Home // GEOProcessing 2021, The Thirteenth International Conference on Advanced Geographic Information Systems, Applications, and Services // View article
Authors:
Flávia Domingos Pacheco
Maíra Ramalho Matias
Gabriel Máximo Silva
Anielli Rosane Souza
Yosio Edemir Shimabukuro
Maria Isabel Sobral Escada
Keywords: digital image processing; segmentation; land use; land cover; smallholders; planetscope
Abstract:
This paper aims to test different methods for image classification focusing on small-scale agriculture in the region of Mocajuba and Cametá, municipalities in the Northeast of Pará state, Brazil. It is an important land use class, always ignored by Land-Use and Land-Cover monitoring systems because of its small size and variable spectral signature. We used an image from the PlanetScope Surface Reflectance Mosaics (Analysis Ready) with spatial resolution of 4.77 meters and 4 spectral bands (red, green, blue and infra-red). After proceeding with a multiresolution segmentation to identify image objects, two object-oriented classification algorithms were tested: Adapted Nearest-neighbor and C5.0 Decision trees algorithms. We selected 122 random points using the images available on Google Earth Pro as reference to assess the accuracy of classifications. Afterwards, confusion matrices were generated. Both methods showed similar overall accuracy and kappa value. However, C5.0 Decision trees reached a higher producer’s accuracy to small-scale agriculture (75%) in comparison to Adapted Nearest-neighbor (65%). The average size of the small-scale agriculture segments estimated was less than 1 ha in both maps, showing the need to carry out studies on scales of greater detail, preferably with images of high spatial resolution to represent these systems properly. In this study, C5.0 Decision trees had the best result, representing the most suitable method for mapping small-scale agriculture in Brazilian Amazon.
Pages: 12 to 19
Copyright: Copyright (c) The Government of Brazil, 2021. Used by permission to IARIA.
Publication date: July 18, 2021
Published in: conference
ISSN: 2308-393X
ISBN: 978-1-61208-871-6
Location: Nice, France
Dates: from July 18, 2021 to July 22, 2021