Vegetation Change Detection Based on Fractal and Spectral Slope Characteristics of Time Series Vegetation Indice

Based on the 15 periods of Landsat8 operational land image (OLI) time series images of three vegetation indices, the one-dimensional fractal value and slope parameters were calculated to explore the change of vegetation index and vegetation area. Three vegetation indices including green vegetation index (GVI), normalized difference vegetation index (NDVI) and optimized soil adjusted vegetation index (OSAVI) were calculated. The 15 periods of vegetation index images are superimposed in time sequence to generate multi-band images. Based on the difference in Jeffries- Matusita (JM) distance, the vegetation indices were divided into four classes. The fractal values of these four classes were calculated, indicating that the fractal values of the three vegetation indices were identically arranged, while the results were consistent with the actual conditions of ground objects. The slope of one-dimensional time series curves of the four categories of vegetation indices were calculated, indicating that the increase and decrease of the three vegetation indices in the four categories are identical. According to the number of occurrences of the slope of the vegetation index, the first three periods with large changes in vegetation index are determined, and the changes after the classification were completed for these three periods. It was found that in the three periods, the order of increase and decrease of vegetation area coincided with the slope of the number of occurrences, and the main land types causing increase and decrease of vegetation area are agricultural land, land under construction and impermeable surface.