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Analysis of Vegetation Growth Trends in Urban Areas Using Dense Landsat Time Series: A Case Study of Tianjin, China.

IEEE International Geoscience and Remote Sensing Symposium (IGARSS)(2022)

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Abstract
Vegetation growth changes in urban areas are important for understanding ecosystem responses to climate change. In this study, a method for vegetation growth trend extraction in urban areas based on piecewise linear regression and seasonality removal from Landsat time series data is proposed. A case study in Tianjin, China indicated that considering seasonality in vegetation growth trend analysis had impact on the absolute values and even the signs of trends. Compared to piecewise linear regression without seasonality removal, the proposed method extracted more pixels with significantly monotonic growth trends.
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Key words
vegetation growth trends,dense landsat time series,urban areas,time series
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