摘要
为了明确辽东湾植被长势的时空变化特征,本文针对传统的遥感影像信息提取速度缓慢、效率较低等问题,基于奥维互动地图(Ovid interactive map,OMAP)平台,利用Landsat遥感影像提取1990—2019年辽东湾生长季NDVI数据,采用一元线性回归对NDVI时空变化特征进行讨论。结果表明:1)以2010年为转折点,近30年来,辽东湾地表植被NDVI呈现先增后减再增的变化趋势,植被覆盖总面积变化较小,但中高植被覆盖区(0.6<NDVI<0.8)和高植被覆盖区(0.8<NDVI<1)所占比例显著增加,低植被覆盖度(0.2<NDVI<0.4)显著减少。2)辽东湾地表NDVI空间分布差异明显,呈现由辽河口三角洲向两侧逐步下降的趋势。受海域资源开发活动影响,自陆向海方向,NDVI呈现先增后低的空间特征。综上,辽东湾NDVI的时空变化受人类开发活动、人为生态修复和海岸带自我恢复能力的共同影响,可作为一种重要定量因子为海岸带环境承载力分析、生态修复评价提供基础数据。
In order to clarify the spatial and temporal variation characteristics of vegetation growth in Liaodong Bay,aiming at the problems of slow speed and low efficiency of traditional remote sensing image information extraction,based on Ovid interactive map(OMAP)platform,Landsat remote sensing images were used to extract the NDVI data of Liaodong Bay during the growing season from 1990 to 2019,and the spatial and temporal variation characteristics of NDVI was discussed by using one-dimensional linear regression.The results show that:(1)Taking 2010 as the turning point,NDVI of surface vegetation in Liaodong Bay showed a trend of first increase,then decrease and then increase during the past 30 years.The total area of vegetation coverage have less change,while the proportion of medium-high vegetation coverage(0.6<NDVI<0.8)and high vegetation coverage(0.8<NDVI<1)increased significantly,low vegetation coverage(0.2<NDVI<0.4)decreased significantly.(2)The spatial distribution of NDVI in Liaodong Bay have obvious differences,which shows a trend of gradual decrease from the Liaohe estuary delta to both sides.Affected by the development of coastal resources,NDVI increased firstly and then decreased from land to sea.In conclusion,the spatial and temporal variation of NDVI in Liaodong Bay is influenced by human development activities,anthropogenic ecological restoration and coastal self-recovery ability,which can be used as an important quantitative factor to provide basic data for coastal environmental carrying capacity analysis and ecological restoration evaluation.
作者
陈俊任
周超
CHEN Junren;ZHOU Chao(Jiangxi Ganhe Surveying and Mapping Geographic Information Co.,Ltd.,Shangrao 334700,China;National Marine Environmental Monitoring Center,Dalian 116023,China)
出处
《测绘与空间地理信息》
2023年第12期66-69,共4页
Geomatics & Spatial Information Technology
关键词
OMAP
植被指数
时空变化
OMAP
vegetation index
spatial and temporal variations
