An improved framework for assessing the impact of different urban development strategies on land cover and ecological quality changes -A case study from Nanjing Jiangbei New Area, China. (March 2023)

• Record Type: Journal Article
• Authors: Shi, Fang; Yang, Boxiang; Li, Mingshi
• Is Part Of: Ecological indicators. Volume 147(2023)
• Publication Date: 2023-03
• Subjects: Land cover classification -- Ecological environment quality -- Modified mask-RCNN -- RO-RSEI -- New-type urbanization; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2023.109998
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: The Modified Mask-RCNN model improved the land cover mapping accuracy. The RO-RSEI outperformed RSEI in ecological quality evaluation. Land cover conversion was the most important reason for ecological quality change. The "new-type urbanization" philosophy valued more ecology than economy. Abstract: Land cover (LC) change has been highly valued by policy makers for driving the evolution of regional ecological and environmental quality. The core area of Nanjing Jiangbei New Area (NJNA) has undergone the development process from traditional urbanization to new-type urbanization (NTU), however the impacts of different urban development strategies or pathways on the change pace and direction of land cover and ecological quality are not adequately understood in a quantitative manner which is not conducive for similar regions to learn lessons from past development processes. Based on RapidEye, GF-1 and SPOT-6 images acquired in 2009, 2015 and 2021, a Modified Mask-RCNN framework was devised and implemented to create a high accuracy LC dataset first in this analysis. Then, the applicability or efficacy of the Remote Sensing Ecological Index (RSEI) model and the Regional Optimized Remote Sensing Ecological Index (RO-RSEI) model, developed from the Landsat observations was compared in characterizing the ecological quality. Finally, the attribution analysis of spatio-temporal changes in LC and their induced ecological quality evolutions was carried out in conjunction with socio-economic factors. The results showed that the overall accuracies of the LC classifications were estimated at 91.50 % (2009), 91.25 % (2015), and 92.75 % (2021), respectively. The mean values of RO-RSEI analyses were at 0.652, 0.649, and 0.656, respectively, indicating that in the past 12 years, the ecological quality first got degraded then got ameliorated along with the urbanization. The urban green spaces got restored and increased in the NTU process, and protecting the forest and cropland was also reinforced thanks to the strict enforcement of related policies. These positive changes are attributed to the popularization of ecological civilization philosophy and the escalation of social awareness of environmental protection and low carbon development. The proposed framework can provide technical reference for ecological quality monitoring under the progress of NTU.