Satellite-based assessment of the August 2018 flood in parts of Kerala, India

Vishnu, C.L.; Sajinkumar, K.S.; Oommen, Thomas; Coffman, Richard A.; Thrivikramji, K. P.; Rani, V. R.; Keerthy, S.

doi:10.1080/19475705.2018.1543212

Cited by 108 publications

(35 citation statements)

References 22 publications

(21 reference statements)

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“…Nearly 500 people died in the event [74]. Parts of the city of Cochin-the commercial capital of Kerala-were flooded, with a 90% increase in water cover and a water level rise of up to 5 m to 10 m [75]. As a result, major infrastructure assets including the airport, roads and railways had to be closed for safety reasons.…”

Section: A Purpose-driven Approach To Uas Deployment In the Context Omentioning

confidence: 99%

Guidelines for the Use of Unmanned Aerial Systems in Flood Emergency Response

Salmoral

Casado

Muthusamy

et al. 2020

Water

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There is increasing interest in using Unmanned Aircraft Systems (UAS) in flood risk management activities including in response to flood events. However, there is little evidence that they are used in a structured and strategic manner to best effect. An effective response to flooding is essential if lives are to be saved and suffering alleviated. This study evaluates how UAS can be used in the preparation for and response to flood emergencies and develops guidelines for their deployment before, during and after a flood event. A comprehensive literature review and interviews, with people with practical experience of flood risk management, compared the current organizational and operational structures for flood emergency response in both England and India, and developed a deployment analysis matrix of existing UAS applications. An online survey was carried out in England to assess how the technology could be further developed to meet flood emergency response needs. The deployment analysis matrix has the potential to be translated into an Indian context and other countries. Those organizations responsible for overseeing flood risk management activities including the response to flooding events will have to keep abreast of the rapid technological advances in UAS if they are to be used to best effect.

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Section: A Purpose-driven Approach To Uas Deployment In the Context Omentioning

confidence: 99%

Guidelines for the Use of Unmanned Aerial Systems in Flood Emergency Response

Salmoral

Casado

Muthusamy

et al. 2020

Water

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“…A landslide inventory forms the basis for studies of landslide hazard, risk, and prevention studies (Fan et al, 2019;Guzzetti et al, 2012;Marcelino et al, 2009;Moosavi et al, 2014). Critical elements of analysis include their spatial distribution pattern (Duman et al, 2005;Galli et al, 2008;Xu, 2015), their occurrences with respect to landform evolution (Guzzetti et al, 2012;Rosi et al, 2018), and a range of other environment factors (Duman et al, 2005), susceptibility mapping (van Den Eeckhaut et al, 2009), triggering factors (Li et al, 2016), community risk assessment and mitigation (Marcelino et al, 2009), and land use planning and risk management (Colombo et al, 2005). A detailed landslide inventory should contain information on location, types of failures, geometries, date of occurrence, triggering factors, possible failure mechanisms, and damage caused (Rosi et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Constructing a complete landslide inventory dataset for the 2018 monsoon disaster in Kerala, India, for land use change analysis

Hao

Westen²,

Martha

et al. 2020

Earth Syst. Sci. Data

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Abstract. Event-based landslide inventories are important for analyzing the relationship between the intensity of the trigger (e.g., rainfall, earthquake) and the density of the landslides in a particular area as a basis for the estimation of the landslide probability and the conversion of susceptibility maps into hazard maps required for risk assessment. They are also crucial for the establishment of local rainfall thresholds that are the basis of early warning systems and for evaluating which land use and land cover changes are related to landslide occurrence. The completeness and accuracy of event-based landslide inventories are crucial aspects to derive reliable results or the above types of analyses. In this study, we generated a relatively complete landslide inventory for the 2018 monsoon landslide event in the state of Kerala, India, based on two inventories that were generated using different methods: one based on an object-based image analysis (OBIA) and the other on field surveys of damaging landslides. We used a collaborative mapping approach based on the visual interpretation of pre- and post-event high-resolution satellite images (HRSIs) available from Google Earth, adjusted the two inventories, and digitized landslides that were missed in the two inventories. The reconstructed landslide inventory database contains 4728 landslides consisting of 2477 landslides mapped by the OBIA method, 973 landslides mapped by field survey, 422 landslides mapped both by OBIA and field methods, and an additional 856 landslides mapped using the visual image (Google Earth) interpretation. The dataset is available at https://doi.org/10.17026/dans-x6c-y7x2 (van Westen, 2020). Also, the location of the landslides was adjusted, based on the image interpretation, and the initiation points were used to evaluate the land use and land cover changes as a causal factor for the 2018 monsoon landslides. A total of 45 % of the landslides that damaged buildings occurred due to cut-slope failures, while 34 % of those having an impact on roads were due to road cut-slope failures. The resulting landslide inventory is made available for further studies.

