Surface water detection and delineation using remote sensing images: a review of methods and algorithms

Bijeesh, T. V.; Narasimhamurthy, K.N.

doi:10.1007/s40899-020-00425-4

Cited by 81 publications

(67 citation statements)

References 95 publications

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“…Droughts and climate variability cannot be completely understood, without understanding their impacts on the environment and societies [47]. Monitoring trends and profiling their impacts on surface water resources is important, as it helps to make informed decisions to address and mitigate the impacts [48].…”

Section: Zimbabwementioning

confidence: 99%

“…As previously mentioned, the first Landsat mission was launched in 1972 and has since been supplying medium resolution images [47]. Additional Landsat satellite missions were launched in the late 1970s and the 1980s [65].…”

Section: Advancements In Remote Sensing Systems and Their Role In Dromentioning

confidence: 99%

“…Landsat 7 was launched in 1999 and was comprised of the Enhanced Thematic Plus (ETM+) [65]. These Landsat missions were often used to detect surface water bodies and detect changes on the Earth's surface [47]. Landsat 8 was launched in February 2013 and consists of the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS).…”

Section: Advancements In Remote Sensing Systems and Their Role In Dromentioning

confidence: 99%

“…The Sentinel-2 sensor, launched in June 2015, provides the most requisite spatial data continuity for climate variability and drought monitoring, in addition to SPOT and Landsat missions, among others [47]. It consists of the Multispectral Instrument (MSI) and has 13 reflective wavelength bands, four 10 m visible and near-infrared (NIR) bands, six 20 m red edge, near infrared, and shortwave infrared (SWIR) bands, and three 60 m bands [47]. Sentinel-2 has a temporal resolution of 5 days and has a swath of 290 km ( Table 2).…”

Section: Advancements In Remote Sensing Systems and Their Role In Dromentioning

confidence: 99%

“…With the advancement in technology, there has been an increased use of satellite images for various water related studies [47]. For instance, advancements in the development of water indices, analysis or integration techniques, and availability of multi-temporal and multi-spectral images mean that it is easier to detect changes in surface water bodies [26].…”

Section: Remote Sensing Products For Drought and Climate Variability mentioning

confidence: 99%

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Impacts of Climate Variability and Drought on Surface Water Resources in Sub-Saharan Africa Using Remote Sensing: A Review

et al. 2020

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Climate variability and recurrent droughts have caused remarkable strain on water resources in most regions across the globe, with the arid and semi-arid areas being the hardest hit. The impacts have been notable on surface water resources, which are already under threat from massive abstractions due to increased demand, as well as poor conservation and unsustainable land management practices. Drought and climate variability, as well as their associated impacts on water resources, have gained increased attention in recent decades as nations seek to enhance mitigation and adaptation mechanisms. Although the use of satellite technologies has, of late, gained prominence in generating timely and spatially explicit information on drought and climate variability impacts across different regions, they are somewhat hampered by difficulties in detecting drought evolution due to its complex nature, varying scales, the magnitude of its occurrence, and inherent data gaps. Currently, a number of studies have been conducted to monitor and assess the impacts of climate variability and droughts on water resources in sub-Saharan Africa using different remotely sensed and in-situ datasets. This study therefore provides a detailed overview of the progress made in tracking droughts using remote sensing, including its relevance in monitoring climate variability and hydrological drought impacts on surface water resources in sub-Saharan Africa. The paper further discusses traditional and remote sensing methods of monitoring climate variability, hydrological drought, and water resources, tracking their application and key challenges, with a particular emphasis on sub-Saharan Africa. Additionally, characteristics and limitations of various remote sensors, as well as drought and surface water indices, namely, the Standardized Precipitation Index (SPI), Palmer Drought Severity Index (PDSI), Normalized Difference Vegetation (NDVI), Vegetation Condition Index (VCI), and Water Requirement Satisfaction Index (WRSI), Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Land Surface Water Index (LSWI+5), Modified Normalized Difference Water Index (MNDWI+5), Automated Water Extraction Index (shadow) (AWEIsh), and Automated Water Extraction Index (non-shadow) (AWEInsh), and their relevance in climate variability and drought monitoring are discussed. Additionally, key scientific research strides and knowledge gaps for further investigations are highlighted. While progress has been made in advancing the application of remote sensing in water resources, this review indicates the need for further studies on assessing drought and climate variability impacts on water resources, especially in the context of climate change and increased water demand. The results from this study suggests that Landsat-8 and Sentinel-2 satellite data are likely to be best suited to monitor climate variability, hydrological drought, and surface water bodies, due to their availability at relatively low cost, impressive spectral, spatial, and temporal characteristics. The most effective drought and water indices are SPI, PDSI, NDVI, VCI, NDWI, MNDWI, MNDWI+5, AWEIsh, and AWEInsh. Overall, the findings of this study emphasize the increasing role and potential of remote sensing in generating spatially explicit information on drought and climate variability impacts on surface water resources. However, there is a need for future studies to consider spatial data integration techniques, radar data, precipitation, cloud computing, and machine learning or artificial intelligence (AI) techniques to improve on understanding climate and drought impacts on water resources across various scales.

