SPECTRAL INDICES OF VEGETATION TO CAATINGA OF THE AREA OF SEMI-ARID OF RIO GRANDE OF NORTE, BRAZIL

Autores/as

  • Joel Medeiros Bezerra Postgraduate Program in Agricultural Engineering from the Federal University of Rural Pernambuco - UFRPE, Recife-PE, Brazil
  • Rochele Sheila Vasconcelos Doctoral student in Postgraduate Program in Agricultural Engineering from the Federal University of Rural Pernambuco - UFRPE, Recife-PE, Brazi
  • Geber Barbosa de Albuquerque Moura Agronomy Department - DEPA, UFRPE. Recife-PE, Brazil.
  • José Espínola Sobrinho Agronomy Department - DEPA, UFRPE. Recife-PE, Brazil.

DOI:

https://doi.org/10.5935/2237-2202.20120002

Palabras clave:

Remote sensing, rainfall, National Park of Furna Feia.

Resumen

The Caatinga is an exclusively Brazilian vegetation, predominantly in the Northeast, which covers 10% of the country, being an environment understudied, especially in view of remote sensing. Thus, the aim of this study is to analyze the spatial and temporal changes in vegetation of Caatinga, in the period from 2008 to 2011, through products and techniques of remote sensing data from the Landsat 5 TM, combined with weather data. The study was conducted in the area of the proposed National Park of Furna Feia located in the municipalities of Mossoró and Baraúna in the state of Rio Grande of Norte, situated in the semiarid region of northeastern Brazil. We used three images from Landsat 5 TM satellite orbit point 63 and 216 on the following dates: 13 August 2008, 01 September 2009 and 06 August 2011. The image processing for calculating the Normalized Difference Vegetation Index values (NDVI) was performed with ERDAS Imagine 9.1 and ArcGIS 9.3. The junction of products from remote sensing with weather data allowed a coherent and reasoned, where they subsidize an understanding of physical phenomena relating to rainfall variability of the response timeline of Caatinga vegetation. There was an increase in NDVI values over the years studied, noting the direct relationship with the occurrence of rainfall.

Biografía del autor/a

Joel Medeiros Bezerra, Postgraduate Program in Agricultural Engineering from the Federal University of Rural Pernambuco - UFRPE, Recife-PE, Brazil

Postgraduate Program in Agricultural Engineering from the Federal University of Rural Pernambuco - UFRPE, Recife-PE, Brazil

Rochele Sheila Vasconcelos, Doctoral student in Postgraduate Program in Agricultural Engineering from the Federal University of Rural Pernambuco - UFRPE, Recife-PE, Brazi

Postgraduate Program in Agricultural Engineering from the Federal University of Rural Pernambuco - UFRPE, Department of Rural Technology - DTR, Recife-PE, Brazil

Geber Barbosa de Albuquerque Moura, Agronomy Department - DEPA, UFRPE. Recife-PE, Brazil.

Adunct teacher, Agronomy Department - DEPA, UFRPE. Recife-PE, Brazil.

José Espínola Sobrinho, Agronomy Department - DEPA, UFRPE. Recife-PE, Brazil.

Adunct teacher, Agronomy Department - DEPA, UFRPE. Recife-PE, Brazil.

Citas

Allen, R.G. et al. Surface Energy Balance Algorithm for Land (SEBAL) – Advanced training and user’s Manual. Idaho, 98, 2002.

Barbosa, H.A.; Hueti, A.R.; Baethgen, W.E. 2006. A 20 - year study of NDVI variability over the Northeast Region of Brazil. Journal of Arid Environments, London, 67, 288-307.

Baret, G.; Guyot, G. 1991. Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sensing of Environment, (35), 161-173.

Bastiaanssen, W. G. M. 1995. Regionalization of surface flux densities and moisture indicators in composite terrain. Ph.D. Thesis, Wageningen Agricultural University, Wageningen, Netherlands, 237.

Bento, D. M.; Cruz, J. B. Proposta de criação de unidade de conservação federal parque nacional da Furna Feia Municípios de Baraúna e Mossoró no Estado do Rio Grande do Norte, 2011. Disponível em: http://www.icmbio.gov.br/portal/images/stories/o-quefazemos/parnadafurnafeirasite.pdf Acesso em: Maio de 2012.

Braga, C. C.; Sansigolo, C. A; Rao, T. V. R. Padrões de variabilidade espaciais e temporais de NDVI na região nordeste do Brasil utilizando análise fatorial. Anais....Congresso Brasileiro de Meteorologia (CBMET), 2000 Edição XI. Rio de Janeiro, RJ, 2000.

