自然资源学报 ›› 2019, Vol. 34 ›› Issue (5): 1079-1092.doi: 10.31497/zrzyxb.20190514
收稿日期:
2018-08-01
修回日期:
2019-01-24
出版日期:
2019-05-28
发布日期:
2019-05-28
作者简介:
作者简介:刘文斌(1994- ),男,湖北鄂州人,硕士,研究方向为遥感影像的地学应用。E-mail:
基金资助:
Wen-bin LIU(), Jian-bin TAO(
), Meng XU, Rui-qing CHEN, Yang GUO
Received:
2018-08-01
Revised:
2019-01-24
Online:
2019-05-28
Published:
2019-05-28
摘要:
油菜是我国第五大农作物和重要的油料作物。获取油菜的种植分布信息对食用油市场的发展和粮食安全具有重要意义。两湖平原泛指包括湖北江汉平原和湖南洞庭湖平原在内的广大平原区域,是我国重要的粮棉油生产基地,“湖广熟,天下足”指的就是这一地区。由于耕地破碎,种植结构复杂,两湖平原轮作和间作的现象非常普遍,传统的遥感监测方法难以准确地获取冬油菜的空间分布。本文提出了一种基于人工神经网络ANN的子像元冬油菜提取方法,将时间序列MODIS-EVI和GF-1数据结合以提取两湖平原的冬油菜丰度信息。首先采用顺序前向选择SFS算法从时间序列MODIS-EVI数据集中进行物候特征优选;然后构建融合多源数据的ANN模型估算两湖平原的冬油菜丰度。结果表明:基于ANN方法获取的冬油菜分布具有较高的精度(ANN估算结果与GF-1和统计数据的验证精度分别为91.54%和74.70%),在利用中分辨率影像进行大尺度冬油菜精细制图方面显示出巨大潜力,可为我国冬油菜的空间分布制图和时空格局分析提供技术方法。
刘文斌, 陶建斌, 徐猛, 陈瑞卿, 郭洋. 基于人工神经网络多源数据融合的子像元冬油菜提取——以两湖平原为例[J]. 自然资源学报, 2019, 34(5): 1079-1092.
Wen-bin LIU, Jian-bin TAO, Meng XU, Rui-qing CHEN, Yang GUO. A study of winter rape extraction at sub-pixel fusing multi-source data based on Artificial Neural Networks:A case study of Jianghan and Dongting Lake Plain[J]. JOURNAL OF NATURAL RESOURCES, 2019, 34(5): 1079-1092.
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