Analyzing the spatiotemporal pattern and driving factors of wetland vegetation changes using 2000-2019 time-series Landsat data.

Abstract

Probing the long-term spatiotemporal patterns of wetland vegetation changes and their response to climate change and human activities is critical to make informed decisions regarding ecosystem protection. Here, the spatiotemporal patterns and factors that drive vegetation changes in the Dongting Lake wetland from 2000 to 2019 were analyzed using monthly normalized difference vegetation index (NDVI) data at a 30m spatial resolution. First, abrupt vegetation changes were identified using the breaks for additive season and trend approach. Moreover, the relative impacts of climatic factors on monthly vegetation changes were quantified using a partial correlation-based approach, and the effects of three specific climatic factors (temperature, precipitation, and solar radiation) and human factors on vegetation recovery and degradation were determined. Our study found that: 1) the study area is becoming greener, with NDVI increases of 0.006 per year; however, there was a pronounced interannual variation in the vegetation types; 2) more than 50% of the vegetation pixels exhibited at least two breakpoints, with ~5% of the vegetation pixels exhibiting eight breakpoints; 3) in the past 20years, human activities have favored wetland vegetation recovery (58.85%), whereas climate change threatens wetland vegetation (59.19%). Regarding climate factors, the influence of solar radiation on vegetation was found to be stronger than that of temperature and precipitation.