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Article

How Does Scale Effect Influence Spring Vegetation Phenology Estimated from Satellite-Derived Vegetation Indexes?

1
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
2
School of Resources and Environment, University of Electronic Science and Technology of China, 2006 Xiyuan Avenue, West Hi-tech Zone, Chengdu 611731, China
3
Key Laboratory of Alpine Ecology, Institute of Tibetan Plateau Research, CAS Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, 16 Lincui Road, Beijing 100101, China
4
Geospatial Sciences Center of Excellence, Department of Geography and Geospatial Sciences, South Dakota State University, Brookings, SD 57007, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(18), 2137; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11182137
Received: 7 August 2019 / Revised: 8 September 2019 / Accepted: 10 September 2019 / Published: 13 September 2019
(This article belongs to the Special Issue Remote Sensing of Vegetation Phenology)
As an important land-surface parameter, vegetation phenology has been estimated from observations by various satellite-borne sensors with substantially different spatial resolutions, ranging from tens of meters to several kilometers. The inconsistency of satellite-derived phenological metrics (e.g., green-up date, GUD, also known as the land-surface spring phenology) among different spatial resolutions, which is referred to as the “scale effect” on GUD, has been recognized in previous studies, but it still needs further efforts to explore the cause of the scale effect on GUD and to quantify the scale effect mechanistically. To address these issues, we performed mathematical analyses and designed up-scaling experiments. We found that the scale effect on GUD is not only related to the heterogeneity of GUD among fine pixels within a coarse pixel, but it is also greatly affected by the covariation between the GUD and vegetation growth speed of fine pixels. GUD of a coarse pixel tends to be closer to that of fine pixels with earlier green-up and higher vegetation growth speed. Therefore, GUD of the coarse pixel is earlier than the average of GUD of fine pixels, if the growth speed is a constant. However, GUD of the coarse pixel could be later than the average from fine pixels, depending on the proportion of fine pixels with later GUD and higher growth speed. Based on those mechanisms, we proposed a model that accounted for the effects of heterogeneity of GUD and its co-variation with growth speed, which explained about 60% of the scale effect, suggesting that the model can help convert GUD estimated at different spatial scales. Our study provides new mechanistic explanations of the scale effect on GUD. View Full-Text
Keywords: land surface phenology; scale effect; spatial heterogeneity; spring phenology; spatial resolution; vegetation index; vegetation growth speed land surface phenology; scale effect; spatial heterogeneity; spring phenology; spatial resolution; vegetation index; vegetation growth speed
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MDPI and ACS Style

Liu, L.; Cao, R.; Shen, M.; Chen, J.; Wang, J.; Zhang, X. How Does Scale Effect Influence Spring Vegetation Phenology Estimated from Satellite-Derived Vegetation Indexes? Remote Sens. 2019, 11, 2137. https://0-doi-org.brum.beds.ac.uk/10.3390/rs11182137

AMA Style

Liu L, Cao R, Shen M, Chen J, Wang J, Zhang X. How Does Scale Effect Influence Spring Vegetation Phenology Estimated from Satellite-Derived Vegetation Indexes? Remote Sensing. 2019; 11(18):2137. https://0-doi-org.brum.beds.ac.uk/10.3390/rs11182137

Chicago/Turabian Style

Liu, Licong, Ruyin Cao, Miaogen Shen, Jin Chen, Jianmin Wang, and Xiaoyang Zhang. 2019. "How Does Scale Effect Influence Spring Vegetation Phenology Estimated from Satellite-Derived Vegetation Indexes?" Remote Sensing 11, no. 18: 2137. https://0-doi-org.brum.beds.ac.uk/10.3390/rs11182137

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