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Correction published on 18 April 2019, see Remote Sens. 2019, 11(8), 939.

Open AccessArticle

Determining the Start of the Growing Season from MODIS Data in the Indian Monsoon Region: Identifying Available Data in the Rainy Season and Modeling the Varied Vegetation Growth Trajectories

1
State key Laboratory of Resources and Environmental Information system, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
4
Geography and Environment, University of Southampton, Southampton SO17 1BJ, UK
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(1), 122; https://doi.org/10.3390/rs10010122
Received: 10 November 2017 / Revised: 9 January 2018 / Accepted: 15 January 2018 / Published: 18 January 2018
(This article belongs to the Special Issue Land Surface Phenology)
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Abstract

In the Indian monsoon region, frequent cloud cover in the rainy season results in less valid satellite observations during the vegetation growth period, making it difficult to extract land surface phenology (LSP). Even worse, many valid but humid observations were misidentified as clouds in the MODIS cloud mask, causing severe gaps in the LSP product. Using a refined cloud detection approach to separate clear-sky and cloudy observations, this study found that potentially valid observations during the vegetation growth period could be identified. Furthermore, the varied vegetation growth trajectories cannot be well-fitted by a global curve-fitting approach, but can be modelled by using the locally adjusted cubic-spline capping approach, which performed well for any seasonal patterns. Applying this approach, the start of growing season (SOS) was determined with 9.18% of vegetation growth amplitude between the maximum and minimum NDVI to generate the SOS product (2000–2016). The valid percentage of this regional product largely increased from 29.30% to 69.76% compared with the MCD12Q2 product, and its reliability was approximate to that of deciduous broadleaf forest in North America and Europe. This product could serve as a basis for understanding the response of terrestrial ecosystems to the changing Indian monsoon. View Full-Text
Keywords: land surface phenology; vegetation growth trajectory; start of growing season; Indian monsoon; climate change; MODIS land surface phenology; vegetation growth trajectory; start of growing season; Indian monsoon; climate change; MODIS
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Shang, R.; Liu, R.; Xu, M.; Liu, Y.; Dash, J.; Ge, Q. Determining the Start of the Growing Season from MODIS Data in the Indian Monsoon Region: Identifying Available Data in the Rainy Season and Modeling the Varied Vegetation Growth Trajectories. Remote Sens. 2018, 10, 122.

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