Minimum Thresholding Method Research Articles

A Survey on Global Thresholding Methods for Mapping Open Water Body Using Sentinel-2 Satellite Imagery and Normalized Difference Water Index

The aim of this study is to investigate the performance of fifteen automatic thresholding methods, namely Huang and Wang’s fuzzy thresholding method, inter-mode thresholding method, isodata thresholding method, Li and Tam’s thresholding method, maximum entropy thresholding method, mean thresholding method, minimum error thresholding method, minimum thresholding method, moment-preserving thresholding method, Otsu’s thresholding method, percentile (p-tile) thresholding method, Renyi’s entropy thresholding method, Shanbhag’s thresholding method, triangle thresholding method and Yen’s thresholding method, for mapping open water body using Sentinel-2 data based on Normalized Difference Water Index (NDWI). Sentinel-2 data was acquired on 22 September 2018 and Lake Salda from Turkey was selected as a test site. Due to the lack of digital reference data of the test site, Support Vector Machine (SVM) classification was implemented to Sentinel-2 data and the classified image was utilized as reference data since previous studies proved that SVM classification provided better results than the thresholding methods. SVM classification results were evaluated using 1000 random points and the Overall Accuracy (OA) and Kappa coefficient were obtained 96.2% and 0.90, respectively. The thresholding methods were assessed using the statistical measures, namely OA, Kappa and Misclassification Error (ME). Considering the remote sensing perspective, all thresholding methods presented satisfying results having at least 92% OA for open water body extraction. The obtained accuracy results showed that minimum thresholding method was the best method among these fifteen algorithms with 0.000264 ME, 99.9355% OA and 0.9987 Kappa. On the other hand, p-tile and Shanbhag’s thresholding method provided the worst accuracy results for open water body delineation.

Potential of global thresholding methods for the identification of surface water resources using Sentinel-2 satellite imagery and normalized difference water index

The aim of this study is to investigate the performance of 15 automatic thresholding methods, namely Huang and Wang’s fuzzy thresholding method, intermode thresholding method, isodata thresholding method, Li and Tam’s thresholding method, maximum entropy thresholding method, mean thresholding method, minimum error thresholding method, minimum thresholding method, moment-preserving thresholding method, Otsu’s thresholding method, percentile (p-tile) thresholding method, Renyi’s entropy thresholding method, Shanbhag’s thresholding method, triangle thresholding method, and Yen’s thresholding method, for mapping water body using Sentinel-2 data based on normalized difference water index. Three different types of surface water bodies, such as a natural lake (Lake Burdur), a dam reservoir (Aslantaş Dam Reservoir), and a part of a river (Aras River), are chosen to reveal the potential of 15 thresholding methods. The reference water body maps of each test site were generated by manual digitization of high-resolution Google Earth images. The thresholding methods were assessed using the statistical measures, namely overall accuracy (OA), Kappa coefficient, producer’s accuracy, user’s accuracy, and misclassification error (ME). The accuracy analyses of 15 thresholding methods were carried out separately for each test site, and then the overall accuracies were calculated to determine the best method. The obtained OA results showed that minimum thresholding method was the best method among these 15 algorithms with 0.0008 ME, 99.92% OA, and 0.9758 Kappa coefficient. On the other hand, Shanbhag’s method provided the lowest overall accuracies as 0.3133 ME, 68.67% OA, and 0.3190 Kappa coefficient.