Land use mapping for the forest-steppe ecotone in the Greater Khingan Mountains, 2019 to 2021

Generating accurate thematic land use maps is importance in ecologically vulnerable regions, especially considering the challenges associated with extracting the forest-steppe ecotone and its associated uncertainties and high error rates. By employing the Principal Component Analysis (PCA) method to integrate Sentinel-1 and Sentinel-2 imagery, high-resolution (10 meters) land use cover products were generated for the forest-steppe ecotone of the Greater Khingan Mountains from 2019 to 2021. The classification process utilized prior knowledge and an object-oriented classification-based approach. The main objective was to evaluate the accuracy improvement achieved through the integration of multi-source remote sensing data, while highlighting the advantages of the object-based classification method and comparing it with existing products. The results demonstrated a significant enhancement in classification accuracy, surpassing the accuracy obtained from individual Sentinel-1 or Sentinel-2 images. Furthermore, the object-oriented analysis approach yielded classification results that more accurately represented real-world land cover conditions while reducing salt-and-pepper noise. The research also showcased superior accuracy in delineating complex riverine wetlands, outperforming other existing land use/land cover (LULC) datasets. The generated 10m land use products provide valuable information for supporting sustainable development, effective management, and ecological assessment and conservation efforts in the Greater Khingan Mountains.

在生态脆弱区域生成精确的主题土地利用地图具有重要意义，特别是在考虑提取森林草原过渡带及其相关的不确定性和高误差率所面临的挑战。通过运用主成分分析（PCA）方法整合Sentinel-1和Sentinel-2影像，生成了2019年至2021年大兴安岭森林草原过渡带的高分辨率（10米）土地利用覆盖产品。分类过程结合了先验知识和面向对象分类方法。主要目标是评估通过整合多源遥感数据所实现的精度提升，并突出面向对象分类方法的优点，并将其与现有产品进行比较。结果表明，分类精度显著提高，超越了仅使用单个Sentinel-1或Sentinel-2影像所获得的精度。此外，面向对象的分析方法产生了更准确地反映现实世界土地覆盖条件的分类结果，同时降低了椒盐噪声。该研究还展示了在复杂河川湿地边界描绘方面的卓越精度，超越了其他现有的土地利用/土地覆盖（LULC）数据集。生成的10米土地利用产品为支持大兴安岭的可持续发展、有效管理和生态评估与保护工作提供了宝贵信息。