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Dynamic monitoring of wetland cover changes using time-series remote sensing imagery

 

Lifan Chen^a, Zhenyu Jin^a, Ryo Michishita^a, Jun Cai^b, Tianxiang Yue^c, Bin Chen^d, Bing Xu^{a, e, f}

 

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

b Center for Earth System Science, Tsinghua University, Beijing, 100084, China

c Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

d School of Environment, Beijing Normal University, Beijing 100875,China

e Department of Geography, University of Utah, 260 S. Central Campus Dr., Salt Lake City, UT 84112, USA

f College of Environment, Tsinghua University, Beijing, 100084, China

 

ABSTRACT

Time-series remote sensing data, such as Moderate Resolution Imaging Spectroradiometer (MODIS) data hold considerable promise for investigating long-term dynamics of land use/cover change (LUCC), given their significant advantages of frequent temporal coverage and free cost. However, because of the complex ecological environment of wetlands, the applicability of these data for studying temporal dynamics of wetland-related land-cover types is limited. This is especially so for the Poyang Lake, China's largest freshwater lake, which has active seasonal and inter-annual dynamics. The primary objective of this study is to investigate the suitability of MODIS 250-m maximum value composite (MVC) vegetation indexes (VIs) for dynamics monitoring of the Poyang Lake. We applied a time-series 16-day MODIS NDVI from 2000 to 2012 and developed a method to classify wetland cover types based on timing of inundation. We combined techniques of applying iterative self-organizing data analysis (ISODATA) with varying numbers of clusters and a transformed divergence (TD) statistic, to implement annual classification of smoothed time-series NDVI. In addition, we propose a decision tree based on features derived from NDVI profiles, to characterize phenological differences among clusters. Supported by randomly generated validation samples from TM images and daily water level records, we obtained a satisfactory accuracy assessment report. Classification results showed various change patterns for four dominant land cover types. Water area showed a non-significant declining trend with average annual change rate 33.25 km2, indicating a drier Poyang lake, and emergent vegetation area had weak change over the past 13 years. Areas of submerged vegetation and mudflat expanded, with significant average annual change rate 23.51 km2 for the former. The results suggest that MODIS' 250-m spatial resolution is appropriate and the classification method based on timing of inundation is useful for mapping general land cover patterns of Poyang Lake.

 

PUBLISHED BY: ECOLOGICAL INFORMATICS, 2014, 24: 17-26

 

Key WORDS: ICE-SHEET MODEL; SIZE DISTRIBUTIONS; ICEBERGS

 

SOURCE: http://www.sciencedirect.com/science/article/pii/S157495411400079X