Predicting the impacts of urban land change on LST and carbon storage using InVEST, CA-ANN and WOA-LSTM models in Guangzhou, China-Reference-Cited by-同舟云学术

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Predicting the impacts of urban land change on LST and carbon storage using InVEST, CA-ANN and WOA-LSTM models in Guangzhou, China

Published:2022-11-17 Issue:1 Volume:16 Page:437-454
ISSN:1865-0473
Container-title:Earth Science Informatics
language:en
Short-container-title:Earth Sci Inform

Author:

Wang Ao,Zhang Maomao,Kafy Abdulla - Al,Tong Bin,Hao Daoqing,Feng Yanfei

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Link

https://link.springer.com/content/pdf/10.1007/s12145-022-00875-8.pdf

Reference50 articles.

1. Abbas Z, Yang G, Zhong Y, Zhao Y (2021) Spatiotemporal change analysis and future scenario of LULC using the CA-ANN approach: a case study of the Greater Bay Area, China. Land 10(6):584. https://doi.org/10.3390/land10060584

2. Abegaz A, Tamene L, Abera W, Yaekob T, Hailu H, Nyawira SS, Da Silva M, Sommer R (2020) Soil organic carbon dynamics along chrono-sequence land-use systems in the highlands of Ethiopia. Agric Ecosyst Environ 300(September):106997. https://doi.org/10.1016/j.agee.2020.106997

3. Ahmed Z, Asghar MM, Malik MN, Nawaz K (2020) Moving towards a sustainable environment: the dynamic linkage between natural resources, human capital, urbanization, economic growth, and ecological footprint in China. Resourc Policy 67(August):101677. https://doi.org/10.1016/j.resourpol.2020.101677

4. Boori MS, Choudhary K, Paringer R, Kupriyanov A (2021) Spatiotemporal ecological vulnerability analysis with statistical correlation based on satellite remote sensing in Samara, Russia. J Environ Manag 285(May):112138. https://doi.org/10.1016/j.jenvman.2021.112138

5. Bullock EL, Woodcock CE, Souza C, Olofsson P (2020) Satellite-based estimates reveal widespread Forest degradation in the Amazon. Glob Chang Biol 26(5):2956–2969. https://doi.org/10.1111/gcb.15029

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