Assessing Potential Bioenergy Production on Urban Marginal Land in 20 Major Cities of China by the Use of Multi-View High-Resolution Remote Sensing Data

Abstract

For the purpose of bioenergy production, biomass cropping on marginal land is an appropriate method. Less consideration has been given to estimating the marginal land in cities at a fine spatial resolution, especially in China. Marginal land within cities has great potential for bioenergy production. Therefore, in this research, the urban marginal land of 20 representative cities of China was estimated by using detailed land-cover and 3D building morphology information derived from Ziyuan-3 high-resolution remote sensing imagery, and ancillary geographical data, including land use, soil type, and digital elevation model data. We then classified the urban marginal land into “vacant land” and “land between buildings”, and further revealed its landscape patterns. Our results showed that: (1) the suitable marginal land area ranged from 17.78 ± 1.66 km2 to 353.48 ± 54.19 km2 among the 20 cities; (2) it was estimated that bioethanol production on marginal land could amount to 0.005–0.13 mT, corresponding to bioenergy of 2.1 × 1013–4.0 × 1014 J for one city; (3) from the landscape viewpoint, the marginal landscape pattern tended to be more fragmented in more developed cities. Our results will help urban planners to reclaim unused urban land and develop distributed bioenergy projects at the city scale.

Sustainable development of million cities: Spatial evidence from Russia

“…− The classification of the urban marginal land into "vacant land" and "land between buildings" can support the disclosure of landscape patterns, thus, support urban planners to reclaim unused urban land and develop distributed bioenergy projects at a city scale [36,37].…”

Identification of fragmented cropland in arid and semiarid sandy areas: a case study of horqin left rear banner

“…Fang et al adopted satellite images with a 30 m resolution to identify marginal land by selecting indicators such as land use type and land cover type and considering environmental impact (Wang and Shi, 2015). Alternatively, Ben et al used ZY-3 3D land-cover products and the Chinese soil database to exclude land unsuitable for cultivation, conduct screening based on relevant indicators of land quality and crop environment, and finally identify urban marginal land (Zhang et al, 2021). This approach reduces the limitations of the second method, with which results with relatively low accuracy are produced.…”