Abstract
Landsat remote sensing image is a widely used data source in water remote sensing. Normalized difference water index (NDWI), modified normalized difference water index (MNDWI) and automated water extraction index (AWEI) are commonly used water extraction classifiers. In the process of their application, because the threshold varies with the location and time of the research object, how to select the threshold with the highest classification accuracy is a time-consuming and challenging task. The purpose of this study was to explore a method that can not only improve the accuracy of water extraction, but also provide a fixed threshold, and can meet the requirements of automatic water extraction. We introduced the local spatial auto correlation statistics and calculate the Getis-Ord Gi* index to have hot spot analysis. Comparative analysis showed that the accuracy of water classification had been greatly improved through hot spot analysis. AWEIsh classifier had the best classification accuracy under the condition of INVERSE_DISTANCE neighborhood rule and Z > 1.96, and the accuracy changes least in different time, different location and different vegetation coverage images. Therefore, in the process of regional water extraction, hot spot analysis method was effective, which was helpful to improve the accuracy of water extraction.
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Data availability statement
All data included in this study are available upon request by contact with the corresponding author.
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Funding
This research was funded by the National Key Research and Development Project of China (Grant no. 2018YFC0407703-1, 2017YFC0403301), Anhui University of Science and Technology Master's and Doctor's Fund Projects (Grant no. ZY030), Natural Science Foundation of the Anhui Higher Education Institutions of China (Grant no. KJ2017A072).
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Conceptualization, Xingyuan Cui and Lei Wang; Data curation, Jian Wang and Lei Wang; Formal analysis, Lei Wang; Funding acquisition, Xingyuan Cui; Methodology, Tao Su; Software, Jian Wang; Supervision, Lei Wang; Validation, Tao Su and Xingyuan Cui.
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Su, T., Wang, J., Cui, X. et al. Study on monitoring water area in irrigation area by local space self-correlation index. Environ Earth Sci 82, 18 (2023). https://doi.org/10.1007/s12665-022-10703-3
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DOI: https://doi.org/10.1007/s12665-022-10703-3