Classification of Hainan island natural forest based on multi-source remote sensing data

Therefore, it is of great significance for a country to develop the forest resources inventory and perform dynamic monitoring. Research on the classification of natural forests not only supports the investigation of tropical forests, but also provides the basis for the study of forest species diversity.

The dual-polarized SAR data from Sentinel-1A sensor and the optical remote sensing data from Landsat-8 sensor were used for classification of Hainan island tropical natural forest. First, we analyzed the single-band, multi-band, normalized difference vegetation index (NDVI) characteristics of optical data, and the single-phase, multi-temporal backscattering characteristics of SAR data. Then, optical and backscattering characteristics were selected for natural forest classification whereby the natural forest range of Hainan Island was extracted by using support vector machine (SVM).