Abstract
The correlation coefficient can calculate paired correlations among different ecological indicators as a whole, but it cannot calculate the specific interval association and the correlation among multiple indicators. This paper proposed an interval association (IA) method of the remote sensing ecological index (RSEI), based on the concept lattice and frequent closed itemset. In the IA method, the ecosystem was viewed as a complex system with a hierarchical structure, and the association among multiple indicators was calculated using the information granulation of RSEI. The interval association support degree (IASD) could measure the association clustering strength of these IA concepts. Calculation of MODIS data compiled by Google Earth Engine (GEE) showed that the IA concepts of RSEI in China were primarily composed of selected middle indicator intervals in 2017. The overall eco-environmental condition in China was general when assessed through IA. The spatial distribution of the remote sensing eco-environment in China displayed strong spatial association clustering. Furthermore, the IA of RSEI focused on the first few concepts with high IASD values.
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Acknowledgements
The authors deeply appreciate the Guangxi Natural Science Foundation, the National Natural Science Foundation of China, and the anonymous reviewers for their insightful comments and suggestions.
Availability of data and materials
The datasets generated and analysed during the current study are available in the GEE repository, (https://code.earthngine.google.com/).
Funding
This research was funded by the Guangxi Natural Science Foundation (Grant No. 2020GXNSFAA297176), and the National Natural Science Foundation of China (Grant No. 41571077, U1901219).
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WHL analysed and interpreted the IA among NDVI, NDWI, LST, and NDBI of the RSEI indicator system and proposed a framework for calculating and analysing the IA of RSEI in China. XN calculated the IA results of RSEI in China for 5 years, i.e. 2000, 2005, 2009, 2014, and 2017, explained the results, and was a major contributor in writing the manuscript. ZHZ was a major contributor in writing the manuscript. All the authors read and approved the final manuscript.
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Liao, W., Nie, X. & Zhang, Z. Interval association of remote sensing ecological index in China based on concept lattice. Environ Sci Pollut Res 29, 34194–34208 (2022). https://doi.org/10.1007/s11356-021-17588-y
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DOI: https://doi.org/10.1007/s11356-021-17588-y