Utility of Normalized Difference Water Index and GIS for Mapping Surface Water Dynamics in Sub-Upper Krishna Basin

Ashtekar, Avinash S.; Mohammed‐Aslam, M. A.; Moosvi, Ali Raza

doi:10.1007/s12524-019-01013-6

Cited by 16 publications

(3 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The relation between the green and NIR bands highlights in the images the conditions of high soil moisture and water masses [35][36][37]. In turn, it highlights the upper wetting limit of the foreshore caused by the highest run-up of the last high tide before the satellite image acquisition date.…”

Section: Image Processingmentioning

confidence: 94%

Long-Term Analysis of Wave Climate and Shoreline Change along the Gulf of California

et al. 2020

View full text Add to dashboard Cite

The last ten years have shown that Climate Change (CC) is a major global issue to attend to. The integration of its effects into coastal impact assessments and adaptation plans has gained great attention and interest, focused on avoiding or minimizing human lives and asset losses. Future scenarios of mean sea level rises and wave energy increase rates have then been computed, but downscaling still remains necessary to assess the possible local effects in small areas. In this context, the effects of CC on the wave climate in the Gulf of California (GC), Mexico, have received little attention, and no previous studies have tackled the long-term trend of wave climate at a regional scale. In this paper, the long-term trends of the wave height, wave period and wave energy in the GC were thus investigated, using the fifth-generation climate reanalysis dataset (ERA5). The long-term shoreline evolution was also examined from historical Landsat images, so as to identify erosional hotspots where intervention can be prioritized. The results indicate that both the mean and extreme wave regimes in the GC are getting more energetic and that two-thirds of the coast is suffering chronic erosion. A discrepancy between the trends of the wave period and wave height in some regions of the Gulf was also found. Finally, the importance of natural processes, human activity and CC in the shoreline change is highlighted, while addressing the need for future permanent field observations and studies in the GC.

show abstract

Section: Image Processingmentioning

confidence: 94%

Long-Term Analysis of Wave Climate and Shoreline Change along the Gulf of California

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Normalized Difference Water Index (NDWI) is the most frequently used method of mapping waterbodies in a wetland because it is easily distinguished in visible green and near-infrared (NIR) wavelengths region due to their strong absorptivity (Ashtekar et al 2019;Yan et al 2017;Bahera et al 2012). The NDWI pixels value greater than zero shows the waterbodies in wetlands.…”

Section: Mapping Of Waterbody In the Reservoir Using Ndwimentioning

confidence: 99%

Hydrological Change Detection Mapping and Monitoring of Ramganga Reservoir, Pauri Gharwal, Uttarakhand, Using Geospatial Technique

Rawat

Pandey

Yadav

et al. 2021

Geospatial Technologies for Land and Water Resources Management

View full text Add to dashboard Cite

Wetlands serve an essential role in conserving the ecological balance of both biotic and abiotic lives in both inland and coastal environments. Hence, understanding their existence and the spatial extent of change in the wetland ecosystem is vital and monitored using remote sensing technology. A study was performed for the Ramganga reservoir, located in Uttarakhand, India, one of the important wetlands in Uttarakhand that comes under Ramsar sites with many bird species and is rich in biodiversity. The present study modeled the spatiotemporal changes of the reservoir using the multi-temporal Landsat TM (1992, 2000, and 2010) and Landsat OLI-TIRS (2020) imageries. While performing spatiotemporal analysis, the applicability of various satellite-derived indexes such as the Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Turbidity Index (NDTI) has been employed for retrieval of wetland elements including the wetland extent boundary, water-spread area, aquatic vegetation, and turbidity level of the reservoir during preand post-monsoon seasons by using remote sensing and hierarchical decision tree algorithm. In the post-monsoon season, the minimum and maximum water-spread areas were 59.98 km 2 in 1992 and 74.30 km 2 in 2010, respectively. Similarly, in the pre-monsoon season, the reservoir had a minimum, and the maximum water-spread area was 28.697 km 2 in 2010 and 58.536 km 2 in 2020, respectively. The total aquatic vegetation of wetland was increased from 3.41 to 4.14 km 2 in the years 1992 and 2020 during post-monsoon. Throughout the study period, the medium turbidity level in the reservoir was observed to be less than 1 km 2 . The result indicates that these different satellite-derived spectral indices are less time-consuming and provide more accurate mapping and wetlands monitoring. This requires constant monitoring of the

show abstract

“…Normalized difference water index (NDWI) derived from satellite images are commonly and successfully utilized in surface water body detection and mapping (Du et al 2014(Du et al , Özelkan 2020. NDWI was used to detect the surface water bodies in parts of Upper Krishna River basin, Maharashtra State of India (Ashtekar et al 2019). However, this type of analytical operations needs specific high-end software and voluminous downloaded data sets to create desired output which is time cumbersome process.…”

mentioning

confidence: 99%

Surface Water Mapping using Google Earth Engine (GEE) for South Gujarat Forest

2023

IJE

View full text Add to dashboard Cite

The spatial and temporal changes in surface water area were analyzed in Dang district of south Gujarat. The time series of normalized difference water index (NDWI) with Google earth engine (GEE) open source online planetary processing platform was used. Spatial distribution precipitation, LST, NDVI and ETa were also analyzed. The surface water availability showed high positive correlation with precipitation (0.76), LST (0.93) and (0.90). ETThe surface water availability varied month wise, minimum surface water area was observed in a May while maximum in January Availability of surface water increases NDVI and ETa thus decrease LST and . .Present results vice-versa would be helpful to planner and forest department to make decisions for water conservation activities in forest area.

show abstract

Utility of Normalized Difference Water Index and GIS for Mapping Surface Water Dynamics in Sub-Upper Krishna Basin

Cited by 16 publications

References 15 publications

Long-Term Analysis of Wave Climate and Shoreline Change along the Gulf of California

Long-Term Analysis of Wave Climate and Shoreline Change along the Gulf of California

Hydrological Change Detection Mapping and Monitoring of Ramganga Reservoir, Pauri Gharwal, Uttarakhand, Using Geospatial Technique

Surface Water Mapping using Google Earth Engine (GEE) for South Gujarat Forest

Contact Info

Product

Resources

About