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Identification of croplands of winter cereals in Rio Grande do Sul state, Brazil, through unsupervised classification of normalized difference vegetation index images

Authors :
Amanda H. Junges
Denise C. Fontana
Daniele G. Pinto
Source :
Engenharia Agrícola, Vol 33, Iss 4, Pp 883-895 (2013)
Publication Year :
2013
Publisher :
Sociedade Brasileira de Engenharia Agrícola, 2013.

Abstract

This study aimed to propose methods to identify croplands cultivated with winter cereals in the northern region of Rio Grande do Sul State, Brazil. Thus, temporal profiles of Normalized Difference Vegetation Index (NDVI) from MODIS sensor, from April to December of the 2000 to 2008, were analyzed. Firstly, crop masks were elaborated by subtracting the minimum NDVI image (April to May) from the maximum NDVI image (June to October). Then, an unsupervised classification of NDVI images was carried out (Isodata), considering the crop mask areas. According to the results, crop masks allowed the identification of pixels with greatest green biomass variation. This variation might be associated or not with winter cereals areas established to grain production. The unsupervised classification generated classes in which NDVI temporal profiles were associated with water bodies, pastures, winter cereals for grain production and for soil cover. Temporal NDVI profiles of the class winter cereals for grain production were in agree with crop patterns in the region (developmental stage, management standard and sowing dates). Therefore, unsupervised classification based on crop masks allows distinguishing and monitoring winter cereal crops, which were similar in terms of morphology and phenology.

Details

Language :
English, Spanish; Castilian, Portuguese
ISSN :
01006916
Volume :
33
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Engenharia Agrícola
Publication Type :
Academic Journal
Accession number :
edsdoj.06ac7f5fcecb4f798b64f19f145e8e9a
Document Type :
article
Full Text :
https://doi.org/10.1590/S0100-69162013000400027