METHOD FOR EVALUATING PLANT COVER AND QUANTIFICATION USING PIXEL TO PIXEL CORRELATION INDICES

Authors

  • José carlos de Souza Department of Geography of the Goiás State University, GO, Brazil.
  • Elfany Reis do Nascimento Lopes Laboratory of Geoprocessing and Environmental Mathematical Modeling of the Paulista State University - Institute of Science and Technology of Sorocaba.
  • Jocy Ana Paixão de Sousa Laboratory of Geoprocessing and Environmental Mathematical Modeling of the Paulista State University - Institute of Science and Technology of Sorocaba.
  • Antônio Cesar Germano Martins Paulista State University - Institute of Science and Technology of Sorocaba.
  • Roberto Wagner Lourenço Paulista State University - Institute of Science and Technology of Sorocaba.

DOI:

https://doi.org/10.4090/juee.2018.v12n2.245-256

Keywords:

Vegetation index, Remote sensing, Correlation Matrixes, Pixels, Plant Cover.

Abstract

This study brings results on Normalized Difference Vegetation Index (NDVI), the Adjusted Vegetation Index of Soil (SAVI) and the Index of Water by Normalized Difference (NDWI) through a method that uses correlation matrices built on a pixel to pixel combination for spatial and temporal analysis of plant cover. The study was developed by using Landsat 8 images from January and August, 2015. Image processing was performed with ArcGis and Matlab building correlation matrices to evaluate variations of each index in Brazilian vegetation. Results showed decreasing values of the three indices from wet to dry period. Climatic conditions influenced on the vigor and moisture content of vegetation. The pixel to pixel correlation method is appropriated to study vegetation changes and quantify increase, decrease or maintenance of vegetation.

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Author Biographies

José carlos de Souza, Department of Geography of the Goiás State University, GO, Brazil.

Geographer formed by Goiás State University Master in Geography from the Goiás Federal University. PhD in Environmental Sciences from the Paulista State University. Professor of the Department of Geography of the Goiás State University.

Elfany Reis do Nascimento Lopes, Laboratory of Geoprocessing and Environmental Mathematical Modeling of the Paulista State University - Institute of Science and Technology of Sorocaba.

PhD in Environmental Sciences from the Paulista State University.

Jocy Ana Paixão de Sousa, Laboratory of Geoprocessing and Environmental Mathematical Modeling of the Paulista State University - Institute of Science and Technology of Sorocaba.

Master in Environmental Sciences from the Paulista State University.

Antônio Cesar Germano Martins, Paulista State University - Institute of Science and Technology of Sorocaba.

PhD in Electrical Engineering from the São Paulo University. Professor of the Paulista State University - Institute of Science and Technology of Sorocaba

Roberto Wagner Lourenço, Paulista State University - Institute of Science and Technology of Sorocaba.

PhD in Geosciences and Environment from the Paulista State University. Professor of the Paulista State University - Institute of Science and Technology of Sorocaba

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Published

2019-01-03

Issue

Vol 12, No 2 (2018)

Section

Articles

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