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“…Flood is one of the devastating natural calamities due to extreme rainfall events that affect the society (Mishra et al, 2018). Odisha flood (2006) (Bhatt et al, 2017;Vishnu et al, 2019). The use of geospatial data, tools and hydrological models has become essential part of flood studies world over in the last 30 years (Liu and De Smedt, 2005;Aggarwal et al, 2009;Dang and Kumar 2017).…”

Section: Introductionmentioning

confidence: 99%

“…The use of geospatial data, tools and hydrological models has become essential part of flood studies world over in the last 30 years (Liu and De Smedt, 2005;Aggarwal et al, 2009;Dang and Kumar 2017). The months of July-August, 2018 have seen heavy rainfall in the state of Kerala, India (CWC, 2018;Kerala State Disaster Management, 2018;Mishra et al, 2018;Vishnu et al, 2019) that caused worst flooded situations in the various regions of this state. The major rainfall events occurred at the end of July, 8-10 August and one extreme rainfall event occurred during 14-17 August 2018 (Table 1 showing total rainfall during 1 June -22 August 2018).…”

Section: Introductionmentioning

confidence: 99%

Synergistic Use of Remote Sensing, Gis and Hydrological Models for Study of August 2018 Kerala Floods

Thakur

Ranjan

Singh

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Remote sensing and hydrological models are one of the foremost tools for rapid and comprehensive study of flood hazards and disasters in any parts of the world. Current study is focused on severe 2018 Kerala flood, and is done using various remote sensing data, geospatial tools and combination of hydrological/hydrodynamic/topographical models. Flood mapping is done with pre and post floods remote sensing datasets. For pre-Flood analysis, Normalized Difference Water Index (NDWI) map was prepared on Google Earth Engine (GEE), using Sentinel-2 images for the period of Feb. 2017 to identify permanent water bodies. For post-Flood analysis, GEE was used to download the pre-processed and thermal noise removed Sentinel-1 SAR image for Aug. 9, 2018, Aug. 14 and Aug. 21, 2018 and flood maps were generated using this data. In addition to SAR data, probable flood inundation areas using topography-based flood inundation tool HAND (Height Above Nearest Drainage tool) was also utilized. Hydrological simulation was carried out for all 12 major river sub-basins of Kerala, where floods are reported. Indian Meteorological Department-Global Precipitation Measurement (IMD-GPM) gridded daily data is used as input meteorological data for hydrological simulations. The hydrological simulations results were verified using published Central Water Commission (CWC) reports and reservoirs data for India-WRIS. The hydrodynamic simulation was also performed for simulating the Idukki dam release data and flood condition in downstream areas. Overall, an integrated study and developed approach can be utilized by state and central water and disaster management agencies to develop flood early warning systems.

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Satellite-based assessment of the August 2018 flood in parts of Kerala, India

Cited by 108 publications

References 22 publications

Guidelines for the Use of Unmanned Aerial Systems in Flood Emergency Response

Guidelines for the Use of Unmanned Aerial Systems in Flood Emergency Response

Constructing a complete landslide inventory dataset for the 2018 monsoon disaster in Kerala, India, for land use change analysis

Synergistic Use of Remote Sensing, Gis and Hydrological Models for Study of August 2018 Kerala Floods

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