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Global Land Cover Heterogeneity Characteristics at Moderate Resolution for Mixed Pixel Modeling and Inversion
Wentao Yu1,2; Jing Li1; Qinhuo Liu1,2,3; Yelu Zeng4; Jing Zhao1; Baodong Xu1,3; Gaofei Yin5
第一作者单位State key laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China ; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
通讯作者单位State key laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China ; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China ; Joint Center for Global Change Studies, Beijing 100875, China
通讯作者Jing Li ; Qinhuo Liu
2018
发表期刊REMOTE SENSING
ISSN2072-4292
卷号10期号:6页码:856
文章类型Article
产权排序5
摘要Spatial heterogeneity is present in the land surface at every scale and is one of the key factors that introduces inherent uncertainty into simulations of land surface processes and parameter retrieval based on remotely sensed data. Because of a lack of understanding of the heterogeneous characteristics of global mixed pixels, few studies have focused on modeling and inversion algorithms in heterogeneous areas. This paper presents a parameterization scheme to describe land cover heterogeneity quantitatively by composition and boundary information based on high-resolution land cover products. Global heterogeneity features at the 1-km scale are extracted from the GlobeLand30' land cover dataset with a spatial resolution of 30 m. The composition analysis of global mixed pixels shows that only 35% of pixels over the land surface of Earth are covered by a single land cover type, namely, pure pixels, and only 25.8% are located in vegetated areas. Pixels mixed with water are more common than pixels mixed with any other non-vegetation type. The fragmentation analysis of typical biomes based on the boundary length shows that the savanna is the most heterogeneous biome, while the evergreen broadleaf forest is the least heterogeneous. Deciduous needleleaf forests are significantly affected by canopy height differences, while crop and grass biomes are less affected. Lastly, the strengths and limitations of the method and the application of the land cover heterogeneity characteristics extracted in this study are discussed.
关键词spatial heterogeneity land cover mixed pixel compositions fragmentation radiative transfer
DOI10.3390/rs10060856
收录类别SCI
语种英语
WOS记录号WOS:000436561800050
引用统计
文献类型期刊论文
条目标识符http://ir.imde.ac.cn/handle/131551/23435
专题数字山地与遥感应用中心
作者单位1.State key laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;
2.College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China;
3.Joint Center for Global Change Studies, Beijing 100875, China;
4.Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA;
5.Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
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GB/T 7714
Wentao Yu,Jing Li,Qinhuo Liu,et al. Global Land Cover Heterogeneity Characteristics at Moderate Resolution for Mixed Pixel Modeling and Inversion[J]. REMOTE SENSING,2018,10(6):856.
APA Wentao Yu.,Jing Li.,Qinhuo Liu.,Yelu Zeng.,Jing Zhao.,...&Gaofei Yin.(2018).Global Land Cover Heterogeneity Characteristics at Moderate Resolution for Mixed Pixel Modeling and Inversion.REMOTE SENSING,10(6),856.
MLA Wentao Yu,et al."Global Land Cover Heterogeneity Characteristics at Moderate Resolution for Mixed Pixel Modeling and Inversion".REMOTE SENSING 10.6(2018):856.
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