摘要
为了更加准确有效地监测田间尺度上土壤盐渍化的时空分布,针对农田-裸地交错带,提出先区分农田和裸地两种景观再进行盐渍化提取的策略,首次使用高分二号数据对艾比湖流域农田-裸地交错带干湿两季的盐渍化进行提取和分析。结果表明:本文方法的总精度达到95%以上,且减少了常规分类中经常出现的"椒盐现象";纹理特征的加入使农田类别的光谱可分性从1.5以下提升到1.7,进而增加了提取农田边界的精确性;研究区干季的盐渍化面积较湿季上升了50%左右,中度盐渍化的面积比例上升最大为27%,干湿季差异非常明显。本研究推进了国产高分二号亚米级数据在干旱区农田-裸地交错带盐渍化提取的研究与应用,也为干旱区农田灌溉方案的制定和次生盐渍化灾害的控制提供信息支持。
Soil salinization is one of the main degradation problems in arid and semiarid regions.With the improvement of the resolution of remote sensing images,the salinization monitoring has gradually shifted from regional scale to field scale.However,present salinization of field scale in China still adopts regional scale classification method.In order to monitor the spatial and temporal distribution of soil salinization at the field scale more accurately,in this paper,the strategy to distinguish farmland from bareland ecotone first was proposed and GF-2 data were used to extract and analyze the salinization in dry and wet season in the farmland-bareland ecotone of Aibi Lake Basin.The results show that:(1)The total precision of the method is over 95%,and the phenomenon of“salt and pepper”is reduced.(2)The addition of texture features increased the spectral separability of cropland from 1.5 to 1.7 and increased the classification accuracy.(3)The area of salinization in dry season increased by 50%compared with that in wet season,and the area of moderate salinization increased most by 27%.The difference between dry and wet seasons was very obvious.This research promoted the salinization extraction research of domestic-made GF-2 sub-meter data in the farmland-bareland ecotone.It is helpful to the formulation of farmland irrigation scheme in arid area and provides information for secondary salinization disaster control.
作者
缪琛
丁建丽
占玉林
顾行发
余涛
MIAO Chen;DING Jian-li;ZHAN Yu-lin;GU Xing-fa;YU Tao(College of Resources and Environment Sciences,Xinjiang University,Urumqi 830046,China;Key Laboratory of Oasis Ecosystem of Ministry of Education,Xinjiang University,Urumqi 830046,China;State Key Laboratory of Remote Sensing Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100101,China;Chinese Research Academy of Environmental Sciences,Beijing 100012,China)
出处
《桂林理工大学学报》
CAS
北大核心
2018年第1期69-77,共9页
Journal of Guilin University of Technology
基金
国家自然科学基金项目(41371416
U1303381
41261090
41161063)
新疆维吾尔自治区科技支疆项目(201591101)
新疆维吾尔自治区重点实验室课题(2016D03001)
新疆区重点实验室专项基金(2014KL005)
高分辨率对地观测系统重大专项(Y4D00100GF)
