Detections of Long-term Land Cover Dynamics from AVHRR and MODIS Greenness

Authors: Xiaoyang Zhang*,
Topics: Land Use and Land Cover Change, Global Change
Keywords: land cover and land use change , remote sensing, climate change
Session Type: Paper
Day: 4/13/2018
Start / End Time: 1:20 PM / 3:00 PM
Room: Estherwood, Sheraton, 4th Floor
Presentation File: No File Uploaded

Land surface properties have experienced significant changes during past few decades because of the global climate change and human activities. To detect the long-term land cover dynamics globally, this study investigated interannual greenness variation using AVHRR long term data record (version 5) and MODIS (collection 6) data from 1982 to 2016 and its relationship with land cover change. Based on daily two band enhanced vegetation index (EVI2) at a spatial resolution of 0.05 degrees (~5km), we reconstructed daily vegetative trajectory for each pixel using hybrid piecewise logistic models, from which the EVI2 amplitude and EVI2 integration during vegetation growing seasons were quantified. Further, long-term EVI2 greenness was decomposed to trend and oscillatory components using the Singular Spectrum Analysis (SSA) method. The first SSA component (trend) was then utilized to extract long-term breakpoints by conducting analyses of Breaks for Additive Seasonal and Trend (BFAST). By combining long-term breakpoints and oscillations of EVI2 greenness, the hotspots of potential land cover change were identified. Furthermore, these hotspots were associated with the interannual land cover changes from global 500m MODIS land cover land cover product (MCD12Q1) for 2001–2016 and National Land Cover Database (NLCD) maps from the Multi-Resolution Land Characteristics (MRLC) consortium in 1992, 2001, 2006, 2011, and 2016 across the United States. Finally, the relationships between hotspots of EVI2 greenness variations and land cover changes were explored.

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