Spatial and Temporal Changes in Vegetation in the Ruoergai Region, China

Timely monitoring of the changes in coverage and growth conditions vegetation (forest, grass) is very important for preserving regional global ecological environment. Vegetation information mainly reflected by its spectral characteristics, namely, differences green plant leaves canopies remote sensing domains. The normalized difference index (NDVI) commonly used to describe dynamic vegetation, but NDVI sequence not long enough support exploration due many reasons, such as sensors. Thus, from different sensors should be scientifically combined using logical methods. In this study, Global Inventory Modeling Mapping Studies (GIMMS) Advanced Very High Resolution Radiometer (AVHRR) Moderate-resolution Imaging Spectroradiometer (MODIS) are Savitzky–Golay (SG) method then utilized investigate temporal spatial Ruoergai wetland area (RWA). trends RWA analyzed evaluate monitor region. regard annual changes, average shows an overall increasing trend region during past three decades, with a linear coefficient 0.013/10a, indicating that has been continuously improving. seasonal coefficients 0.020, 0.021, 0.004, 0.004/10a spring, summer, autumn, winter, respectively. regression between gross domestic product (GDP) also calculated, 0.0024, 0.0015, 0.0020, determination (R2) 0.453, 0.463, 0.444 Aba, Ruoergai, Hongyuan, positive correlation GDP may indicate increased societal development promotes some respects resulting planting more trees or promotion tree protection activities. Through analysis NDVI, it can assessed relatively large condition good overall.