Notes on academic studies

A Satellite View of the Wetland Transformation Path and Associated Drivers in the Greater Bay Area of China during the Past Four Decades

Kun Sun, Weiwei Yu

Remote Sens (2024)

As a highly productive and biologically diverse ecosystem, wetlands provide unique habitat for a wide array of plant and animal species. Owing to the strong disturbance by human activities and climate change, wetland degradation and fragmentation have become a common phenomenon across the globe. The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is a typical case. The GBA has experienced explosive growth in the population and economy since the early 1980s, which has resulted in complicated transitions between wetlands and non-wetlands. However, our knowledge about the transformation paths, associated drivers, and ecological influence of the GBA’s wetlands is still very limited. Taking advantage of the land use maps generated from Landsat observations over the period of 1980–2020, here, we quantified the spatiotemporal transformation paths of the GBA’s wetlands and analyzed the associated drivers and ecological influence. We found that the dominant transformation path between wetland and non-wetland was from wetland to built-up land, which accounted for 98.4% of total wetland loss. The primary transformation path among different wetland types was from coastal shallow water and paddy land to reservoir/pond, with the strongest transformation intensity in the 1980s. The driving forces behind the wetland change were found to vary by region. Anthropogenic factors (i.e., population growth and urbanization) dominated in highly developed cities, while climate factors and aquaculture had a greater influence in underdeveloped cities. The findings presented in this study will provide a reference for wetland management and planning in the GBA. From the Abstract

Multimodal transportation and city carbon emissions over space and time: Evidence from Guangdong-Hong Kong-Macao Greater Bay Area, China

Luqi Wang, Zhenqiang Wu, Xiaoxia Wang

Journal of Cleaner Production (November 2023)

The effectiveness of climate policies will determine CO2 emissions and goal achievement. However, the coupled integration among driving factors on emissions is not given enough attention and analysis in most quantitative modeling. To clarify the effectiveness of de-carbonization pathways, here we identify coupled factors documented across a range of studies and connect them in a coupled system framework. The empirical analysis reveals the de-carbonization significance and potential of coupled variables in the GBA. These potentials can be decisive for determining policies and emission outcomes. After in-depth spatial and time-fixed analysis, spatial spillover effects of driving factors are identified. And the driving effect of the independent variable is further decomposed into direct effect and indirect effect to show a complex coupled correlation. The novelty of this study is that it explores the coupled correlation among driving factors and quantitatively verified these relationships. Research findings have important reference value for policymakers in assisting de-carbonization strategies design. From the Abstract