Relationship between cotton productivity and variability of NDVI obtained by landsat images

Authors

  • Fabio Henrique Rojo Baio Universidade Federal de Mato Grosso do Sul
  • Danilo Carvalho Neves Universidade Federal de Mato Grosso do Sul
  • Cid Naudi da Silva Campos Universidade Federal de Mato Grosso do Sul
  • Paulo Eduardo Teodoro

DOI:

https://doi.org/10.14393/BJ-v34n6a2018-39583

Keywords:

coefficient of variation, orbital image, vegetation index.

Abstract

The availability of satellite images has generated a large number of regional and global studies on vegetation mapping. