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1

Department of Geoinformation, Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia

2

UTM-IRDA Digital Media, K-Economy Research Alliance UTM and Faculty of Computing, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia

3

Institute of Geospatial Science and Technology INSTeG, Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia





*

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Abstract Lake Urmia is the 20th largest lake and the second largest hyper saline lake before September 2010 in the world. It is also the largest inland body of salt water in the Middle East. Nevertheless, the lake has been in a critical situation in recent years due to decreasing surface water and increasing salinity. This study modeled the spatiotemporal changes of Lake Urmia in the period 2000–2013 using the multi-temporal Landsat 5-TM, 7-ETM+ and 8-OLI images. 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 AWEI were investigated for the extraction of surface water from Landsat data. Overall, the NDWI was found superior to other indexes and hence it was used to model the spatiotemporal changes of the lake. In addition, a new approach based on Principal Components of multi-temporal NDWI NDWI-PCs was proposed and evaluated for surface water change detection. The results indicate an intense decreasing trend in Lake Urmia surface area in the period 2000–2013, especially between 2010 and 2013 when the lake lost about one third of its surface area compared to the year 2000. The results illustrate the effectiveness of the NDWI-PCs approach for surface water change detection, especially in detecting the changes between two and three different times, simultaneously. View Full-Text

Keywords: NDWI; Landsat; surface water; change detection NDWI; Landsat; surface water; change detection





Autor: Komeil Rokni 1,* , Anuar Ahmad 1,* , Ali Selamat 2 and Sharifeh Hazini 3

Fuente: http://mdpi.com/



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