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Unsupervised Burned Area Mapping in Greece: Investigating the Impact of Precipitation, Pre- and Post-Processing of Sentinel-1 Data in Google Earth Engine

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F23%3A10469958" target="_blank" >RIV/00216208:11310/23:10469958 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1109/IGARSS52108.2023.10283130" target="_blank" >https://doi.org/10.1109/IGARSS52108.2023.10283130</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/IGARSS52108.2023.10283130" target="_blank" >10.1109/IGARSS52108.2023.10283130</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Unsupervised Burned Area Mapping in Greece: Investigating the Impact of Precipitation, Pre- and Post-Processing of Sentinel-1 Data in Google Earth Engine

  • Original language description

    Wildfires are one of the most significant threats to ecosystems and are increasing in frequency globally. The aim of this study is to monitor the evolution of selected wildfires in Greece that occurred during August 2021 using Sentinel-1 SAR data and unsupervised k-means clustering in Google Earth Engine. First, changes in time series after the start of the fire and the influence of precipitation were investigated. In this study, the influence of different speckle filters and post-classification filters on clustering results was tested. The difference Normalized Burn Ratio Index (dNBR) derived from Sentinel-2 data was used as a validation dataset to assess accuracy using the F1-score, overall accuracy, omission and commission error. The best achieved F1-scores were higher than 0.70 with omission error lower than 35% in all selected areas, where the Lee speckle filter with an 11x11 kernel window size and a 2 ha post-classification filter performed the best.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10508 - Physical geography

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium

  • ISBN

    979-8-3503-2010-7

  • ISSN

    2153-6996

  • e-ISSN

    2153-7003

  • Number of pages

    4

  • Pages from-to

    2520-2523

  • Publisher name

    The Institute of Electrical and Electronics Engineers, Inc.

  • Place of publication

    California, USA

  • Event location

    Pasadena, California, USA

  • Event date

    Jul 16, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001098971602192