地球信息科学学报 ›› 2017, Vol. 19 ›› Issue (6): 846-853.doi: 10.3724/SP.J.1047.2017.00846
王九中1(), 田海峰2,3,*(
), 邬明权2, 王力2, 王长耀2
收稿日期:
2017-03-07
修回日期:
2017-04-14
出版日期:
2017-06-20
发布日期:
2017-06-20
通讯作者:
田海峰
E-mail:wangjiuzhong0103@163.com;haifengd_tg@163.com
作者简介:
作者简介:王九中(1967-),男,河北人,博士生,主要从事生态学研究。E-mail:
基金资助:
WANG Jiuzhong1(), TIAN Haifeng2,3,*(
), WU Mingquan2, WANG Li2, Wang Changyao2
Received:
2017-03-07
Revised:
2017-04-14
Online:
2017-06-20
Published:
2017-06-20
Contact:
TIAN Haifeng
E-mail:wangjiuzhong0103@163.com;haifengd_tg@163.com
摘要:
在省域尺度上,冬小麦遥感识别中存在冬小麦物候不一致、地表环境复杂、数据处理复杂、遥感数据冗余、选择适当的分类样本困难、分类精度低等问题,而遥感数据云平台为解决这些问题提供了良好的数据基础和数据处理能力。以河南省为研究区,以谷歌地球引擎(Google Earth Engine)云平台为支撑,基于2015年和2002年前后年份河南省冬小麦识别关键期内的2296景Landsat遥感影像,采用NDVI重构增幅算法建立冬小麦大区域遥感快速制图模型,实现了2015年和2002年的河南省冬小麦分布制图。结果表明:2015年和2002年冬小麦种植面积分别为56 055.79 km2和47 296.11 km2,与统计数据比,精度达到97%;2002-2015年,河南省冬小麦种植分布存在明显变化,总体播种面积呈增加趋势,2015年比2002年增加8759.69 km2,增幅为18.52%。与传统计算机冬小麦制图方法相比,基于Google Earth Engine云平台的数据处理和制图效率均获得千倍以上的提升。
王九中, 田海峰, 邬明权, 王力, 王长耀. 河南省冬小麦快速遥感制图[J]. 地球信息科学学报, 2017, 19(6): 846-853.DOI:10.3724/SP.J.1047.2017.00846
WANG Jiuzhong,TIAN Haifeng,WU Mingquan,WANG Li,Wang Changyao. Rapid Mapping of Winter Wheat in Henan Province[J]. Journal of Geo-information Science, 2017, 19(6): 846-853.DOI:10.3724/SP.J.1047.2017.00846
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