Improving flood monitoring in rural areas using remote sensing

Ghofrani, Zahra; Sposito, Victor; Faggian, Robert

doi:10.2166/wpt.2018.118

Cited by 6 publications

(4 citation statements)

References 12 publications

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“…Khosravani et al (2017) have shown that the NDWI index is more accurate than the other indices for change detection of lake Parishan. Ghofrani et al, 2019…”

Section: Resultsmentioning

confidence: 99%

“…Flooding is one of the most common and destructive natural hazards affecting human life and creating many economic problems around the world. Therefore, accurate monitoring of flood events is increasingly necessary to gain insight about both causes and remedies (Refice et al, 2017;Ghofrani et al, 2019). The first concern in flood management plans is mapping flood area.…”

Section: Introductionmentioning

confidence: 99%

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Flood Monitoring Using Ndwi and Mndwi Spectral Indices: A Case Study of Aghqala Flood-2019, Golestan Province, Iran

Soltanian

Abbasi

Bakhtyari

2019

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

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Assessment of changes of water bodies and vegetation by traditional methods is very difficult and costly. The use of satellite data makes it possible to study water bodies and vegetation more accurately and cost effectively. Accordingly, various digital methods have been developed to discover and detect changes of earth's surface features. Flood is one of the important factors contributing to the destruction of natural resources. The purpose of this research is to evaluate the flood areas in the Aghqala area in Golestan province of Iran. The level of water bodies in the spring of 2018 and 2019 was compared and evaluated based on the NDWI and MNDWI indices using Landsat images. The results showed that water bodies' area in the spring of 2018 was 24.13 km 2 which increased to 185.34 km 2 at 2019 using NDWI; while the MNDWI due to the excessive sensitivity to the water considered agriculture wetlands as an area of water bodies. Therefore, the NDWI yielded more logical results. Also, change detection methods based on spectral and radiometric information using indices are more accurate than the classification maps and more changes can be shown. Using satellite imagery to monitor changes is essential to facilitate the planning of natural hazards management.

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“…Khosravani et al (2017) have shown that the NDWI index is more accurate than the other indices for change detection of lake Parishan. Ghofrani et al, 2019…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Flood Monitoring Using Ndwi and Mndwi Spectral Indices: A Case Study of Aghqala Flood-2019, Golestan Province, Iran

Soltanian

Abbasi

Bakhtyari

2019

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

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“…In Shouguang, both algorithms based on Sentinel-1 and Sentinel-2 with random forest classification for rivers showed OA values of 85.22% and 95.45%, respectively (Huang and Jin 2020). Furthermore, for rural watershed areas in Australia, using two algorithms based on Landsat Oli 8 imagery with unsupervised classification proved to be effective, with OA values of 96.04% and 95.70%, respectively (Ghofrani et al 2019). Implementation on rivers and lakes in Canada, the Tennessee River in the US, the Swedish lake Lungsjön, and Mongolia's Lake Khar-Us using Sentinel-2 imagery showed outstanding accuracy with consecutive OA values based on the NDWI (0.97, 0.965, 0.94, and 0.925) and the MNDWI (0.97, 0.962, 0.96, and 0.945;Niu et al 2022).…”

Section: Discussionmentioning

confidence: 99%

Flood mapping based on open-source remote sensing data using an efficient band combination system

Hidayah

Pranadiarso

Halik

et al. 2022

AGS

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Flood mapping is an essential component of planning flood mitigation. The availability of remote sensing data makes rapid flood mapping possible. This article develops an accurate method for rapid flood mapping using satellite imagery. Sentinel-2 imagery was tested by acquiring data before and after a flood event in a lowland area. Flooding extraction was performed using the newly developed Flood Inundation Extraction Index (FIEI) and compared to the Modified Normalized Difference Water Index (MNDWI), the most commonly used index. Based on the choice of threshold, the results are divided into flooded and non-flooded areas. Evaluation of the performance accuracy based on the total and kappa coefficients showed that the FIEI approach is more accurate than the MNDWI approach.

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“…According to the study by Blöschl et al (2017) larger part of Bosnia and Herzegovina faced altered temporal flood patterns which resulted in earlier floods. Monitoring flood events is critical for gaining insights into causes and flood damages (Ghofrani et al, 2019;Refice et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal patterns of flooded areas in the lower part of the Sana river basin (Bosnia and Herzegovina)

Ivanišević

Savić

Pavić

et al. 2022

B SERBIAN GEOGRAPHIC

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Floods are the most frequent and devastating natural hazard event in Bosnia and Herzegovina. The detected increase in extreme precipitation over the study area in the last period has altered flood event patterns due to climate changes. Higher frequency of flood events and lack of flood protection infrastructure has a severe impact on socio-economic sectors and natural ecosystems. This paper focuses on the identification of flooded areas for each single flooding event in the lower part of the Sana river basin during the period 2016-2020. For delineating flooded areas, both radar and optical satellite imagery were used. Data obtained after processing remote sensing images were overlaid with a detailed land cover map in order to get insight into flooded land cover types. From temporal aspects, floods are most common during the spring season. They are usually caused by rapid snowmelt and prolonged excessive precipitation. Considering spatial aspects, flooded areas vary from 110 to 522 hectares in the study area. Over 95% of the flooded areas are arable land, meadows and pastures. Most affected settlements by floods are urban and suburban area of Prijedor, Gomjenica, Hambarine, Rakovcani, Rizvanovici, Brezicani, Donja Dragotinja, Vitasavci, Svodna, Blagaj Rijeka and urban area of Novi Grad. The applied methodological approach represents a starting point for further investigation of flooded areas in the Sana basin and data obtained by this analysis can be used in water management, spatial planning and emergency planning.

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Improving flood monitoring in rural areas using remote sensing

Cited by 6 publications

References 12 publications

Flood Monitoring Using Ndwi and Mndwi Spectral Indices: A Case Study of Aghqala Flood-2019, Golestan Province, Iran

Flood Monitoring Using Ndwi and Mndwi Spectral Indices: A Case Study of Aghqala Flood-2019, Golestan Province, Iran

Flood mapping based on open-source remote sensing data using an efficient band combination system

Spatio-temporal patterns of flooded areas in the lower part of the Sana river basin (Bosnia and Herzegovina)

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