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Open AccessArticle

Global Land Cover Heterogeneity Characteristics at Moderate Resolution for Mixed Pixel Modeling and Inversion

1
State key laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
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College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
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Joint Center for Global Change Studies, Beijing 100875, China
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Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA
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Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
*
Authors to whom correspondence should be addressed.
Remote Sens. 2018, 10(6), 856; https://doi.org/10.3390/rs10060856
Received: 16 April 2018 / Revised: 16 May 2018 / Accepted: 24 May 2018 / Published: 1 June 2018
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. View Full-Text
Keywords: spatial heterogeneity; land cover; mixed pixel; compositions; fragmentation; radiative transfer spatial heterogeneity; land cover; mixed pixel; compositions; fragmentation; radiative transfer
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MDPI and ACS Style

Yu, W.; Li, J.; Liu, Q.; Zeng, Y.; Zhao, J.; Xu, B.; Yin, G. Global Land Cover Heterogeneity Characteristics at Moderate Resolution for Mixed Pixel Modeling and Inversion. Remote Sens. 2018, 10, 856.

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