Volume 4, Issue 6, November 2019, Page: 112-129
Determination of Forest Reserves Area Using Images Processed by Drones, Neural Networks and Monte Carlo Method
Paulo Marcelo Tasinaffo, Computer Science Department, Brazilian Aeronautics Institute of Technology (ITA), São Jose dos Campos, Brazil
Afonso Henriques Moreira Santos, Electrical Engineering Institute, Federal University of Itajuba (UNIFEI), Itajuba, Brazil
Elias Cavalcante Junior, Computer Science Department, Brazilian Aeronautics Institute of Technology (ITA), São Jose dos Campos, Brazil
Carlos Henrique Quartucci Forster, Computer Science Department, Brazilian Aeronautics Institute of Technology (ITA), São Jose dos Campos, Brazil
Rafael Augusto Lopes Shigemura, Computer Science Department, Brazilian Aeronautics Institute of Technology (ITA), São Jose dos Campos, Brazil
Rafael Jacomel, IBM Brazil, São Paulo, Brazil
Victor Ulisses Pugliese, Computer Science Department, Brazilian Aeronautics Institute of Technology (ITA), São Jose dos Campos, Brazil
Bruno Koshin Vazquez Iha, Mathematics and Statistics Institute, Sao Paulo University (USP), Sao Paulo, Brazil
Adilson Marques da Cunha, Computer Science Department, Brazilian Aeronautics Institute of Technology (ITA), São Jose dos Campos, Brazil
Gildarcio Sousa Goncalves, Computer Science Department, Brazilian Aeronautics Institute of Technology (ITA), São Jose dos Campos, Brazil
Luiz Alberto Vieira Dias, Computer Science Department, Brazilian Aeronautics Institute of Technology (ITA), São Jose dos Campos, Brazil
Received: Jun. 26, 2019;       Accepted: Jul. 30, 2019;       Published: Dec. 24, 2019
DOI: 10.11648/j.mcs.20190406.13      View  82      Downloads  42
Abstract
Land cover classification analysis from satellite imagery methods are important because they are the basis for characterizing surface conditions and evolution, supporting the management and optimization of land resources, evaluating global climate and environmental changes, and facilitating sustainable regional economic and social development. In order to address these necessities, artificial neural networks have been used extensively. In addition, other methods based on computer vision are very useful to solve this task. In this paper, the authors propose an approach based on Monte Carlo method and artificial neural networks in order to classify regions of small forest reserves from drones’ images and calculate their respective areas. Next to the small forest reserve will be extended a standard rectangular tarpaulin of 250 square meters and based on this reference it will be possible to calculate the area of the forest reserve if the ground is relatively flat. The proposed approach will be compared with a method based on watershed algorithm. The automatic calculation of the forest area through images generated by drones has much practical application for environmental engineers, for example, for the calculation of environmental impact and determination of carbon loss if such forests are consequently deforested.
Keywords
Remote Sensing, Artificial Neural Networks, Monte Carlo Methods, Watershed Algorithm, Unmanned Aerial Vehicles (UAVs), Drone-based Imagery
To cite this article
Paulo Marcelo Tasinaffo, Afonso Henriques Moreira Santos, Elias Cavalcante Junior, Carlos Henrique Quartucci Forster, Rafael Augusto Lopes Shigemura, Rafael Jacomel, Victor Ulisses Pugliese, Bruno Koshin Vazquez Iha, Adilson Marques da Cunha, Gildarcio Sousa Goncalves, Luiz Alberto Vieira Dias, Determination of Forest Reserves Area Using Images Processed by Drones, Neural Networks and Monte Carlo Method, Mathematics and Computer Science. Vol. 4, No. 6, 2019, pp. 112-129. doi: 10.11648/j.mcs.20190406.13
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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