Brasil, Ibama; MMA. Monitoramento do desmatamento nos biomas brasileiros por satélite – Monitoramento do Bioma caatinga 2002 a 2008. Centro de Sensoriamento Remoto – CSR/IBAMA, 2010. Disponível em: <http://siscom.ibama.gov.br/monitorabiomas/caatinga/relatrio_tcnico_caatinga_72.pdf. Acesso em: Maio de 2012.

Brinkmann, K.; Dickhoefer, U.; Schlecht, E.; Buerkert, A. 2011. Quantification of aboveground rangeland productivity and anthropogenic degradation on the Arabian Peninsula using Landsat imagery and field inventory data. Remote Sensing of Environment, 115, 465-474.

Chagas, F.C. Normais Climatológicas para Mossoró, RN (1970-1996). ESAM, 1997, (Monografia de graduação em Engenharia Agronômica) 40.

Chander, G.; Markham, B. 2003. Revised Landsat-5 TM Radiometric Calibration Procedures ans Postcalibration Dynamic Ranges. IEEE Transactions on Geoscience and Remote Sensing. 41(11).

Cunha, J. E. B. L.; Rufino, I. A. A.; Silva, B. B.; Chaves, I. B. 2012. Dinâmica da cobertura vegetal para a Bacia de São João do Rio do Peixe, PB, utilizando-se sensoriamento remoto. Revista Brasileira de Engenharia Agrícola e Ambiental, 16(5). Campina Grande.

Embrapa Solos. Sistema brasileiro de classificação de solos. Rio de Janeiro, 1999. 412.

Filho, J. F. C.; Francisco, P. R. M.; Andrade, M. V.; Silva, L.; Dantas, R. L. D. Estimativa do índice de vegetação da diferença normalizada (NDVI) na microrregião de Sousa-PB utilizando imagens do CBERS-2. Anais... XV Congresso Brasileiro de Agrometeorológica, Aracaju-SE, 2007.

Gordon, L.J.; Steffen, W.; Jönsson, B.F.; Folke, C.; Falkenmark, M.; Johannesen, 2005. Å. Human modification of global water vapor flows from the land surface. Proceedings of the National Academy of Sciences, 102 (21), 7612-7617.

Gurgel, H.C.; Ferreira, N.J.; Luiz, A.J.B. 2003. Estudo da variabilidade do NDVI sobre o Brasil utilizando-se a análise de agrupamento. Revista Brasileira de Engenharia Agrícola e Ambiental, Campina Grande, 7(1), 85-90.

Holben, B.N.; Tucker, C.J.; Cheng-jeng, F. 1980. Spectral assessment of soyabeanleaf area and leaf biomass. Photogrammetric Engineering and Remote Sensing, 46(5), 651-656.

Markham, B. L.; Barker, L. L. 1987. Thematic mapper bandpass solar exoatmospherical irradiances, Int. Journal of Remote Sensing, 8(3), 517-523.

Ponzoni, F. J.; Shimabukuro, Y, E. Sensoriamento remoto no estudo da vegetação. São José dos Campos-SP. Ed: Parêntese, 2009.

Rodrigues, J. O.; Andrade, E. M.; Teixeira, A. S.; Silva, B. B. 2009. Sazonalidade de variáveis biofísicas em regiões semiáridas pelo emprego do sensoriamento remoto. Revista Engenharia Agrícola, Jaboticabal, 29(3), 452-465, jul./set.

Sampaio, E.V.S.B. 2003. Caracterização da caatinga e fatores ambientais que afetam a ecologia das plantas lenhosas. In: V.C. Sales (ed.). Ecossistemas brasileiros: manejo e conservação. Fortaleza, Expressão Gráfica e Editora.129-142.

Silva, K. S. T.; Lima, A.; Almeida, A. M. Estudo da sazonalidade da caatinga com dados de sensor MODIS. Anais...XV Simpósio Brasileiro de Sensoriamento Remoto- SBSR, Curitiba, PR, Brasil, 30 de abril á 05 de maio de 2011, INPE, 1881.

Warrick, A.W.; Nielsen, D.R. (1980) Spatial variability of soil physical properties in the field. In: Hillel, D. Applications of soil physics. New York: Academic Press.

Descargas

Publicado

2012-09-14

Cómo citar

Bezerra, J. M., Vasconcelos, R. S., Moura, G. B. de A., & Sobrinho, J. E. (2012). SPECTRAL INDICES OF VEGETATION TO CAATINGA OF THE AREA OF SEMI-ARID OF RIO GRANDE OF NORTE, BRAZIL. Journal of Hyperspectral Remote Sensing, 2(2), 010–024. https://doi.org/10.5935/2237-2202.20120002

Número

Sección

Hyperspectral remote sensing and Atmosphere

Artículos más leídos del mismo autor/a