Author(s)

Zhen Chen¹, Yiyang Zheng^2*

¹School of Earth Sciences and Resources, China University of Geosciences (Beijing), Beijing, China.
²Mudanjiang Natural Resources Survey Center, China Geological Survey, Mudanjiang, China.

In this paper, Hailin City of Heilongjiang Province, China is taken as the research area. As an important city in Heilongjiang Province, China, the sustainable development of its ecological environment is related to the opening up, economic prosperity and social stability of Northeast China. In this paper, the remote sensing ecological index (RSEI) of Hailin City in recent 20 years was calculated by using Landsat 5/8/9 series satellite images, and the temporal and spatial changes of the ecological environment in Hailin City were further analyzed and the influencing factors were discussed. From 2003 to 2023, the mean value of RSEI in Hailin City decreased and increased, and the ecological environment decreased slightly as a whole. RSEI declined most significantly from 2003 to 2008, and it increased from 2008 to 2013, decreased from 2013 to 2018, and increased from 2018 to 2023 again, with higher RSEI value in the south and lower RSEI value in the northwest. It is suggested to appropriately increase vegetation coverage in the northwest to improve ecological quality. As a result, the predicted value of Elman dynamic recurrent neural network model is consistent with the change trend of the mean value, and the prediction error converges quickly, which can accurately predict the ecological environment quality in the future study area.

Remote Sensing Ecological Index, Long Time Series, Space-Time Change, Elman Dynamic Recurrent Neural Network

Chen, Z. and Zheng, Y. (2024) Study on Ecological Change Remote Sensing Monitoring Method Based on Elman Dynamic Recurrent Neural Network. Journal of Geoscience and Environment Protection, 12, 31-44. doi: 10.4236/gep.2024.124003.