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

Abstract

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 RSEI_LA (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 RSEI_LA, 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 RSEI_LA, the results of RSEIFE effectively reveal the ecological benefits of both water bodies themselves and their surrounding environments, which lead to more accurate and comprehensive basis for the implementation of environmental protection policies.

Keywords: Eco-environment quality; Entropy method; Remote sensing ecological index (RSEI); Surface ecological simulation.