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

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 m2. 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.

A landscape ecology assessment of land-use change on the Great Plains-Denver (CO, USA) metropolitan edge

For better or worse, in those parts of the world with a widespread farming, livestock rising, and urban expansion, the maintenance of species richness and ecosystem services cannot depend only upon protected natural sites. Can they rely on a network of cultural landscapes endowed with their own associated biodiversity? We analyze the effects of land-cover change on landscape ecological patterns and processes that sustain bird species richness associated to cropland-grassland landscapes in the Great Plains-Denver metropolitan edge. Our purpose is to assess the potential contribution to bird biodiversity maintenance of Great Plain's cropland-grassland mosaics kept as farmland green belts in the edge of metropolitan areas. We present a quantitative landscape ecology assessment of land-cover changes (1930-2010) experienced in five Great Plains counties in Colorado. Several landscape metrics assess the diversity of land-cover patterns and their impact on ecological connectivity indices. These metrics are applied to historical land-cover maps and datasets drawn from aerial photos and satellite imagery. The results show that the cropland-grassland mosaics that link the metropolitan edge with the surrounding habitats sheltered in less human-disturbed areas provide a heterogeneous land matrix were a high bird species richness exists. They also suggest that keeping multifunctional farmland-grassland green belts near the edge of metropolitan areas may provide important ecosystem services, supplementing traditional conservation policies. Our maps and indicators can be used for selecting certain types of landscape patterns and priority areas on which biodiversity conservation efforts and land-use planning can concentrate.