Spatial and temporal characteristics of carbon storage in Beihai City under land use change based on InVEST model
DOI:
https://doi.org/10.54097/oe5hcra7Keywords:
Land use change, Beihai City, InVEST model, Carbon stockAbstract
Land use change is a crucial factor influencing changes in carbon storage, and its impact on the carbon cycle and climate change holds significant importance. This study investigates land use changes in Beihai City, utilizing the InVEST model to assess carbon storage. It analyzes the spatiotemporal variations of carbon storage in different time periods and demonstrates the trends and spatial distribution characteristics of different land use types. The primary findings indicate that over the past two decades, cultivated land and forest land have been the main types of land use in Beihai City. Land use conversion primarily occurs between forest land and cultivated land, as well as between cultivated land and water areas. Overall, there has been an increasing trend in carbon storage within Beihai City, largely attributed to expansions in both forested areas and cultivated lands. Furthermore, there are disparities in how different conversions between various land use type
References
O'Neil S.COP 26:Some progress,but nations still fiddling while world warms[J]. Engineering, 2022, 1(4):6-8.
Guo Xiaohui, Xue Shiyu, Zhu Lirong, et al. Impacts of land use/cover and climate change on runoff in the upper reaches of Wanquan River[J]. Journal of Hainan University (Natural Science Edition), 2023, 41(1):48-55.
Qu Songjie, Han Ling, Huang Xin, et al.Spatiotemporal evolution analysis of carbon storage in Shaanxi Province under different scenarios in the future.202310028.
Zhu Zhiqiang, Ma Xiaoshuang, Hu Hong, 2021. Spatiotemporal Evolution and Prediction of Ecosystem Carbon Storage in Guangzhou Based on Coupled FLUS-InVEST Model[J]. Bulletin of Soil and Water Conservation. 2013.
Yang Xiaowei, Zhao Juan, Zhu Jiatian, et al.Spatiotemporal change and prediction of ecosystem carbon storage in Xi'an City based on PLUS and InVEST models[J].Natural Resources Remote Sensing,2022.
Shao Zhuang, Chen Ran, Zhao Jing, et al.Spatiotemporal evolution and prediction of ecosystem carbon storage in Beijing based on FLUSH and InVEST models[J].Acta Ecologica Sinica,2022,42(23):9456-9469.
Zhang Yucheng, Han Nianlong, Hu Ke et al.Effect of land use change on the spatial and temporal differentiation of carbon storage in the mountainous areas of central Hainan Island[J].Journal of Nanjing Forestry University (Natural Science Edition), 2023, 47(02).
Wang Chaoyue, Guo Xianhua, Guo Li, et al.Land use change and its impact on carbon storage in Northwest China based on FLUS-InVEST: A case study of Hubao-Hubei and Yu urban agglomeration[J].Chinese Journal of Ecology and Environmental Sciences, 2022, 31(08).
Tang Lingdong, Liang Gaodou, Gu Guanhai, Xu Jun, Lian Duan, Zhang Xinying, Yang Xiaoxiong, Lu Rucheng. Spatiotemporal Evolution Characteristics, Pattern and Driving Mechanism of Ecological Environment of China's Land Boundary Ecological Security Barrier[J]. Review of Environmental Impact Assessment, 1032023, Volumes 1-18.
Miao Yiyi.Simulation study on county land use change and carbon storage optimization based on FLUS and InVEST models[D]. Shandong Agricultural University, 2023.
Yang Yuanyuan, Dai Erfu, Fu Hua.Research Framework for Ecosystem Service Function Value Evaluation Based on InVEST Model.Journal of Capital Normal University. 2012.
Zhao Xianchao, Zhu Xiang, Zhou Yueyun, 2013. Analysis of carbon emission effects and spatio-temporal patterns of different land use patterns in Hunan Province[J]. Journal of Environmental Science, 33(03): 941-949.
Zhou Rubo, Lin Meizhen, Wu Zhuo, et al., 2018. Response of ecosystem carbon storage to land use change on the west bank of the Pearl River[J]. Ecological Science, 37(06): 175-183.
Zhu Pengfei.Ecological effects of land use/cover change in coastal areas of Guangxi based on InVEST model.Nanning, Guangxi Normal University.2018.
Zhang You. Study on carbon emission effect in Chengdu Plain region based on LUCC[D]. Sichuan Normal University, 2018.
Zhang Yucheng, Han Nianlong, Hu Ke, et al.Effect of land use change on the spatial and temporal differentiation of carbon storage in the mountainous areas of central Hainan Island[J].Journal of Nanjing Forestry University (Natural Science Edition), 2023, 47(02):115-122.
Zhang Tianhai, Tian Ye, Xu Shu, et al., 2018. Evolution of land use pattern in coastal cities and its impact on ecosystem service value[J]. Chinese Journal of Ecology, 38(21): 7572-7581.
