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Classification of Summer Crops Using Active Learning Techniques on Landsat Images in the Northwest of the Province of Buenos Aires

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Cloud Computing, Big Data & Emerging Topics (JCC-BD&ET 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1291))

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Abstract

The present work aims to obtain a classifier for summer crops in the northwest of Buenos Aires province from Landsat satellite images. Active Learning (AL) was used as the classification technique since it obtains satisfactory results using a small set of labeled samples to train the algorithm. The construction of the training set is iteratively performed by means of a heuristic for the selection of the unlabeled samples to be classified by an expert. The following heuristics were used for comparison: Breaking Ties, Multiclass Level Uncertainty, Margin Sampling, and Random Sampling. The algorithm was also compared with the supervised technique Support Vector Machine (SVM). The experiments were tested on three Landsat 8 images from different dates using 6 bands per image and various vegetation indices. The results obtained using AL in combination with the different heuristics do not differ substantially from SVM.

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Author information

Authors and Affiliations

  1. Institute of Research and Transfer of Technology (ITT), National University of Norwest of Buenos Aires Province (UNNOBA), Sarmiento 1169, 6000, Junín, Buenos Aires, Argentina

    Lucas Benjamin Cicerchia & Claudia Cecilia Russo

  2. Commission of Scientific Research of the Buenos Aires Province (CICPBA), Buenos Aires, Argentina

    María José Abasolo & Claudia Cecilia Russo

  3. Consejo Nacional de Investigaciones Científicas Y Técnicas (CONICET), Buenos Aires, Argentina

    Lucas Benjamin Cicerchia

  4. III-LIDI, Faculty of Informatics, National University of La Plata (UNLP), 50 and 120 Street, 2nd Floor, 1900, La Plata, Buenos Aires, Argentina

    María José Abasolo

Authors
  1. Lucas Benjamin Cicerchia
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  2. María José Abasolo
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  3. Claudia Cecilia Russo
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Corresponding author

Correspondence to Lucas Benjamin Cicerchia .

Editor information

Editors and Affiliations

  1. III-LIDI, Facultad de Informatica, Universidad Nacional de La Plata and CIC, La Plata, Argentina

    Enzo Rucci

  2. III-LIDI, Facultad de Informática, Universidad Nacional de La Plata and CIC, La Plata, Argentina

    Marcelo Naiouf

  3. III-LIDI, Facultad de Informática, Universidad Nacional de La Plata and CIC, La Plata, Argentina

    Franco Chichizola

  4. III-LIDI, Facultad de Informática, Universidad Nacional de La Plata and CIC, La Plata, Argentina

    Laura De Giusti

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Cicerchia, L.B., Abasolo, M.J., Russo, C.C. (2020). Classification of Summer Crops Using Active Learning Techniques on Landsat Images in the Northwest of the Province of Buenos Aires. In: Rucci, E., Naiouf, M., Chichizola, F., De Giusti, L. (eds) Cloud Computing, Big Data & Emerging Topics. JCC-BD&ET 2020. Communications in Computer and Information Science, vol 1291. Springer, Cham. https://doi.org/10.1007/978-3-030-61218-4_10

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  • DOI: https://doi.org/10.1007/978-3-030-61218-4_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61217-7

  • Online ISBN: 978-3-030-61218-4

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