scholarly journals Flash Flood Characteristics of Ciberang River, Its Impact and Mitigation

2021 ◽  
Vol 930 (1) ◽  
pp. 012085
Author(s):  
V Say ◽  
D Legono ◽  
A P Rahardjo ◽  
R A Yuniawan
Keyword(s):  
Flash Flood ◽  
Satellite Image ◽  
Image Data ◽  
Steep Slope ◽  
Decision Makers ◽  
Mountainous Regions ◽  
Impact Area ◽  
Satellite Image Data ◽  
The Impact ◽  
Flood Characteristics

Abstract Flash flood is a deadly natural disaster that develops at space and time scales caused by high rainfall intensities and frequently occurs. It occurs in mountainous regions with steep slope relief and often causes a loss of economy, society, and environment and threatens human lives. The Ciberang river is located at Lebak district, Banten Province, and has been experiencing a significant flash flood from December 31, 2019 to January 01, 2020, which contributed to various damages, including households nearby the river. In this study, the impact areas were identified with the HEC-RAS model and satellite image data. The impact area was damage on eight sub-districts, including agriculture (77.86 Ha), buildings (0.80 Ha), roads (2.5 km), and nine bridges. In addition, this study tried to build Sabo Dam upstream of Banjar Irigasi sub-districts to respond to the flash flood occurrence. The results have reduced the discharge to around 40 m3/s, and the travel time was delayed about 53 min. The results of this study help the community and decision-makers be ready for further flash flood disasters.

scholarly journals NDVI Based Analysis on the Impact of 2004 Tsunami Disaster Recovery Toward Vegetation Condition in Banda Aceh

2019 ◽  
Vol 8 (3) ◽  
pp. 66-71
Author(s):  
Zinatul Hayati ◽  
Saumi Syahreza ◽  
M Syukri Surbakti
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Landsat Imagery ◽  
Satellite Image ◽  
Image Data ◽  
Tsunami Disaster ◽  
Satellite Image Data ◽  
2004 Tsunami ◽  
The Impact ◽  
Banda Aceh

Perubahan tutupan lahan banyak terdapat di kota-kota yang sedang berkembang. Banda Aceh, Indonesia merupakan salah satu provinsi yang sudah mengalami peningkatan jumlah penduduk dan percepatan pembangunan. Pasca bencana gempa dan tsunami 2004 perubahan penggunaan dan tutupan lahan (land use and land cover change/LULC) terlihat semakin meluas, dan hal ini berdampak pada berkurangnya lahan vegetatif. Artikel ini menjelaskan cara menganalisis NDVI dengan mengunakan data citra satelit Landsat 5 dan 8 untuk mengetahui kerapatan vegetasi di wilayah Banda Aceh dengan 9 kecamatan yang diambil tahun 2004, 2009, dan 2017. Studi ini mengidentifikasi antara pola perubahan tutupan lahan dan menyelidiki dampak tsunami, sehingga banyak kehilangan vegetasi pada lingkungan tersebut. Penelitian ini menggunakan Sistem Informasi Geografis (GIS) dimana tahap awal adalah mengumpulkan data citra satelit. Pada tahap kedua dilakukan pengolahan data menggunakan software PCI Geomatika 2016. Hasil analisa citra menjelaskan tahun 2004, 2009 dan 2017  kawasan kehijauan, masih banyak terdapat di kecamatan Lueng Bata, Ulee Kareng dan Banda Raya. Changes in land cover are often found in developing cities. Banda Aceh is one of the provinces in Indonesia that experiences an increase in the population and accelerated development. Land use and land cover (LULC) have increased dramatically since the 2004 earthquake and tsunami disaster and continued to reduce the vegetative land. This article explains how to analyze NDVI using Landsat 5 and 8 of the satellite image data. It aims to determine the vegetation density of Banda Aceh in 9 sub-districts taken in 2004, 2009 and 2017. This study identified patterns of changes in land cover and investigated the impact of the tsunami on the vegetational loss of the environment. Geographic Information System (GIS) was used in the study in which the satellite image data were collected before they were processed in the PCI Geomatika 2016 software. The results indicate that in the years of 2004, 2009 and 2017, many green areas are present in Lueng Bata, Ulee Kareng and Banda Raya sub-district. Keywords: Remote Sensing, Landsat Imagery, and NDVI

