摘要
针对现有遥感变化检测方法中变化信息提取不够精确、对待检测影像数据质量和配准精度要求高等问题,提出一种利用时空自相关指数检测植被变化的方法。该方法先计算待检测区域两个时相影像数据的时空自相关指数,再设定目标函数确定变化检测最佳阈值,并以空间自相关指数为依据滤除噪声、提高检测精度,可以集成现有基于像元和基于对象的变化检测方法的相对优势,同时把握待检测区域的整体和细部特征变化。以长汀县人工植被和自然植被变化检测为案例的实证研究结果表明,所提出的方法在一定程度上克服了现有变化检测方法在精度、适应性与自动化程度3个方面的局限性,能更好地满足遥感影像变化检测的应用需求。
For dealing with the drawbacks of present change detection methods by remote sensing images,this article proposed a new method by making use of spatiotemporal autocorrelation index.The method firstly calculated the values of spatiotemporal autocorrelation index of two temporal remotely sensed image data of the detected area,then figured out the optimal threshold of change detection with object function,and filtered noises according to spatial autocorrelation index to improve the detection precision.In this way,the advantage of present pixel-based and object-based change detection methods could be integrated,so that the overall region changes and the detail feature changes could be obtained at the same time.The results of case study on change detection of artificial vegetation and natural vegetation in Changting County show that the proposed method is able to overcome the limitations of present methods in precision,applicability and automation at a certain extent,which will better meet the application demands of change detection by using remote sensing images.
出处
《遥感信息》
CSCD
北大核心
2016年第3期37-44,共8页
Remote Sensing Information
基金
"十二五"国家科技支撑计划项目(2013BAC08B02-01)
关键词
植被变化检测
时空自相关
最佳阈值
空间自相关
长汀县
vegetation change detection
spatiotemporal autocorrelation
optimal threshold
spatial autocorrelation
Changting County
