地理科学进展 ›› 2016, Vol. 35 ›› Issue (5): 655-663.doi: 10.18306/dlkxjz.2016.05.012
• 研究论文 • 上一篇
袁玉娟1,2(), 尹云鹤1,**(
), 戴尔阜1, 刘荣高3, 吴绍洪1
接受日期:
2015-05-01
出版日期:
2016-05-27
发布日期:
2016-05-27
通讯作者:
尹云鹤
作者简介:
作者简介:袁玉娟(1989-),女,河北衡水人,硕士生,主要从事植被遥感研究,E-mail:
基金资助:
Yujuan YUAN1,2(), Yunhe YIN1,*(
), Erfu DAI1, Ronggao LIU3, Shaohong WU1
Accepted:
2015-05-01
Online:
2016-05-27
Published:
2016-05-27
Contact:
Yunhe YIN
Supported by:
摘要:
全球变化背景下,准确获取森林覆盖是监测森林资源动态、实现林业可持续发展的重要基础。为将省级尺度森林资源清查面积资料空间化,以黑龙江省为例,利用1999-2003年该省森林资源清查面积数据,结合2000年500 m分辨率的MODIS数据,构建了基于阈值分割的森林类型遥感识别方法。该方法利用不同地表覆被类型归一化植被指数时间序列的季节分异特征,以森林资源清查面积为标准,设定森林类型的划分阈值,识别了黑龙江省森林类型的空间分布。最后,基于分层随机抽样和精度评价方法,表明森林类型识别结果与地面参考数据具有较高的一致性,总体分类精度为78.1%;特别是季节特征明显的落叶林,精度可达80%以上。本文所构建的方法可将森林清查统计数据进行准确的空间定位,同时结合多期森林资源连续清查资料和遥感信息,可为识别并量化区域生态系统生物量和碳库变化等提供科技支撑。
袁玉娟, 尹云鹤, 戴尔阜, 刘荣高, 吴绍洪. 基于阈值分割的黑龙江省森林类型遥感识别[J]. 地理科学进展, 2016, 35(5): 655-663.
Yujuan YUAN, Yunhe YIN, Erfu DAI, Ronggao LIU, Shaohong WU. Forest cover classification based on remote sensing threshold consistent with statistics in Heilongjiang Province[J]. PROGRESS IN GEOGRAPHY, 2016, 35(5): 655-663.
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