Mapping land-use and land-cover changes through the integration of satellite and airborne remote sensing data.

Lin, Meng-Hsuan; Lin, Ying-Tong; Tsai, Min-Lin; Chen, Yi-Ying; Chen, Yi-Chun; Wang, Hsueh-Ching; Wang, Chi-Kuei

Abstract

An integrated, remotely sensed approach to assess land-use and land-cover change (LULCC) dynamics plays an important role in environmental monitoring, management, and policy development. In this study, we utilized the advantage of land-cover seasonality, canopy height, and spectral characteristics to develop a phenology-based classification model (PCM) for mapping the annual LULCC in our study areas. Monthly analysis of normalized difference vegetation index (NDVI) and near-infrared (NIR) values derived from SPOT images enabled the detection of temporal characteristics of each land type, serving as crucial indices for land type classification. The integration of normalized difference built-up index (NDBI) derived from Landsat images and airborne LiDAR canopy height into the PCM resulted in an overall performance of 0.85, slightly surpassing that of random forest analysis or principal component analysis. The development of PCM can reduce the time and effort required for manual classification and capture annual LULCC changes among five major land types: forests, built-up land, inland water, agriculture land, and grassland/shrubs. The gross change LULCC analysis for the Taoyuan Tableland demonstrated fluctuations in land types over the study period (2013 to 2022). A negative correlation (r =  - 0.79) in area changes between grassland/shrubs and agricultural land and a positive correlation (r = 0.47) between irrigation ponds and agricultural land were found. Event-based LULCC analysis for Taipei City demonstrated a balance between urbanization and urban greening, with the number of urbanization events becoming comparable to urban greening events when the spatial extent of LULCC events exceeds 1000 m . Besides, small-scale urban greening events are frequently discovered and distributed throughout the metropolitan area of Taipei City, emphasizing the localized nature of urban greening events. [Abstract copyright: © 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.]

Citation

Lin, M., Lin, Y., Tsai, M., Chen, Y., Chen, Y., Wang, H., & Wang, C. (2024). Mapping land-use and land-cover changes through the integration of satellite and airborne remote sensing data. Environmental Monitoring and Assessment, 196(3), Article 246. https://doi.org/10.1007/s10661-024-12424-5

• Journal Article Type: Article
• Acceptance Date: Feb 2, 2024
• Online Publication Date: Feb 8, 2024
• Publication Date: Feb 8, 2024
• Deposit Date: Apr 9, 2024
• Journal: Environmental Monitoring and Assessment
• Print ISSN: 0167-6369
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 196
• Issue: 3
• Article Number: 246
• DOI: https://doi.org/10.1007/s10661-024-12424-5
• Keywords: Remote Sensing Technology, Land-cover/land-use change, Airborne lidar canopy height, Policy Making, Phenology, SPOT images, Landsat images, Ponds, Agriculture, Environmental Monitoring
• Public URL: https://durham-repository.worktribe.com/output/2275919