As technology develops, the use of artificial intelligence is increasingly widespread, including in remote sensing. Artificial intelligence can also be used to obtain various information from satellite imagery such as image processing, recognition, or identification. The existence of this technology is in-line with the increasing availability of various existing satellite images. Artificial intelligence can assist users in detecting objects in the image more faster than the traditional ones. In the identification process through image, training data is needed in the form of a dataset with a certain label. In this paper, we will discuss the method creation of remote sensing dataset for estimating burned area by using Landsat-8 imagery with Python and Geographic Information System (GIS) software. The final purpose of this study is to provide the dataset of burned area considering that almost every year Indonesia experiences land fires. With the dataset for the burnt area, it is hoped that it can help respond to and handle fire disasters more quickly and efficiently.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    The development of remote sensing dataset for burned areas using Landsat-8 imagery, case study Indonesia



    Conference:

    THE 9TH INTERNATIONAL SEMINAR ON AEROSPACE SCIENCE AND TECHNOLOGY – ISAST 2022 ; 2022 ; Bogor, Indonesia


    Published in:

    Publication date :

    2023-12-11


    Size :

    8 pages





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English