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Section: Zimbabwementioning

confidence: 99%

Section: Advancements In Remote Sensing Systems and Their Role In Dromentioning

confidence: 99%

Section: Advancements In Remote Sensing Systems and Their Role In Dromentioning

confidence: 99%

Section: Advancements In Remote Sensing Systems and Their Role In Dromentioning

confidence: 99%

Section: Remote Sensing Products For Drought and Climate Variability mentioning

confidence: 99%

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Impacts of Climate Variability and Drought on Surface Water Resources in Sub-Saharan Africa Using Remote Sensing: A Review

et al. 2020

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The use of remote sensing indices to understand flood‐recharged soil moisture impacts on trees in semi‐arid floodplains: A review

et al. 2022

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Remote sensing indices (RSIs) are essential for detection, mapping and monitoring of floods, soil moisture and tree characteristics. An understanding of the nexus between flood-recharged soil moisture (FRSM) and endangered biodiversity tree hotspots in semi-arid floodplains is critical. Specifically, the influence of FRSM on biophysical characteristics of keystone tree species with social, economic, ecological and environmental functions is crucial. However, the use of RSIs to understand the link between episodic floods, FRSM and trees, as well as their respective spatiotemporal dynamics within the semi-arid floodplains, remains largely unexplored. Hence, this study reviewed literature on the adoption of RSIs in understanding short-term phenological and long-term tree structural changes arising from flood-related infiltration. The reviewed literature shows the predominance of the normalised difference water index, the land surface water index and normalised difference vegetation index for flood, FRSM and tree mapping. The review also shows the emergence of SAR-based normalised difference flood index for understanding the impacts of FRSM on riparian trees. Although the review identified an increase in data availability, however, there are high costs of active commercial remote sensing data of superior quality and computing resources. Furthermore, available free data are incapable of penetrating canopies and have coarse spatial resolution constraining the use of RSIs to understand the impacts of FRSM on trees. In view of increasing free SAR data and cloudbased computing resources, application of emerging deep learning algorithms offers prospects for the use of RSIs to understand the impacts of FRSM on riparian trees.

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Mapping of the Himalayan Surface Waters Using Remote Sensing and Geographic Information System Tools: An Overview of Single Band-Based Techniques

Ganie

Posti

Kunal

2023

Fisheries and Aquaculture of the Temperate Himalayas

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Surface water detection and delineation using remote sensing images: a review of methods and algorithms

Cited by 81 publications

References 95 publications

Impacts of Climate Variability and Drought on Surface Water Resources in Sub-Saharan Africa Using Remote Sensing: A Review

Impacts of Climate Variability and Drought on Surface Water Resources in Sub-Saharan Africa Using Remote Sensing: A Review

The use of remote sensing indices to understand flood‐recharged soil moisture impacts on trees in semi‐arid floodplains: A review

Mapping of the Himalayan Surface Waters Using Remote Sensing and Geographic Information System Tools: An Overview of Single Band-Based Techniques

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