摘要
冰川时空演化不仅对河川径流、生物生存环境、地表形态产生巨大的影响,而且冰川本身对气候变化有着强烈的响应.在全球气候变暖背景下,对冰川长时间演化过程进行监测具有重要意义.文章利用TM影像、OLI影像,通过非监督分类法、监督分类法、比值阈值法、雪盖指数法(NDSI)、基于多尺度分割的面向对象法、基于神经网络的冰川识别方法对梅里雪山地区的冰川信息进行提取.结果表明,基于神经网络的冰川识别方法对于裸冰区及冰碛覆盖区的冰川信息提取效果相对较好,提取精度最高.在此基础上,基于ENVI深度学习模块,利用神经网络分类法解译1989、1998、2009年和2019年梅里雪山地区的冰川信息,并结合Google Earth和DEM数据,对其进行目视修正,最终得到了1989—2019年梅里雪山地区冰川边界变化图,结果显示1989—2019年梅里雪山地区的冰川退缩了23.77 km^(2),年均退缩0.79 km^(2),面积相对退缩率为17.03%,年均相对退缩率为0.57%.
Not only does the temporal and spatial evolution of glaciers have a great impact on river runoff,living environment and surface morphology,but glaciers themselves have a strong response to climate change as well.Under the background of global warming,it is of great significance to monitor the long-term evolution of glaciers.In this paper,TM image and OLI image are used to extract glacier information in Meili Snow Mountain Area through unsupervised classification,supervised classification,ratio threshold method,snow cover index(NDSI),object-oriented method based on multi-scale segmentation and glacier recognition method based on neural network.The results show that:it is of relatively good effect to extract information of bare ice area and moraine covered area glacier,by means of the glacier recognition method based on neural network;extraction accuracy is the highest.Subsequently,based on ENVI deep learning module,the glacier information of Meili Snow Mountain Area in 1989,1998,2009 and 2019 is interpreted by using neural network classification method,and then the interpretation is visually corrected combined with Google Earth and DEM data.Finally,the glacier boundary change map of Meili Snow Mountain Area from 1989 to 2019 is obtained.The results show that the glacier in Meili Snow Mountain Area retreated by 23.77 km^(2) from 1989 to 2019,with an average annual retreat rate of 0.79 km^(2);and the area relative retreat rate is 17.03%,with an average annual relative retreat rate of 0.57%.
作者
钟鼎杰
杨存建
ZHONG Ding-jie;YANG Cun-jian(Key Laboratory of Land Resources Evaluation and Monitoring in Southwest,Sichuan Normal University,Chengdu 610068,Sichuan,China;The Faculty of Geography and Resources Science,Sichuan Normal University,Chengdu 610068,Sichuan,China)
出处
《云南大学学报（自然科学版）》
CAS
CSCD
北大核心
2021年第5期942-952,共11页
Journal of Yunnan University(Natural Sciences Edition)
基金
国家重点研发计划(2018YFB0505303)
四川省科技厅重点研发项目(2020YFG0146).
关键词
冰川时空演化
梅里雪山
面向对象分类
神经网络
深度学习
冰川信息提取
temporal and spatial evolution of glaciers
Meili Snow Mountain
object oriented classification
neural network
deep learning
glacier information extraction
