Study of biophysical parameters using remote sensing techniques to Quixeré-CE region.

Camilla K Borges

doi:10.5935/2237-2202.20160028

Abstract

This work aims to analyze the behavior and the spatial variability of energy fluxes, albedo, surface temperature and vegetation index (NDVI) through the SEBAL algorithm, used in remote sensing for different surfaces in the region of Quixeré-EC. It was used TM- Landsat 5 satellite images for the dates October 24, 2005 and August 8, 2006, where the SEBAL algorithm was applied to calculate the fluxes of H, LE, Rn, G, and the surface albedo. From the clippings of a coverage area of banana orchard, savanna and bare soil, in order to check the H + LE and Rn-G components of energy balance. Correlations greater than 0.99 was observed between the components of energy balance H + LE and Rn-G, the relationship between surface albedo and radiation balance in the orchard area showed higher correlations to 0.88, the area comprised by savanna, for the day 297 showed no good correlation between variables, approximately 69% of unexplained variation in day 220 was about 0.88 correlation between the variables, this fact is associated homogeneous characteristics of the area that presented an increase of moisture available in relation to day 297.

Highlights

Climate change caused by human action, has brought the need for modeling of environmental parameters of the surface and atmosphere, to learn more about the use of transformation processes and occupation (Bezerra et al, 2014).With the improvement of the techniques applied in remote sensing for monitoring several meteorological and environmental phenomena, in order to help the weather forecast at, estimating water needs of a culture, crop and climate change, etc
SEBAL (Surface Energy Balance Algorithm for Land) allows the estimation of energy flows that occur in the Earth's surface interface with the atmosphere from the data obtained through remote sensing
To calculate the Surface Albedo it was used the correction of the planetary albedo for atmospheric transmissivity (Allen, 2002): α α toa α p τsw 2 αp is reflected solar radiation to the satellite ranging between 0.025 and 0.04, but for the SEBAL model is recommended to use the value of 0.03, based on Bastiaanssen (2000), and τsw is the atmospheric transmittance defined as the fraction of incident radiation transmitted through the atmosphere by the effects of absorption and reflection, for clear sky conditions (Allen, 2002): τsw 0,75 2.10 5 z The Normalized Difference Vegetation Index (NDVI) is given in terms of the bands near infrared (ρ4 ) and red (ρ3) (Allen, 2002)

Summary

Introduction

Climate change caused by human action, has brought the need for modeling of environmental parameters of the surface and atmosphere, to learn more about the use of transformation processes and occupation (Bezerra et al, 2014).With the improvement of the techniques applied in remote sensing for monitoring several meteorological and environmental phenomena, in order to help the weather forecast at, estimating water needs of a culture, crop and climate change, etc. The application of remote sensing techniques make it possible to analyze the spatial variability, making it advantageous technical and budgetary the point of view (Santos, 2009; Borges, 2013). In this sense, SEBAL (Surface Energy Balance Algorithm for Land) allows the estimation of energy flows that occur in the Earth's surface interface with the atmosphere from the data obtained through remote sensing. Latent heat flow is determined as a residue of the energy balance, the net radiation, heat flow in soil

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