CASE STUDY: IDENTIFICATION OF DESERTIFICATION IN THE YEARS 1999, 2006 AND 2011 IN MOSSORÓ-RN

Authors

  • Maryana Cavalcante Cordeiro UFCG
  • Nayara Arroxelas dos Santos UFCG
  • Virgínia Mirtes Alcântara Silva UFCG
  • Danielle de Melo Luiz UFAL
  • Vicente de Paulo Rodrigues da Silva UFCG

DOI:

https://doi.org/10.29150/jhrs.v5.4.p101-106

Keywords:

Remote Sensing, Desertification, Semiarid

Abstract

Desertification is defined as a process of destruction of the productive potential of the land by means of the pressure exerted by human activities on fragile ecosystems, whose regeneration capacity is low. The UN classifies desertification just the damage in range located in climates semiarid, arid and sub-humid dry. This process causes three types of impacts: environmental, social and economic. The objective of this study was to evaluate the efficiency of application of the Surface Energy Balance Algorithm for Land (SEBAL) model in estimating surface albedo, temperature and vegetation index, indicators those used to assess desertification in the city of Natal, Rio Grande do Norte, making a comparison between years 1999, 2006 and 2011, having as parameter data of TM / Landsat-5. The variables studied are important weather and climate parameters in meteorological studies. The results showed that the surface albedo is increasing, temperature and vegetation index had similar behaviors in 2006, in which these two corresponded to higher values ​​than in 1999 and 2011.

 

Author Biographies

Maryana Cavalcante Cordeiro, UFCG

Degree in meteorology by UFAL. I am currently a graduate student in meteorology UFCG. Practice areas: Remote Sensing, Urban Heat Islands, Air Pollution, Environmental Monitoring.

Nayara Arroxelas dos Santos, UFCG

Degree in meteorology by UFAL. I am currently a graduate student in meteorology UFCG.

Virgínia Mirtes Alcântara Silva, UFCG

PhD in Natural Resources.

Danielle de Melo Luiz, UFAL

Graduate student in meteorology.

Vicente de Paulo Rodrigues da Silva, UFCG

Professor of meteorology and natural resources.

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Published

2016-02-11

Issue

Section

Hyperspectral remote sensing and Atmosphere