Dynamic analysis of correlation patterns between urban population and construction land at different administrative levels: The case of Hangzhou megacity

Xiang, Shanshan; Huang, Lingyan; Zhou, Mengmeng; Shan, Liping; Dong, Baiyu; Wang, Ke

doi:10.1016/j.ecolind.2023.110407

Cited by 1 publication

(1 citation statement)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As the capital of the Zhejiang Province in China and the second largest metropolis in the Yangtze River Delta, Hangzhou City is located between 118 • 20 ′ 23 ′′ -120 • 42 ′ 50 ′′ E and 30 • 33 ′ 54 ′′ -29 • 11 ′ 19 ′′ N, in the lower reaches of the Qiantang River (Figure 1). The area includes 10 districts, two counties, and one county-level city, covering an area of 16,846.92 km 2 [33]. This region encompasses a vegetation zone named subtropical evergreen broad leaved forests and has a humid subtropical monsoon climate with four distinct seasons, including hot and humid summers and cold and dry winters [34,35].…”

Section: The Study Areamentioning

confidence: 99%

Annually Spatial Pattern Dynamics of Forest Types under a Rapid Expansion of Impervious Surfaces: A Case Study of Hangzhou City

Zhu,

Zhou,

Liu

et al. 2023

Forests

View full text Add to dashboard Cite

Dramatic forest dynamics strongly influence pressure mitigation from the increasing population and climate changes of an urban landscape. Effectively monitoring landscapes in a spatiotemporally consistent manner, satellite remote sensing has emerged as the first analytical tool to help us understand the changes in urban forests. At present, most studies focus on classification algorithms, spatial analysis methods, and ecosystem models, and the literature lacks spatiotemporally explicit research on the responses of different types of forests to urbanization. Thus, in this study, Hangzhou was selected as a typical metropolitan area to determine the annual spatial patterns of urban forests at a forest-type level. To illustrate the spatial pattern dynamics of different forest types resulting from rapid urbanization, this study characterized the Landsat-based spatial patterns of different forest types, as well as their annual changes from 2000 to 2022 using object-based backdating classification, land-use transfer matrix, area-weighted centroids, and landscape pattern indexes. The spatiotemporal effects of impervious surface expansion on forest pattern changes at a type scale were discussed. The results demonstrated that forests, mainly located in the southwest, decreased from 11,660.69 to 11,516.15 km2. Moreover, evergreen broadleaved forests occupied the largest area and had the most decreased ratio among the three forest types over 23 years, followed by evergreen needle-leaved and deciduous broadleaved forests. In total, 103.37 km2 of forest areas transformed to impervious surfaces, with the highest annual transformation of area occurring among evergreen broadleaved forests widely across Hangzhou City and the lowest occurring among deciduous broadleaved forests. Forests lost adjacency due to the development of Hangzhou City, while this southwestward shrinkage slowed down over 23 years, resulting in the highest increase in the degree of evergreen broadleaved forest fragmentation. Therefore, measures of city planning according to the deep effects of adjustments of administrative divisions to forest suitability should be implemented, such as green ecological corridor construction. This research provides a Landsat-based methodology at a spatiotemporally explicit-scale perspective for better understanding forest changes under high-speed urbanization.

show abstract

Section: The Study Areamentioning

confidence: 99%