| # | Document title | Authors | Year | Source | Cited by |
| 1 | The classification of noise-afflicted remotely sensed data using three machine-learning techniques: Effect of different levels and types of noise on accuracy | Boonprong S., Boonprong S., Cao C., Chen W., Ni X., Xu M., Acharya B.K., Acharya B.K. | 2018 | ISPRS International Journal of Geo-Information
7(7) | 25 |
| 2 | Random forest variable importance spectral indices scheme for burnt forest recovery monitoring-multilevel RF-VIMP | Boonprong S., Boonprong S., Cao C., Chen W., Bao S., Bao S. | 2018 | Remote Sensing
10(6) | 22 |
| 3 | A novel classification technique of Landsat-8 OLI image-based data visualization: The application of Andrews' plots and fuzzy evidential reasoning | Boonprong S., Cao C., Torteeka P., Chen W. | 2017 | Remote Sensing
9(5) | 10 |
| 4 | The dynamics of wetland cover change using a state estimation technique applied to time-series remote sensing imagery | Insom P., Insom P., Cao C., Boonsrimuang P., Torteeka P., Torteeka P., Boonprong S., Boonprong S., Liu D., Liu D., Chen W. | 2017 | Geomatics, Natural Hazards and Risk
8(2),pp. 1662-1677 | 4 |
| 5 | A straightforward framework to find crop age from multiple satellite images: A case study of para rubber | Boonprong S., Torteeka P., Jongkroy P., Raksapatcharawong M., Sukawattanavijit C. | 2018 | Proceedings - 39th Asian Conference on Remote Sensing: Remote Sensing Enabling Prosperity, ACRS 2018
2,pp. 636-644 | 0 |
| 6 | Bare Land Referenced Algorithm from Hyper-Temporal Data (BRAH) for Land Use and Land Cover Age Estimation | Boonprong S., Khantachawana A. | 2023 | Land
12(7) | 0 |