Surface water estimation at regional scale using hybrid techniques in GEE environment-A case study on Punjab State of India

Sur, Koyel; Verma, Vibha

doi:10.1016/j.rsase.2021.100625

Cited by 7 publications

(7 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With the immense amount of data accumulated through satellite RS imagery over time, the use of traditional software for processing remote sensing data has become timeconsuming, costly, and inefficient (Sur et al, 2021). RS cloud computing, with its high-performance computing efficiency, enables effective solutions to geographic research problems in vast areas and over long periods of time.…”

Section: Discussionmentioning

confidence: 99%

Meteorological driving factors effecting the surface area of Ebinur Lake and determining associated trends and shifts

Yao

Wang²,

Chen³

et al. 2022

Front. Environ. Sci.

View full text Add to dashboard Cite

Changes in lake water resources and regional hydrological processes in response to climate change and human activity necessitates timely and accurate access to lake change information to monitor water cycles and water security. The Ebinur Lake Basin has experienced a serious ecological crisis in recent years, which is majorly due to excess use of its water. Therefore, in this study, we used Ebinur Lake as a research object, and used Geographic Information System and remote sensing technology, Landsat, Sentinel, and MODIS images, the Google Earth Engine platform, and the water body index method to determine the changes in lake area from April to October of 2011–2020. Daily data from the Alashankou and Jinghe meteorological stations from 2011 to 2020 were collected. The center of gravity-geographically and temporally weighted regression model was used to analyze the factors changes in surface area. The results showed obvious spatial and temporal heterogeneities for the surface area. Except for 2016, which had unusual/extreme weather, in the last decade, the lake surface area generally showed a monthly decreasing trend from April to October. When Ebinur Lake is one water body, the surface area ranges between 530 and 560 km2. We concluded that the spatio-temporal characteristics of Ebinur Lake can be divided into two levels. When the southeast and northwest regions of the lake merge, it represents the largest possible surface area of Ebinur Lake; this was called the “water storage level”. Historically, Ebinur Lake has lost significant amounts of water, and there is no water body connecting the two main parts of the lake (thereby dividing the lake into two areas); this was called “water demand level”. The trajectory of the center of gravity of the lake is linear, with a slope of 45° and a direction of northwest to southeast. The lake gravity center has different aggregation states. According to the season, it can be divided into spring gathering and autumn gathering. The variation in the surface area of Ebinur Lake is highly correlated with the meteorological and hydrological variation during the year. The highest correlation was observed between lake surface area and wind speed. This study aimed to supplement other studies that explore the lake annually and provide a reference for future water resources management and planning.

show abstract

Section: Discussionmentioning

confidence: 99%

Meteorological driving factors effecting the surface area of Ebinur Lake and determining associated trends and shifts

Yao

Wang²,

Chen³

et al. 2022

Front. Environ. Sci.

View full text Add to dashboard Cite

show abstract

“…During the past few years, a variety of methods and algorithms based on remote sensor image processing have been developed for surface water extraction, such as water detection criteria and the Otsu threshold method (Deng et al, 2019; Sur et al, 2021; Zou et al, 2017). However, our initial experiments suggested that these methods may not be able to generate genuinely reliable outcomes yielding, in some cases, incomplete surface water extraction (and see Deng et al, 2019; Zhou et al, 2021).…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, after computing MNDWI, the Otsu method was used to extract surface water. The equation for computing the optimal threshold for any MNDWI images is as follows (Sur et al, 2021):…”

Section: Seasonal Surface Water Extractionmentioning

confidence: 99%

“…The Otsu approach is based on a histogram-based threshold aiming to find a critical value which divides the pixel distribution of an image into two classes (i.e., background and foreground) so as to minimize the between-class variance and maximize the difference between classes. This method has been widely applied for surface water extraction (Sur et al, 2021). Therefore, after computing MNDWI, the Otsu method was used to extract surface water.…”

Section: Seasonal Surface Water Extractionmentioning

confidence: 99%

“…Given such considerations, remotely sensed data, especially given the increasing availability of cloud computing infrastructures, offer a potentially valuable means of analyzing time series of water surface change and hydrological connectivity at multiple scales, such as catchment and regional scales (Robinson et al, 2015; Mateo et al, 2017). However, water body extraction methods based on remote sensing data mostly use histogram threshold segmentation and water detection criteria (Deng et al, 2019; Sur et al, 2021), which leads to the inaccurate extraction of water bodies, especially in rivers with high turbidity. Accordingly, in this study, an integrated approach considering multiple methods and remote sensing products is used to achieve high-precision extraction of water body extent.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Considering the dynamics of water surface boundaries to measure the evolution of hydrological connectivity in the Yangtze River Delta, China

Li,

Kong,

Yin

et al. 2023

Progress in Physical Geography: Earth and Environment

View full text Add to dashboard Cite

Dynamics of the terrestrial water surface impact hydrological connectivity. Compared with traditionally deployed water surface parameters, changes in the water-boundary more effectively account for the dynamics of water surface and depth resulting from hydrological variations. However, previous studies of hydrological connectivity generally applied only connectivity length or width parameters using the center line of the water body and therefore fail to fully capture the impact of water boundary dynamics. In this study, optimized water body extraction indices based on data obtained from remote sensing imagery are used to develop a novel metric that indicates water surface boundary dynamics and reveal surface hydrological connectivity changes in the Yangtze River Delta from 1990 to 2020. Detailed inter-annual and seasonal changes in the evolution of water body boundaries from a water surface perspective indicate an overall decline in hydrological connectivity against the background of climate change, increased urbanization, and dam construction. The declining trend in connectivity occurs in three phases, viz. from 1990 to 2003, a gradual decline is exhibited but with a very marked degree of inter-seasonal variability; between 2003 and 2012, connectivity remains relatively constant but with a reduced amplitude between seasons; further reductions in the magnitude of seasonal variations characterize the third phase, to 2020. Meanwhile, the stability of hydrological connectivity, indicated by the coefficient of variation, also exhibits marked spatial heterogeneity. Parts of the delta with more tributaries, including the Huaihe and southeastern basins, have lower stability (7.33 and 6.59, respectively) than the Yangtze basin (6.22). This study presents a novel metric to achieve greater precision in the monitoring of hydrological connectivity. Such information can be harnessed to improve regional ecological and water resource management.

show abstract

Spatio–temporal water quality assessment of Chohal and Damsal dams located in Kandi region of Punjab, India by geospatial technique and on-site investigation

Singh,

Sur

2024

Environ Earth Sci

View full text Add to dashboard Cite

Surface water estimation at regional scale using hybrid techniques in GEE environment-A case study on Punjab State of India

Cited by 7 publications

References 21 publications

Meteorological driving factors effecting the surface area of Ebinur Lake and determining associated trends and shifts

Meteorological driving factors effecting the surface area of Ebinur Lake and determining associated trends and shifts

Considering the dynamics of water surface boundaries to measure the evolution of hydrological connectivity in the Yangtze River Delta, China

Spatio–temporal water quality assessment of Chohal and Damsal dams located in Kandi region of Punjab, India by geospatial technique and on-site investigation

Contact Info

Product

Resources

About