Zhibin Ren1, Haifeng Zheng2, Xingyuan He3, Dan Zhang4, Guoqiang Shen1, Chang Zhai1. 1. Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, 4888 Shengbei Road, Changchun, Jilin Province, 130102, China. 2. Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, 4888 Shengbei Road, Changchun, Jilin Province, 130102, China. Electronic address: zhenghaifeng@iga.ac.cn. 3. Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, 4888 Shengbei Road, Changchun, Jilin Province, 130102, China. Electronic address: hexingyuan@iga.ac.cn. 4. Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, 4888 Shengbei Road, Changchun, Jilin Province, 130102, China; Horticultural College, Changchun University, 6543 Weixing Road, Changchun, Jilin Province, 130022, China.
Abstract
BACKGROUND: Understanding spatio-temporal dynamics of UF and its above-ground carbon storage (CS) is important for mitigating urban CO2 emissions under China's rapid urban expansion and greening. METHODS: In our study, vegetation index (VI) data obtained from TM image and CS derived from field-based surveys were amalgamated to develop a regression model to predict spatio-temporal patterns of CS. VI correction model was established by normalizing previous imagery (1984, 1995, and 2005) to 2014 image data. RESULTS: NDVI is better than other VIs for predicting urban forest CS. Both UF area and its CS increased gradually from 1984 to 2014, especially in outer rings of the city. CS showed a definite decreasing trend from outer rings to downtown. Due to urban greening policies, landscape patches of UF or CS recently became larger and more aggregated. The CS by UF class distribution was skewed toward low values in all the years, but the skew gradually decreased over time. It was estimated that the average annual increase of CS by UF could offset 3.9% of the average annual increase in urban carbon emissions. CONCLUSIONS: Our study proposes that spatio-temporal changes in UF patterns dramatically affected the amount of CS and carbon capture. The increase in UF coverage and quality would mitigate more urban carbon emissions, especially in outer rings.
BACKGROUND: Understanding spatio-temporal dynamics of UF and its above-ground carbon storage (CS) is important for mitigating urban CO2 emissions under China's rapid urban expansion and greening. METHODS: In our study, vegetation index (VI) data obtained from TM image and CS derived from field-based surveys were amalgamated to develop a regression model to predict spatio-temporal patterns of CS. VI correction model was established by normalizing previous imagery (1984, 1995, and 2005) to 2014 image data. RESULTS: NDVI is better than other VIs for predicting urban forest CS. Both UF area and its CS increased gradually from 1984 to 2014, especially in outer rings of the city. CS showed a definite decreasing trend from outer rings to downtown. Due to urban greening policies, landscape patches of UF or CS recently became larger and more aggregated. The CS by UF class distribution was skewed toward low values in all the years, but the skew gradually decreased over time. It was estimated that the average annual increase of CS by UF could offset 3.9% of the average annual increase in urban carbon emissions. CONCLUSIONS: Our study proposes that spatio-temporal changes in UF patterns dramatically affected the amount of CS and carbon capture. The increase in UF coverage and quality would mitigate more urban carbon emissions, especially in outer rings.