Developing a web-based system to visualize vegetation trends by a nonlinear regression algorithm
Comparing with traditional linear regression methods that used to monitor vegetation trends, a nonlinear regression algorithm (PolyTrend) developed by Jamali et al. (2014) can provide more accurate information of vegetation trends by fitting a polynomial line with a degree of up to three for ASCII-formed time-series NDVI (Normalized Difference Vegetation Index) dataset of a single pixel. To extend
