Remote Sensing Mapping and Analysis of Spatiotemporal Patterns of Land Use and Cover Change in the Helong Region of the Loess Plateau Region (1986–2020)

• Published in: Remote sensing (Basel, Switzerland) Vol. 16; no. 19; p. 3738
• Main Authors: Li, Jingyu, Chen, Yangbo, Gu, Yu, Wang, Meiying, Zhao, Yanjun
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.10.2024
• Subjects: Agricultural land; Algorithms; Artificial intelligence; Classification; Distribution; Economic development; Environmental aspects; Environmental restoration; Feasibility studies; Geographical distribution; Geographical locations; Google Earth Engine; Grasslands; Identification and classification; Land cover; land cover mapping; Land management; Land use; Land use classification; Land use planning; Landsat satellites; Machine learning; Mapping; random forest; Regions; Remote sensing; Soil erosion; Soil water; Spatial discrimination; Spatial resolution; spatiotemporal analysis of land use and cover data; Sustainable ecosystems; Terraces; Water erosion; China; Loess Plateau; Yellow River
• DOI: 10.3390/rs16193738
• ISSN: 2072-4292

Land use and cover change (LUCC) is directly linked to the sustainability of ecosystems and the long-term well-being of human society. The Helong Region in the Loess Plateau has become one of the areas most severely affected by soil and water erosion in China due to its unique geographical location and ecological environment. The long-term construction of terraces and orchards is one of the important measures for this region to combat soil erosion. Despite the important role that terraces and orchards play in this region, current studies on their extraction and understanding remain limited. For this reason, this study designed a land use classification system, including terraces and orchards, to reveal the patterns of LUCC and the effectiveness of ecological restoration projects in the area. Based on this system, this study utilized the Random Forest classification algorithm to create an annual land use and cover (LUC) dataset for the Helong Region that covers eight periods from 1986 to 2020, with a spatial resolution of 30 m. The validation results showed that the maps achieved an average overall accuracy of 87.54% and an average Kappa coefficient of 76.94%. This demonstrates the feasibility of the proposed design and land coverage mapping method in the study area. This study found that, from 1986 to 2020, there was a continuous increase in forest and grassland areas, a significant reduction in cropland and bare land areas, and a notable rise in impervious surface areas. We emphasized that the continuous growth of terraces and orchards was an important LUCC trend in the region. This growth was primarily attributed to the conversion of grasslands, croplands, and forests. This transformation not only reduced soil erosion but also enhanced economic efficiency. The products and insights provided in this study help us better understand the complexities of ecological recovery and land management.