ANALYSIS OF ENVIRONMENTAL PARAMETERS IN GILBUÉS – PI USING SATELLITE IMAGES
DOI:
https://doi.org/10.29150/jhrs.v4.4.p100-110Keywords:
Environmental degradation, remote sensing, SEBAL, S-SEBIAbstract
This paper aims to analyze the desertification process in the Gilbués region, southwestern portion of Piauí state, through remote sensing techniques with a perspective of verify whether there is a relationship of environmental parameters (surface albedo, NDVI, surface temperature, radiation and energy balances, as well as non-evaporative fraction) with the desertification process presented in this study area. We used images from the satellite Landsat 5-TM of August 19, 1994 and August 15, 2010 and applied the SEBAL and S-SEBI algorithms for obtaining environmental parameters analyzed. It was diagnosed cover removal of native vegetation, which may indicate areas undergoing to desertification and/or environmental degradation. Similarly, there was a reduction of surface net radiation, increased soil heat fluxes, reduction of energy used for evaporation and increases in the energy used for heating the soil and air, causing the temperature increase, and a systematic increase of the soil moisture deficit in the studied region.
References
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ALMEIDA-FILHO, R.; CARVALHO, C. M. Mapping land degradation in the Gilbués region, northeastern Brazil, using Landsat TM images. International Journal of Remote Sensing, v. 31, p. 1087–1094, 2010.
ASNER, G. P.; BORGHI, C. E.; OJEDA, R. A. Desertification in Central Argentina: changes in ecosystem carbon and nitrogen from imaging spectroscopy. Ecological Applications, v.13, p.629−648, 2003.
BASTIAANSSEN, W. G. M. SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey. Journal of Hydrology, v. 229, p. 87-100, 2000.
CARVALHO, C. M. Avaliação da desertificação no Sudoeste do Estado do Piauí- PI, através de técnicas de sensoriamento remoto. São Jose dos Campos: INPE, 2007.
CHANDER, G.; MARKHAM, B. Revised Landsat-5 TM Radiometric Calibration Procedures and Post calibration Dynamic Ranges. IEEE Transactions on Geoscience and Remote Sensing, v. 41, p. 2674-2677, 2003.
CREPANI, E.; MEDEIROS J.S. de; PALMEIRA, A.F. - Intensidade pluviométrica: uma maneira de tratar dados pluviométricos para análise da vulnerabilidade de paisagens à perda de solo. São José dos Campos: INPE, ago. 2004. 30 p. (INPE-11237-RPQ/760).
D’ODIORICO, P.; BHATTACHAN, A.; DAVIS, K. F.; RAVI, S.; RUNYAN, C. W. Global desertification: Drivers and feedbacks. Advances in Water Resources, v.51, p.326-344, 2013.
GARCÍA, M.; VILLAGARCÍA, L.; CONTRERAS, S.; DOMINGO, F.; PUIGDEFÁBREGAS, J. Comparison of Three Operative Models for Estimating the Surface Water Deficit using ASTER Reflective and Thermal Data. Sensors, v.7, p.860-883, 2007.
HUETE, A. R. A soil adjusted vegetation index – SAVI. Remote Sensing of Environment, v. 25, p. 295–309, 1988.
IICA, Instituto Interamericano de Cooperação para a Agricultura, 2013. Disponível em: http://www.iicadesertification.org.br/ Acesso em: 23/03/2013.
LAL, R. Carbon Sequestration in Dryland Ecosystems. Environmental Management, v.33, n.4, p.528-544, 2003.
MA, Y.; TSUKAMOTO, O.; HIROHIKO, I. Remote sensing parameterization of the processes of energy and water cycle over desertification areas. Science in China (Series D), v. 45 Supp., p. 47-53, 2002.
OKIN, G. S. Toward a unified view of biophysical land degradation processes in arid and semi-arid lands. In J. F. Reynolds; D. M. Stafford Smith (Eds.), Global Desertification: Do Humans Cause Deserts? p. 95−109, Berlin, Dahlem University Press, 2002.
PAN-BRASIL. Ministério do Meio Ambiente. Secretaria de Recursos Hídricos. Programa de Ação Nacional de Combate à Desertificação e Mitigação dos Efeitos da Seca: PAN – Brasília, 2004.
PEREZ-MARIN, A. M.; CAVALVANTE, A. M. B.; MEDEIROS, S. S.; TINÔCO, L. B. M.; SALCEDO, I. H. Núcleos de desertificação no semiárido brasileiro: ocorrência natural ou antrópica? Parcerias Estratégicas, v.17, n.34, p.87-106, 2012.
ROERINK, G. J.; SU, Z.; MENENTI, M. A Simple Remote Sensing Algorithm to Estimate the Surface Energy Balance. Physics and Chemistry of the Earth (B), v. 25, p. 147-157, 2000.
SANTOS, C. A. C.; SILVA, B. B. Estimativa da evapotranspiração da bananeira em região semiárida através do algoritmo S-SEBI. Revista Brasileira de Agrometeorologia, v. 16, p. 9-20, 2008.
SCHLESINGER, W. H.; REYNOLDS, J. F.; CUNNINGHAM, G. L.; HUENNEKE, L. F.; JARRELI, W. M.; VIRGINIA, R. A.; WHITFORD, W. G. Biological Feedbacks in Global Desertification. Science, v.247, p.1043-1048, 1990.
SOBRINO, J. A.; GOMEZ, M.; JIMENEZ-MUNOZ, J. C.; OLIOSO, A. Application of a simple algorithm to estimate daily evapotranspiration from NOAA-AVHRR images for the Iberian Peninsula. Remote Sensing of Environment, v. 110, p. 139-148, 2007.
SOBRINO, J. A.; GOMEZ, M.; JIMENEZ-MUNOZ, J. C.; OLIOSO, A.; CHEHBOUNI, G. A simple algorithm to estimate evapotranspiration from DAIS data: Application to the DAISEX Campaigns. Journal of Hydrology, v. 315, p. 117−125, 2005.
SOBRINO, J. A.; JACOB, F. Retrieval of evapotranspiration over the Alpilles/ReSeDA experimental site using airborne POLDER sensor and thermal camera. Remote Sensing of Environments, v. 96, p. 399-408, 2005.
VERSTRAETE, M. M.; SCHOLES, R. J.; SMITH, M. S. Climate and desertification: looking at an old problem through new lenses. Frontiers in Ecology and the Environment, v.7, p.421–428, 2009.
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Published
2014-05-14
How to Cite
Santos, Élder G. dos. (2014). ANALYSIS OF ENVIRONMENTAL PARAMETERS IN GILBUÉS – PI USING SATELLITE IMAGES. Journal of Hyperspectral Remote Sensing, 4(4), 100–110. https://doi.org/10.29150/jhrs.v4.4.p100-110
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Hyperspectral remote sensing and Atmosphere
