基于长时序Landsat数据的城市绿地定量遥感监测研究

Monitoring of urban greenspace based on long-time series Landsat imagery

针对遥感影像逐景监督分类方法提取城市绿地存在样本选择具有主观性、历史数据难以获得可靠样本等问题,本文在长时序陆地卫星(Landsat)数据定量化处理基础上,设计了城市绿地的遥感光谱指数模型,建立了一种城市绿地自动识别算法,然后利用1986—2017年的24期Landsat影像对重庆主城核心区的城市绿地进行了监测,获取了重庆城市绿地变化的30 m分辨率、30 a尺度的遥感时空专题数据。研究结果表明,本文方法可为长时序城市绿地监测提供技术与数据支撑。

Monitoring using time series of remote sensing data,has often been constrained by a lack of high-quality training and validation data,especially for historical satellite images.To address this problem,this paper designed a remote sensing index of urban greenspace based on long-time series quantitative Landsat imagery,andthen established an automatic identification algorithm for urban greenspace monitoring.Finally,24 Landsat imagery between 1986 and 2017 were applied to monitor the urban greenspace in the core area of Chongqing city,and the spatio-temporal thematic data of urban greenspace at 30-meter resolution and 30-year scale were obtained.This results showed that this method could provide technical and data support for long-time series urban greenspace monitoring.