Rapid and robust monitoring of flood events using Sentinel-1 and Landsat data on the Google Earth Engine

DeVries, Ben; Huang, Chengquan; Armston, John; Huang, Wenli; Jones, John W.; Lang, Megan W.

doi:10.1016/j.rse.2020.111664

Cited by 311 publications

(175 citation statements)

References 60 publications

Supporting

Mentioning

165

Contrasting

Unclassified

Order By: Relevance

“…The performance of TropWet for mapping open water (user's accuracy: 93%, producer's accuracy: 88%) is equivalent to accuracies reported by approaches based on radar imagery [1][2][3][4][5][6][7]. As discussed previously, radar is better suited to an operational flood hazard mapping system (mainly due to its independence from cloud conditions), but our encouraging results demonstrate that TropWet can be used to make retrospective assessments of historic flood extent.…”

Section: Discussionsupporting

confidence: 51%

“…Monitoring the extent and dynamics of tropical wetlands is important for a range of application areas including, but not limited to, mapping flood water hazard [1][2][3][4][5][6][7], water-borne disease risk [8,9], monitoring wetland ecosystems habitats [10][11][12][13][14], and quantifying wetland-related greenhouse gas emissions [15][16][17][18]. Today's wealth of freely available satellite Earth Observation (EO) resources creates an exciting opportunity to develop the tools needed to provide timely and accurate information on wetlands at regional, national, and even continental scales.…”

Section: Introductionmentioning

confidence: 99%

“…Radar imagery provides one of the most reliable means of detecting flood water mainly due to the fact that this imagery is: (i) independent of cloud cover, (ii) relatively high resolution (e.g., Sentinel-1: 10 m), (iii) relatively high revisit times (e.g., Sentinel-1: 6-12 days), and (iv) there is a strong signal (low backscatter) over relatively smooth water surfaces. DeVries et al [6] used GEE to develop a robust and fully automated near real-time flood mapping system. By harnessing the GEE cloud-based resources, this approach accurately detects floods by interrogating dense-time series Sentinel-1 radar imagery, with refinement provided by optical Landsat-based surface water frequency occurrence maps (Global Surface Water product [33]).…”

mentioning

confidence: 99%

“…By harnessing the GEE cloud-based resources, this approach accurately detects floods by interrogating dense-time series Sentinel-1 radar imagery, with refinement provided by optical Landsat-based surface water frequency occurrence maps (Global Surface Water product [33]). However, like many operational flood monitoring systems [1][2][3][4][5][6][7], this approach is limited to the detection of open water and does not account for vegetated water bodies or emergent flooded vegetation that would be commonplace in a natural wetland landscape [34].L-band radar EO systems are possibly the most promising data for detecting both open water and inundated vegetation [34][35][36]. L band radar imagery not only exhibits distinctive low backscatter signals over relatively smooth open water surfaces, but also at this frequency, L band pulses have the ability to penetrate some vegetation canopies, enabling either a direct estimation of water surface or inference of inundated vegetation resulting from a double-bounce high backscatter mechanism [34][35][36].…”

mentioning

confidence: 99%

mentioning

confidence: 99%

See 4 more Smart Citations

Tropical Wetland (TropWet) Mapping Tool: The Automatic Detection of Open and Vegetated Waterbodies in Google Earth Engine for Tropical Wetlands

2020

View full text Add to dashboard Cite

Knowledge of the location and extent of surface water and inundated vegetation is vital for a range of applications including flood risk management, biodiversity monitoring, quantifying greenhouse gas emissions, and mapping water-borne disease risk. Here, we present a new tool, TropWet, which enables users of all abilities to map wetlands in herbaceous dominated regions based on simple unmixing of optical Landsat satellite imagery in the Google Earth Engine. The results demonstrate transferability throughout the African continent with a high degree of accuracy (mean 91% accuracy, st. dev 2.6%, n = 10,800). TropWet demonstrated considerable improvements over existing globally available surface water datasets for mapping the extent of important wetlands like the Okavango, Botswana. TropWet was able to provide frequency inundation maps as an indicator of malarial mosquito aquatic habitat extent and persistence in Barotseland, Zambia. TropWet was able to map flood extent comparable to operational flood risk mapping products in the Zambezi Region, Namibia. Finally, TropWet was able to quantify the effects of the El Niño/Southern Oscillation (ENSO) events on the extent of photosynthetic vegetation and wetland extent across Southern Africa. These examples demonstrate the potential for TropWet to provide policy makers with crucial information to help make national, regional, or continental scale decisions regarding wetland conservation, flood/disease hazard mapping, or mitigation against the impacts of ENSO.Landsat) with microwave systems (e.g., AMSR: Advanced Microwave Scanning Radiometer, SMAP: Soil Moisture Active Passive) [17,20]. Similarly, there is growing evidence that information from global navigation systems (GNSS-R: Global Navigation Satellite System Reflectometry) can provide timely and reliable classifications of wetlands by exploiting signals over both open water and vegetated water surfaces [21][22][23][24]. These approaches provide valuable tools for quantifying wetland dynamics at continental scales with important applications such as characterising greenhouse gas flux [17,18,24,25]. However, assessments of wetland extent and dynamics using these approaches tend to be generated at relatively coarse spatial resolutions (e.g., 25-36 km) and have limited applicability for informing decisions at a national or sub-national level, particularly related to more fine-scale environmental challenges such as those related to biodiversity, public health, and flood hazard.In terms of inundation mapping, perhaps the most mature area of research is the use of EO satellite imagery for mapping flood water hazards [2][3][4][5]7,[26][27][28][29][30][31][32]. Radar imagery provides one of the most reliable means of detecting flood water mainly due to the fact that this imagery is: (i) independent of cloud cover, (ii) relatively high resolution (e.g., Sentinel-1: 10 m), (iii) relatively high revisit times (e.g., Sentinel-1: 6-12 days), and (iv) there is a strong signal (low backscatter) over relatively smooth water surfaces. ...

