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基于无人机遥感的互花米草长势参数提取与相关性分析

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本文以盐城滨海湿地部分区域为研究区,利用无人机多光谱激光雷达融合技术提取互花米草(Spartina alterniflora)不同物候期的冠层高度、植被指数、覆盖度和倒伏率等长势参数,计算冠层高度与植被指数及其他参数的相关系数并构建了回归模型.结果表明:(1)枯萎期至成熟期的冠层高度逐渐增加,自海向陆的冠层高度整体逐渐减小;枯萎期至开花期的归一化植被指数(normalized difference vegetation index,NDVI)逐渐增加,成熟期的NDVI减小,自海向陆的NDVI整体逐渐减小.(2)非枯萎期的冠层高度与植被指数、覆盖度、倒伏率和空间位置显著相关.(3)冠层高度与植被指数分布存在空间异质性,地理加权回归(geographically weighted regression,GWR)在模型精度和空间异质性分析上均优于普通最小二乘回归(ordinary least square,OLS).
Extraction and correlation analysis of growth parameters of Spartina alterniflora based on UAV remote sensing
With some areas of Yancheng coastal wetland as the study area,the canopy height,vegetation index,coverage and lodging rate of Spartina alterniflora were extracted by UAV multi-spectral lidar fusion technology in different phenological periods.The temporal and spatial variation characteristics of canopy height and vegetation index were analyzed,and the correlation coefficients between canopy height and vegetation index and other parameters were calculated.Three regression models were constructed.The results show that:(1)The canopy height of Spartina alterniflora gradually increased from withering stage to mature stage,and the canopy height gradually decreased as a whole from sea to land.The NDVI gradually increased from the wilting period to the flowering period,while the NDVI decreased in mature stage,and the NDVI gradually decreased from sea to land.(2)The canopy height was significantly correlated with vegetation index,coverage,lodging rate and spatial position in non-withering period.(3)There was spatial heterogeneity in the distribution of canopy height and vegetation index of Spartina alterniflora,and GWR was superior to OLS in model accuracy and spatial heterogeneity analysis.

UAVcanopy heightspartina alternifloravegetation indexgeographically weighted regression

汪煜、谈俊忠、张梅、朱振宇

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南京大学金陵学院,江苏 南京 210089

自然资源部海岸带开发与保护重点实验室,江苏 南京 210024

南京大学地理与海洋科学学院,江苏 南京 210023

南京财经大学经济学院,江苏 南京 210023

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无人机 冠层高度 互花米草 植被指数 地理加权回归

自然资源部海岸带开发与保护重点实验室开放基金

2021CZEPK10

2024

海洋环境科学
国家海洋局海洋环境保护研究所 国家海洋环境监测中心 中国海洋科学学会

海洋环境科学

CSTPCD北大核心
影响因子:0.66
ISSN:1007-6336
年,卷(期):2024.43(1)
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