Water Feature Extraction and Change Detection Using Multitemporal Landsat Imagery
By K. Rokni, A. Ahmad, Ali Selamat, Sharifeh Hazini. Remote Sensing, 2014
644 citations recorded by the source corpus.
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.
Subfields: Ecology, Environmental Engineering, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/d5ced483b12ff2bd68e31415614bcd6922371822
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Citations in the corpus
- Water Bodies' Mapping from Sentinel-2 Imagery with Modified Normalized Difference Water Index at 10-m Spatial Resolution Produced by Sharpening the SWIR Band (2016, methodology): “extracted water features and detected change using Landsat TM, ETM+ and OLI images [26].”
- A Spatial-Temporal Attention-Based Method and a New Dataset for Remote Sensing Image Change Detection (2020, background): “Remote sensing change detection (CD) is the process of identifying "significant differences" between multi-temporal remote sensing images [1] (the significant difference usually depends on a specific application), which has many applications, such as urbanization monitoring [2,3], land use change de”
- SwinSUNet: Pure Transformer Network for Remote Sensing Image Change Detection (2022, background): “CD technology is widely used in urban expansion [1, 2], ecosystem monitoring [3], land use change detection [4], damage assessment [5], environmental monitoring [6] and so on.”