Visual Evidence of Constrained Area of a Cloudburst, 12 June 2018, Tirisha Village, Nubra Valley, Ladakh, India

2020 ◽  
Vol 6 (2) ◽  
pp. 47-57
Author(s):  
Renoj J. Thayyen ◽  
Mritunjay Kumar Singh ◽  
A.P. Dimri
Keyword(s):  
Satellite Data ◽  
Flash Flood ◽  
Satellite Image ◽  
Lapse Rate ◽  
Mountain Ridge ◽  
Temperature Lapse Rate ◽  
Visual Evidence ◽  
Impact Area ◽  
The Impact ◽  
First Time

On 12 June 2018, the Tirisha village in Nubra valley, Ladakh experienced a flash flood from a cloudburst that occurred over the mountain ridge. This event was captured in a Sentinel 2B satellite image at the time of its occurrence. The image also provided unique visual evidence of the constrained area of a cloudburst for the first time. Field survey of impact area at the Tirisha village was carried out on 13 June 2018. It was followed by assessment of the impact at the place of occurrence and further downstream using satellite data taken on, before and subsequent days. Satellite data show small area where cloudburst impact (< 1km2) from a cumulonimbus (Cb) cell of ~2.97 km2 of cloud top area. Rest of the flood catchment remained cloud-free during the event and floodwater in the stream is clearly visible in the imagery. The flash flood entered the Tirisha village situated at the Nubra valley foothills, which destroyed a stretch of 100 m road. Previous studies have suggested inherent atmospheric instability over the arid Ladakh region with an extremely high-temperature lapse rate of >9.8 K/km during 40-70 days during summer months. The extremely constrained nature of this event highlights the challenges involved in monitoring, forecasting and managing such events in the Himalayan region.

scholarly journals Verification of multispectral data processing for the Sentinel-2A bands, field ASD FieldSpec® 3FR and UAV with the DJI STS-VIS

2019 ◽  
pp. 29-39 ◽  
Author(s):  
Stanislav Dugin ◽  
Oksana Sybirtseva ◽  
Stanislav Golubov ◽  
Yelizaveta Dorofey
Keyword(s):  
Pearson Correlation ◽  
Plant Cover ◽  
Satellite Image ◽  
Vegetation Indices ◽  
Image Data ◽  
Multispectral Data ◽  
Maximum Value ◽  
Substantial Correlation ◽  
Satellite Image Data ◽  
Sentinel 2A

The study of plant cover have been performed by the hyperspectral remote sensing method using ASD FieldSpec® 3FR and DJI STS-VIS measurements. The orthophotoplans are compiled for the test plots of interest at the spatial resolution of 2.5 cm. The substantial correlation for the results of terrestrial verification for the satellite image data in the range of Sentinel-2A bands are confirmed. 15 vegetation indices for the Sentinel-2А wavelength bands were drawn at the Pearson correlation coefficient r > 0.97, with a maximum value of the correlation error of 0.07.

scholarly journals Classification of the NOAA Satellite Image Data by Unsupervised Neural Network

1993 ◽  
Vol 29 (3) ◽  
pp. 281-287 ◽  
Author(s):  
Goutam CHAKRABORTY ◽  
Jun-ichi KUDOH ◽  
Norio SHIRATORI ◽  
Shoichi NOGUCHI
Keyword(s):  
Neural Network ◽  
Satellite Image ◽  
Image Data ◽  
Noaa Satellite ◽  
Unsupervised Neural Network ◽  
Satellite Image Data
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