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Research on remote sensing ecological environmental assessment method optimized by regional scale

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Abstract

As the global ecosystem has been severely disturbed by an increasing number of human activities at different scales, remote sensing technology, as an effective quantitative measure of environmental quality, has been widely used. The remote sensing ecological index (RSEI) is one of the most popular and comprehensive ecological quality assessment indices based on the remote sensing data. However, the RSEI model exhibits that the ecological environment under natural conditions is not limited by the spatial scales. In addition, the model has major shortcomings in index selection and eigenvector, which greatly limit the application of RSEI. In this paper, the RSEI model is improved and a remote sensing ecological index optimized by the regional scale (RO-RSEI) is proposed. The result of the study, conducted in Shuangyang District, Changchun City, Jilin Province, shows that the RO-RSEI model has regional ecological significance after the introduction of the scale theory of landscape ecology; the index is preferred to solve problems like the RSEI model applied mechanization and baseless index selection. Meanwhile, due to the optimization of the eigenvector contribution of the optimal index, it solves the problems like non-unique model calculation result caused by principal component analysis or even antipodal calculation result. Compared with the RSEI model, the monitoring result of RO-RSEI model can better reflect the regional ecological changes. The improved model offers the possibility of monitoring ecological environment quality with remote sensing big data and provides a scientific basis for future scholars’ batch computing.

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Data availability

The data sources used in the current research are all public data (the data sources are listed in the first section of the article).

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Funding

This research was funded by the Jilin Provincial Department of Education Project, grant numbers: JJKH201911246KJ and JJKH20191267KJ.

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Authors and Affiliations

  1. School of Prospecting and Surveying, Changchun Institute of Technology, Changchun, 130022, China

    Fang Jiang

  2. Graduate School, Changchun Institute of Technology, Changchun, 130022, China

    Yaqiu Zhang & Junyao Li

  3. Qinghai Bureau of Coal Geology, Qinghai, 810000, China

    Zhiyong Sun

Authors
  1. Fang Jiang
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  2. Yaqiu Zhang
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  3. Junyao Li
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  4. Zhiyong Sun
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Contributions

Conceptualization: Fang Jiang, Yaqiu Zhang. Methodology: Fang Jiang, Yaqiu Zhang, Junyao Li, Zhiyong Sun. Writing: Yaqiu Zhang, Junyao Li. Visualization: Yaqiu Zhang, Junyao Li. Funding acquisition: Fang Jiang, Zhiyong Sun

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Correspondence to Zhiyong Sun.

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Jiang, F., Zhang, Y., Li, J. et al. Research on remote sensing ecological environmental assessment method optimized by regional scale. Environ Sci Pollut Res 28, 68174–68187 (2021). https://doi.org/10.1007/s11356-021-15262-x

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  • DOI: https://doi.org/10.1007/s11356-021-15262-x

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