| Autor: |
Elias Cavalcante Junior, Rafael Jacomel, Victor Ulisses Pugliese, Carlos Henrique Quartucci Forster, Gildarcio Sousa Goncalves, Adilson Marques da Cunha, Afonso Henriques Moreira Santos, Luiz Alberto Vieira Dias, Bruno Koshin Vazquez Iha, Paulo Marcelo Tasinaffo, Rafael Augusto Lopes Shigemura |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
Mathematics and Computer Science. 4:112 |
| ISSN: |
2575-6036 |
| DOI: |
10.11648/j.mcs.20190406.13 |
| Popis: |
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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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