CiteScore

0.5

Indexada na
SCOPUS

QUALIS

B2

2021-2024
quadriênio

Language

Brazilian Journal of Enviromnent

e-ISSN: 2595-4431


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Abstract

Hydrographic networks play a central role in the hydrological cycle and support a wide range of ecosystem services, including urban water supply and agricultural production. Accurate identification of these systems through remote sensing is essential for understanding their dynamics and supporting environmental management strategies. This study evaluated the performance of the spectral indices NDWI and NGWI in detecting water bodies across five Regions of Interest (ROIs) within the Amazon biome. The methodological approach integrated the K-means algorithm with indices derived from CBERS-4 satellite imagery, enabling the extraction of surface water areas. The results indicated better performance of NDWI, with an average median of 0.77, demonstrating greater stability and class separability. NGWI showed a lower median (0.44), but higher producer’s accuracy (82.70%), indicating greater sensitivity in detecting moist and saturated areas. In contrast, NDWI achieved higher user’s accuracy (94.87%), reflecting fewer false positives, while NGWI reached 92.52%. The Dice–Sørensen coefficient was 0.86 for both indices, indicating similar overall performance. These findings demonstrate that, although NDWI is more accurate in delineating open water bodies, NGWI provides complementary potential for identifying areas with surface moisture.

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright (c) 2026 Gabriel Henrique Santos da Silva, Juarez Antonio Da Silva Junior, Admilson da Penha Pacheco, Fabrício Eduardo Silva de Lima, Ubiratan Joaquim Da Silva Junior, Karoline Paes Jamur