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

Widely distributed in the vicinity of the equator, tropical forest is one type of forest with the most abundant species worldwide which has a profound effect on global climate change. 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). The natural tropical forest was classified into five types: tropical rain forest, tropical monsoon forest, evergreen coniferous forest, deciduous broad-leaved mixed forest and coastal forest. The accuracy of classification results was verified and evaluated based on a combination of field survey data and Hainan forestry survey data. The overall accuracy of the classification exceeded 80%. The results provide a reliable remote sensing classification method for Hainan island tropical forest classification. This dataset also has some reference value for the study of tropical natural forest classification in other areas.

广泛分布于赤道附近的热带森林，是全球物种最为丰富的森林类型之一，对全球气候变化具有深远的影响。因此，对于一国而言，开发森林资源清单并执行动态监测具有极其重要的意义。对天然森林进行分类的研究不仅支持热带森林的调查，亦为森林物种多样性的研究奠定了基础。本研究利用Sentinel-1A传感器的双极化合成孔径雷达（SAR）数据和Landsat-8传感器的光学遥感数据对海南岛热带天然森林进行分类。首先，我们对光学数据的单波段、多波段以及归一化植被指数（NDVI）特征，以及SAR数据单相位、多时相的后向散射特征进行了分析。随后，选取光学和后向散射特征进行天然森林分类，通过支持向量机（SVM）提取了海南岛的天然森林范围。天然热带森林被划分为五种类型：热带雨林、热带季雨林、常绿针叶林、落叶阔叶混交林和沿海森林。分类结果的准确性基于实地调查数据和海南林业调查数据的结合进行验证和评估。分类的整体精度超过80%。这些结果为海南岛热带森林分类提供了可靠的遥感分类方法。此外，该数据集对其他地区热带天然森林分类的研究亦具有一定的参考价值。