RSEIFE: A new remote sensing ecological index for simulating the land surface eco-environment

With the development of remote sensing technology, significant progress has been made in the evaluation of the eco-environment. The remote sensing ecological index (RSEI) is one of the most widely used indices for the comprehensive evaluation of eco-environmental quality. This index is entirely based on remote sensing data and can monitor eco-environmental aspects quickly for a large area. However, the use of RSEI has some limitations. For example, its application is generally not uniform, the obtained results are stochastic in nature, and its calculation process cannot consider all ecological elements (especially the water element). In spite of the widespread application of the RSEI, improvements to its limitations are scarce. In this paper, we propose a new index named the remote sensing ecological index considering full elements (RSEIFE). The proposed RSEIFE is compared with commonly used evaluation models such as RSEI and RSEILA (Remote Sensing Ecological Index with Local Adaptability) in several types of study areas to assess the stability and accuracy of our model. The results show that the calculation process of RSEIFE is more stable than those of RSEI and RSEILA, and the results of RSEIFE are consistent with the real eco-environment surface and reveal more details about its features. Meanwhile, compared with RSEI and RSEILA, the results of RSEIFE effectively reveal the ecological benefits of both water bodies themselves and their surrounding environments, which lead to more accurate and compre-hensive basis for the implementation of environmental protection policies.

Automated summary

With the advancement of remote sensing technology, the remote sensing ecological index (RSEI) has been widely used for evaluating eco-environmental quality. However, the limitations of RSEI, such as lack of uniform application, stochastic results, and inability to consider all ecological elements, have led to the proposal of a new index named RSEIFE. Comparisons with other evaluation models have shown that RSEIFE has a more stable calculation process, consistent results with the real eco-environment, and the ability to reveal more details about its features. Moreover, RSEIFE effectively demonstrates the ecological benefits of both water bodies and their surrounding environments, providing a more accurate and comprehensive basis for environmental protection policies.