Mapping small and medium-sized water reservoirs using Sentinel-1A: a case study in Chiapas, Mexico
| Autor: | Pilar Henao, Boris Escalante-Ramírez, Alejandra A. López-Caloca |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Synthetic aperture radar
010504 meteorology & atmospheric sciences Contextual image classification Noise reduction 0211 other engineering and technologies Feature selection 02 engineering and technology 01 natural sciences law.invention Speckle pattern law Binary data General Earth and Planetary Sciences Radar Spatial analysis Geology 021101 geological & geomatics engineering 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | Journal of Applied Remote Sensing. 14:1 |
| ISSN: | 1931-3195 |
| Popis: | Using satellite data to study small water bodies (SWB) and medium-sized water bodies (MSWB) is extremely useful for understanding their status, how to conserve them as water reservoirs, and their vulnerability to climate variability. The images studied in our work correspond to different-sized lagoons located in areas with high and low topography in a tropical region of Chiapas, Mexico. Our research project delineates SWB and MSWB. For this analysis, we considered water bodies to be uniform regions in a synthetic aperture radar image. The robustness of the method was determined based on an analysis of the morphologies of 23 lagoons. Several methods, including Hermite transform, were analyzed and compared with other image denoising methods used to improve speckle reduction. To obtain additional spatial information for image classification, we analyzed texture using the gray-level co-occurrence matrix. The results indicate that the Hermite filter is the best method for identifying water bodies. The advantage of this filter is the identification of local patterns such as edges and lines. It also preserves and improves aspects related to the homogeneity of water bodies, using the Hermite coefficient selection criteria for local pattern feature selection/extraction. The lake water extent products demonstrate that Sentinel-1 is useful for identifying SWB in this study area. The results show very high detection of water bodies, with adequate detection for water bodies larger than 2 ha, and an area accuracy of 80%. |
| Databáze: | OpenAIRE |
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