Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery

By G. Feyisa, Henrik Meilby, R. Fensholt, S. Proud. 2014

1,831 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/995bd0b7b6f4b277a5cd41b6b954fe198e2729a5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Xuebin Qin
2. Ali Selamat
3. Na Zhao
4. Shanshan Zhao
5. Ligang Liang
6. Sharifeh Hazini
7. K. Rokni
8. A. Ahmad

Citations in the corpus

• Mapping of Urban Surface Water Bodies from Sentinel-2 MSI Imagery at 10 m Resolution via NDWI-Based Image Sharpening (2017, methodology): “Feyisa’s [38] Automated Water Extraction Index (AWEI) included two indices: AWEInsh (Equation (3)) is mainly used in areas with dark surfaces Figure 13.”
• Water Feature Extraction and Change Detection Using Multitemporal Landsat Imagery (2014, methodology): “In doing so, the applicability of different satellite-derived indexes including Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Normalized Difference Moisture Index (NDMI), Water Ratio Index (WRI), Normalized Difference Vegetation Index (NDVI), and Automated Water Extraction Index (”