EVALUATION OF IMAGE PROCESSING TECHNIQUES IN ENVIRONMENTAL IMPACT IDENTIFICATION IN POWERLINE

Claudionor Ribeiro Silva, Samuel Lacerda de Andrade, Admilson Penha Pacheco

Abstract


The projects in the energy sector are basically composed of cables and metal structures. While providing benefits, installation and operation of these projects have significant environmental impacts along its path. The aim of this study was to evaluate image processing techniques to identify environmental impacts in energy powerline (path: Ibicoara-Brumado in Bahia / Brazil). Tests were performed on orthophotos with MaxVer classification and segmentation process object-oriented, with experiments integrating LiDAR. The results were analyzed on the basis of commission errors (user accuracy), omission errors (producer accuracy) and kappa index. According to Kappa index calculated, all tests showed ratings classified as excellent. The use of integrated LiDAR with orthophotos demonstrated an improvement in refining the results, with higher accuracy in classification and segmentation. The main evidence of environmental impacts is areas with exposed soil related to access roads, implementation of the infrastructure and use/occupation with agriculture. The area related to exposed soil was 16% demonstrating the need for prevention and conservation actions in LT projects.


Keywords


LiDAR, Impactos ambientais, Linhas de transmissão de energia

References


Andrade A. F., Centeno, J. A. S. (2003). Integração de informações espectrais e de forma na classificação de imagens com redes neurais. Boletim de Ciências Geodésicas, v. 09 (02), 217-231.

ANEEL – (2014) Agência Nacional de Energia Elétrica Linhas de Transmissão. Disponível em: . Acesso em: 28/04/2014.

Arcoverde, G. F. B., Epiphanio, J. C. N., Martins, V. A., Maeda, E. E., Fonseca, L. M. G. (2010). Mapeamento de citrus: avaliação de classificações por árvore de decisão. Revista Brasileira de Cartografia, v. 62 (1), 91-102.

Baatz, M., Schäpe, A. (2000). Multiresolution segmentation: an optimization approach for high quality multi‑scale image segmentation. Journal of Photogrammetry and Remote Sensing, v.58, 12‑23.

Blaschke, T. (2010). Object‑based image analysis for remote sensing. Journal of Photogrammetry and Remote Sensing, v.65, 02-16.

Botelho, M. F., Centeno, J. A. S. (2005). Uso integrado de imagem de alta resolução espacial e altura derivada do LASER Scanner na escolha do classificador orientado a região. Boletim de Ciências Geodésicas, Curitiba, v. 11 (01), 71-87.

Costa, D. T., Vaz, J. S., Lopes, J. S. F. (2012). Grandes Impactos Ambientais no Mundo. Caderno de Meio Ambiente e Sustentabilidade. V. 01(01), 56-73.

Hay, G. J., Castilla, G., (2008). Geographic Object-Based Image Analysis (GEOBIA): A new name for a new discipline. In: Blaschke, T., Lang, S., Hay, G(Eds.), Object Based Image Analysis. Springer, New York, 93–112.

Landis, J. R., Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, v. 33(01), 159-174.

Makarau, A., Palubinskas, G., Reinartz, P. (2011). Multi-sensor data fusion for urban area classification. In: Urban Remote Sensing Event 2011, Munique, 21-24.

Pinho, C. M. D. de, Fonseca, L. M. G., Korting, T. S., Almeida, C. M. de, Kux, H. J. H. (2012). Land‑cover classification of an intra-urban environment using high-resolution images and object‑based image analysis. International Journal of Remote Sensing, v.33, 5973‑5995.

Platt, R. V., Rapoza, L. (2008). An evaluation of an object‑oriented paradigm for land use/land cover classification. The Professional Geographer, v.60, 87‑100.

RIMA – (2014). Relatório de Impacto Ambiental LT 230 Kv Ibicoara/ Brumado II C1 e SE Ibicoara 230/138. Disponível em: . Acessado em: 08/10/2014.

Silva, C. R., Pacheco, A. P., Valente, S. (2014). Análise de dados SRTM e imagens CBERS 2b na identificação de áreas susceptíveis à ocupação irregular em faixa de servidão de linha de transmissão de energia elétrica. Ciência e Natura, v. 36(02), 128–136.




DOI: http://dx.doi.org/10.5902/2179460X19534

Refbacks

  • There are currently no refbacks.


Copyright (c)



Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.