbon sequestration in water bodies.To address the challenge of comprehensively surveying aquatic vegetation biomass in the complex lake vegetation environment of Ulansuhai Lake and to account for the spectral response differences between emergent and submerged plants,this study proposes a biomass estimation model combining remote sensing data with field survey data.Using Landsat 8 imagery and data from 32 field sampling points,and based on ENVI and Matlab software,a partial least squares regression model for the retrieval of aquatic vegetation biomass in Ulansuhai Lake is developed and its accuracy assessed.The results showed that the estimation accuracies of the biomass retrieval models for emergent plants and submerged plants reached 92.93%and 79.80%,respectively.This indicates that the partial least squares regression model is suitable for retrieving aquatic vegetation biomass under small sample conditions and can achieve high accuracy in complex lake vegetation environments.The total biomass of aquatic vegetation in Ulansuhai Lake in June and September 2023 was 781.6×10⁴ and 791.9×10⁴ t,respectively,with emergent plants accounting for 78.03%and 76.82%.Compared to June 2023,the area of emergent plants in Ulansuhai Lake decreased in September,the average biomass per unit area increased,and there was no significant change in spatial distribution; The biomass of submerged plants show a notable increase,with the area expanding,approaching the historical high from 1988(102.06 km²).This research provides scientific evidence for subsequent lake ecological management,health assessment,and water quality restoration in Ulansuhai Lake.

Key words: Ulansuhai, aquatic vegetation, biomass inversion modeling, partial least squares regression, vegetation index

中图分类号:

P237

龚良琛, 徐东坡, 匡箴, 凡迎春, 董佳慧. 乌梁素海水生植物生物量遥感估算[J]. 测绘通报, 2025, 0(9): 51-58.

GONG Liangchen, XU Dongpo, KUANG Zhen, FAN Yingchun, DONG Jiahui. Remote sensing estimation of aquatic vegetation biomass in Ulansuhai Lake[J]. Bulletin of Surveying and Mapping, 2025, 0(9): 51-58.

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