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

Entin Hidayah; Tedy Pranadiarso; Gusfan Halik; Indarto Indarto; Wei-Koon Lee; Mokhammad Farid Maruf

doi:10.3986/AGS.10598

Avtorji

Entin Hidayah University of Jember, Faculty of Engineering, Department of Civil Engineering, Jember, Indonesia https://orcid.org/0000-0002-1233-6850
Tedy Pranadiarso University of Jember, Faculty of Engineering, Department of Civil Engineering, Jember, Indonesia https://orcid.org/0000-0003-2740-848X
Gusfan Halik University of Jember, Faculty of Engineering, Department of Civil Engineering, Jember, Indonesia https://orcid.org/0000-0002-5447-1268
Indarto Indarto University of Jember, Faculty of Agricultural Technology, Department of Agricultural Engineering, Jember, Indonesia https://orcid.org/0000-0001-6319-6731
Wei-Koon Lee University Teknologi Mara, School of Civil Engineering, Shah Alam, Malaysia https://orcid.org/0000-0003-3910-4870
Mokhammad Farid Maruf University of Jember, Faculty of Engineering, Department of Civil Engineering, Jember, Indonesia https://orcid.org/0000-0002-5715-935X

DOI:

https://doi.org/10.3986/AGS.10598

Ključne besede:

hitro kartiranje poplav, Sentinel-2, prilagojen normalizirani vodni indeks, ekstrakcijski indeks najvišjih poplav, kapa koeficient, pravilnost, Indonezija

Povzetek

Kartiranje poplav je ključno za načrtovanje blažitev njihovih posledic. Razpoložljivi podatki, zajeti z daljinskim zaznavanjem, nam to omogočajo. V članku razvijamo natančno metodo za hitro kartiranje poplav na podlagi satelitskih posnetkov. Posnetke Sentinel-2 smo testirali s podatki pred in po poplavi v nižinskem območju. Poplave smo zaznavali s pomočjo na novo razvitega ekstrakcijskega indeksa najvišjih poplav (FIEI) in ga primerjali s prilagojenim normaliziranim vodnim indeksom (MNDWI), ki je najpogosteje uporabljen indeks v tovrstnih raziskavah. Območja smo glede na izbor določenega praga razdelili na poplavljena in nepoplavljena. Vrednotenje natančnosti rezultatov na podlagi skupnih in kapa koeficientov je pokazalo, da je pristop FIEI natančnejši od pristopa MNDWI.

Prenosi

Podatki o prenosih še niso na voljo.

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