show abstract

Section: Discussionsupporting

confidence: 51%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Tropical Wetland (TropWet) Mapping Tool: The Automatic Detection of Open and Vegetated Waterbodies in Google Earth Engine for Tropical Wetlands

2020

View full text Add to dashboard Cite

show abstract

Increased population exposure to Amphan‐scale cyclones under future climates

et al. 2022

View full text Add to dashboard Cite

Southern Asia experiences some of the most damaging climate events in the world, with loss of life from some cyclones in the hundreds of thousands. Despite this, research on climate extremes in the region is substantially lacking compared to other parts of the world. To understand the narrative of how an extreme event in the region may change in the future, we consider Super Cyclone Amphan, which made landfall in May 2020, bringing storm surges of 2–4 m to coastlines of India and Bangladesh. Using the latest CMIP6 climate model projections, coupled with storm surge, hydrological, and socio‐economic models, we consider how the population exposure to a storm surge of Amphan's scale changes in the future. We vary future sea level rise and population changes consistent with projections out to 2100, but keep other factors constant. Both India and Bangladesh will be negatively impacted, with India showing >200% increased exposure to extreme storm surge flooding (>3 m) under a high emissions scenario and Bangladesh showing an increase in exposure of >80% for low‐level flooding (>0.1 m). It is only when we follow a low‐emission scenario, consistent with the 2°C Paris Agreement Goal, that we see no real change in Bangladesh's storm surge exposure, mainly due to the population and climate signals cancelling each other out. For India, even with this low‐emission scenario, increases in flood exposure are still substantial (>50%). While here we attribute only the storm surge flooding component of the event to climate change, we highlight that tropical cyclones are multifaceted, and damages are often an integration of physical and social components. We recommend that future climate risk assessments explicitly account for potential compounding factors.

show abstract

Developing a composite index for urban ecosystem services (Hyrcanian forests—Gorgan)

Zoghi,

Amiri

2023

Integr Envir Assess & Manag

View full text Add to dashboard Cite

The current era has been termed the “Anthropocene,” because of the irreversible impact of human activities. Land use change and urban growth are examples of these disturbances leading to the reduction in many ecosystem services (ESs). The subject of this study, Gorgan, has undergone significant changes that significantly affected the area. Studying these changes and understanding their effects on the ecosystem is essential. An integrated method was used to investigate the process of changing the urban ESs over 35 years, considering the physical and ecological characteristics of the area. This marks the first time such a study has been conducted using the hexagonal unit. Then, the composite total ecosystem services (TESs) index was calculated from the modeled and quantified combination of six ESs, including water yield, flood volume, net primary production, soil retention, carbon sequestration, and air pollution removal. Thereafter, the ESs were mapped and evaluated across time and space. The TES is proposed as an appropriate measure for quantifying ES supply and can indicate the overall function of ESs. According to the findings, the TES value declined from 0.427 in 1985 to 0.247 in 2005 and declined to 0.192 in 2020. Moreover, the Hyrcanian forests were the main source of the highest TES in Gorgan city, whereas urban areas had the lowest levels. The shortage of ESs in the study area has resulted in various crises. These include reduced air quality, heightened flood risk, soil erosion, and ecological imbalances in urban regions. Integr Environ Assess Manag 2023;00:1–16. © 2023 Society of Environmental Toxicology & Chemistry (SETAC).

show abstract

Rapid and robust monitoring of flood events using Sentinel-1 and Landsat data on the Google Earth Engine

Cited by 311 publications

References 60 publications

Tropical Wetland (TropWet) Mapping Tool: The Automatic Detection of Open and Vegetated Waterbodies in Google Earth Engine for Tropical Wetlands

Tropical Wetland (TropWet) Mapping Tool: The Automatic Detection of Open and Vegetated Waterbodies in Google Earth Engine for Tropical Wetlands

Increased population exposure to Amphan‐scale cyclones under future climates

Developing a composite index for urban ecosystem services (Hyrcanian forests—Gorgan)

Contact Info

Product

Resources

About