Lakes are areas of ecological significance that host a wide range of living species. Therefore, monitoring changes in lake surfaces is critical for ecosystem preservation. Since conventional methods based on one-dimensional data analysis have limited capacity to analyze complex systems, they may not always produce the desired results in examining surface change. In this regard, a novel approach based on a three-way analysis model of a multi-temporal dataset was improved for the first time to monitor surface changes in Lake Burdur between 2014 and 2023 in terms of latitude, longitude, and year modes. The newly proposed approach, based on the deconvolution of a multi-temporal data series, provided a new way and an alternative approach with a three-dimensional perspective for the simultaneous prediction of changes in latitude, longitude, and relative quantity profiles of Lake Burdur between 2014 and 2023. The proposed approach is based on the parallel factor analysis (PARAFAC) modeling of the multi-temporal datasets. The change in the lake surface as water levels were monitored from latitudinal and longitudinal profiles was obtained by applying the PARAFAC model to the multi-temporal data array. In the same model, the change in lake water surface over the years was determined from the relative quantity profile. The results obtained from the three-way analysis model were compared with the results provided by the conventional method. It was concluded that the findings of this study could provide valuable information to researchers and policymakers in developing effective strategies to analyze changes in lake surfaces in future studies.
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