Abstract
A lot of timeseries satellite products have been well documented in exploring changes in ecosystems. However, algorithms allowing for measuring the directions, magnitudes, and timing of vegetation change, evaluating the major driving factors, and eventually predicting the future trends are still insufficient. A novel framework focusing on addressing this problem was proposed in this study according to the temporal trajectory of Normalized Difference Vegetation Index (NDVI) timeseries of Moderate Resolution Imaging Spectroradiometer (MODIS). It divided the inter-annual changes in vegetation into four patterns: linear, exponential, logarithmic, and logistic. All the three non-linear patterns were differentiated automatically by fitting a logistic function with prolonged NDVI timeseries. Finally, features of vegetation changes including where, when and how, were evaluated by the parameters in the logistic function. Our results showed that 87.39% of vegetation covered areas (maximum mean growing season NDVI in the 17 years not less than 0.2) in the Shiyng River basin experienced significant changes during 2001–2017. The linear pattern, exponential pattern, logarithmic pattern, and logistic pattern accounted for 36.53%, 20.16%, 15.42%, and 15.27%, respectively. Increasing trends were dominant in all the patterns. The spatial distribution in both the patterns and the transition years at which vegetation gains/losses began or ended is of high consistency. The main years of transition for the exponential increasing pattern, the logarithmic increasing pattern, and the logarithmic increasing pattern were 2008–2011, 2003–2004, and 2009–2010, respectively. The period of 2006–2008 was the foremost period that NDVIs started to decline in Liangzhou Oasis and Minqin Oasis where almost all the decreasing patterns were concentrated. Potential disturbances of vegetation gradual changes in the basin are refer to as urbanization, expansion or reduction of agricultural oases, as well as measures in ecological projects, such as greenhouses building, afforestation, grazing prohibition, etc.
Highlights
Satellite remote sensing has long been a technique of repeated temporal sampling on the earth’s surface
Linear patterns made up 20.16% of the entire vegetation covered areas, of which 18.43% were increasing while 1.73% were decreasing
Our study further indicated that human activities, especially various ecological restoration projects could explain a large part of gradual changes in the Shiyang River Basin because there is a good agreement between the detected patterns of vegetation changes and human-induced landscape transformations or modifications
Summary
Satellite remote sensing has long been a technique of repeated temporal sampling on the earth’s surface. The disturbance events in timeseries could be accurately localized in time. They are receiving increasing attention for monitoring vegetation dynamics at global or regional scale. Changes in ecological systems were divided into two types: gradual change and abrupt change [3], which refer to the trend component in timeseries beyond seasonal variations [4]. Processes of gradual changes are never linear with time in a smooth way and even may be interrupted by sudden drastic trend breaks and stall or reverse completely [9]. Exploring and extracting essential information characterizing vegetation gradual changes based on long-term remote sensing timeseries remains a large challenge
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