Relationship between remote sensing data and field-observed interril erosion

Authors

  • André Geraldo de Lima Moraes Universidade Federal Rural do Rio de Janeiro, Instituto de Agronomia, Departamento de Solos, Rodovia BR-465, Km 7, Campus Universitário, CEP 23851-970 Seropédica, RJ.
  • Daniel Fonseca de Carvalho Universidade Federal Rural do Rio de Janeiro, Instituto de Tecnologia, Departamento de Engenharia, Rodovia BR-465, Km 7, Campus Universitário, CEP 23851-970 Seropédica, RJ.
  • Mauro Antonio Homem Antunes Universidade Federal Rural do Rio de Janeiro, Instituto de Tecnologia, Departamento de Engenharia, Rodovia BR-465, Km 7, Campus Universitário, CEP 23851-970 Seropédica, RJ.
  • Marcos Bacis Ceddia Universidade Federal Rural do Rio de Janeiro, Instituto de Agronomia, Departamento de Solos, Rodovia BR-465, Km 7, Campus Universitário, CEP 23851-970 Seropédica, RJ.

DOI:

https://doi.org/10.1590/S1678-3921.pab2018.v53.25395

Keywords:

linear spectral mixing analysis, rainfall simulator, vegetation indices

Abstract

The objective of this work was to evaluate the relationship between different remote sensing data, derived from satellite images, and interrill soil losses obtained in the field by using a portable rainfall simulator. The study was carried out in an area of a hydrographic basin, located in Médio Paraíba do Sul, in the state of Rio de Janeiro – one of the regions most affected by water erosion in Brazil. Evaluations were performed for different vegetation indices (NDVI, Savi, EVI, and EVI2) and fraction images (FI), derived from linear spectral mixture analysis (LSMA), obtained from RapidEye, Sentinel2A, and Landsat 8 OLI images. Vegetation indices are more adequate to predict soil loss than FI, highlighting EVI2, whose exponential model showed R2 of 0.74. The best prediction models are generated from the RapidEye image, which shows the highest spatial resolution among the sensors evaluated.

Author Biography

Daniel Fonseca de Carvalho, Universidade Federal Rural do Rio de Janeiro, Instituto de Tecnologia, Departamento de Engenharia, Rodovia BR-465, Km 7, Campus Universitário, CEP 23851-970 Seropédica, RJ.

 

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Published

2018-05-08

How to Cite

Moraes, A. G. de L., Carvalho, D. F. de, Antunes, M. A. H., & Ceddia, M. B. (2018). Relationship between remote sensing data and field-observed interril erosion. Pesquisa Agropecuaria Brasileira, 53(3), 332–341. https://doi.org/10.1590/S1678-3921.pab2018.v53.25395

Issue

v.53, n.3, mar. 2018

Section

REMOTE SENSING