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Abrupt spatiotemporal land and water changes and their potential drivers in Poyang Lake, 2000-2012

 

Lifan Chen^a, Ryo Michishita^a, Bing Xu^{a, b, c}

 

a College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China

b Ministry of Education Key Laboratory for Earth System Modelling, Center for Earth System Science, and School of Environment, Tsinghua University, Beijing 100084, China

c Department of Geography, University of Utah, Salt Lake City, UT 84112, USA

 

ABSTRACT

Driven by various natural and anthropogenic factors, Poyang Lake, the largest freshwater lake in China, has experienced significant land use/cover changes in the past few decades. The aim of this study is to investigate the spatial-temporal patterns of abrupt changes and detect their potential drivers in Poyang Lake, using time-series Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day maximum value composite vegetation indices between 2000 and 2012. The breaks for additive seasonal and trend (BFAST) method was applied to the smoothed time-series normalized difference vegetation index (NDVI), to detect the timing and magnitude of abrupt changes in the trend component. Large part of Poyang Lake (98.9% for trend component) has experienced abrupt changes in the past 13 years, and the change patterns, including the distributions in timing and magnitudes of major abrupt trend changes between water bodies and land areas were clearly differentiated. Most water bodies had abrupt increasing NDVI changes between 2010 and 2011, caused by the sequential severe flooding and drought in the two years. In contrast, large parts of the surrounding land areas had abrupt decreasing NDVI changes. Large decreasing changes occurred around 2003 at the city of Nanchang, which were driven by urbanization. These results revealed spatial-temporal land cover changing patterns and potential drivers in the wetland ecosystem of Poyang Lake. (C) 2014 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

 

KEYWORDS: MODIS, Time-series analysis, Vegetation index, Signal decomposition, Trend breaks, Driving forces

 

PUBLISHED BY: ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2014, 98: 85-93

 

SOURCE: http://www.sciencedirect.com/science/article/pii/S0924271614002391