Wu Bin, Zhang Wenzhu, Tian Yichao, Liang Mingzhong, Xu Jun, Gu Guanhai. Ecosystem characteristics and carbon storage of typical mangrove islands in the Beibu Gulf of the South China Sea[J]. Journal of Resources and Ecology, 2022, 13(3), 458-465.
Zhang Meng. Spatiotemporal evolution of land use in the process of urbanization and its impact on carbon storage and carbon cycle in urban forests[D]. Zhejiang A&F University, 2020.
Tao Zhou, Peijun Shi.Indirect effects of land use change on soil carbon storage in China.Advances in Earth Science.2006. (02).
Spatiotemporal characteristics of terrestrial carbon storage in Ganzi Prefecture from 2000 to 2020 based on land use change based on InVEST model.2022.
Xu Jun, Li Jiansong, Peng Hao, He Yanjun, Wu Bin. Information Extraction from High-resolution Remote Sensing Images Based on Multi-scale Segmentation and Case Inference[J]. Photogrammetry Engineering and Remote Sensing, Vol. 88, No. 3, March 2022, pp. 199-205.
Jun Xu, Li Jiansong. A Method for Constructing a Case Database Using High-resolution Remote Sensing Land Cover Classification Information[J]. Journal of Space Science, 65 (2018): 173-184.
Xu Jun, Li Jiansong, Peng Hao, He Yanjun, Wu Bin. Information Extraction from High-resolution Remote Sensing Images Based on Multi-scale Segmentation and Case Inference[J]. Photogrammetry Engineering and Remote Sensing, Vol. 88, No. 3, March 2022, pp. 199-205.
Jun, Xu, Li Jiansong. A method for constructing a case library based on high-resolution remote sensing landcover classification information[J]. Journal of Space Science, 65 (2018): 173-184.
Xu Jun, Zhang Xinmiao, Li Jiansong. Road extraction method for high-resolution remote sensing images based on two-layer CBR model. Journal of Dalian Maritime University. 2017,43 (4):104-111.
Xu Jun, Li Xin, Li Jiansong. Water information extraction from remote sensing images based on example inference. Journal of Guangxi University (Natural Science Edition). 2017,42 (3):1078-1085.
Zhao M, Zhou G, 2003. Estimation of forest vegetation carbon storage in China and its response to climate change[C]. Abstracts of the 70th Annual Meeting of the Botanical Society of China (1933-2003), 301.
Zhu Chao, Zhao Shuqing, Zhou Decheng, 2012. Estimation of organic carbon storage in urban built-up areas of China from 1997 to 2006[J]. Chinese Journal of Applied Ecology, 23(05): 1195-1202.
Fang Jingyun, Huang Yao, Zhu Jiangling, et al.Forest ecosystem carbon budget and its influencing mechanism[J].China Basic Science, 2015, 17(3):20-25.
Wu Peijun, Liu Xiaoping, Li Xia, et al.Impact Assessment of Urban Expansion on Carbon Storage in Terrestrial Ecosystems Based on InVEST Model and Cellular Automata—A Case Study of Guangdong Province. Geography and Geoscience. 2016.
Feng Jingke.Analysis of spatio-temporal changes and driving forces of land use in Guilin City from 2000 to 2020.2022(3), F301, 24.
Ge Fei, Xu Jingjia, Jia Fengming.Analysis of land use change and its driving factors in Foshan City from 2000 to 2020.20231121.
Duan Xuanyu, Gong Wenfeng, Sun Yuxin, et al.Land use change in the coastal zone of Hainan Island and its impact on the temporal and spatial evolution of carbon storage[J].Bulletin of Soil and Water Conservation, 2022, 42(5):301-311.
Deng Zhe, Ding Wenguang, Pu Xiaoting, et al.Spatiotemporal distribution of carbon storage in Qilian Mountain National Park based on InVEST model[J].Bulletin of Soil and Water Conservation,2022,42(3):324-334,396.
Qi M, Wang F, Hua Yongchun, et al.Land use change and carbon storage assessment in Inner Mongolia Autonomous Region based on PLUS and InVEST models.20230905.
Fang Zanshan, Zhong Cairong, Wang Fengxia, et al.Spatiotemporal evolution and prediction of carbon storage in Hainan Island ecosystem coupled with InVEST and FLUSH model.Bulletin of Soil and Water Conservation. 2023. 43(05).
Yin Ke, Liao Siyu.Spatiotemporal variation and prediction of carbon storage in the Three Gorges Reservoir area (Chongqing section) based on InVEST and PLUS models.2024.
Li Xiaojun, Che Liangge, Hu Baoqing. Analysis of spatiotemporal differences of ecosystem carbon storage in Beihai City based on FLUS-InVEST model[J].Bulletin of Surveying and Mapping,2023,(06).
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.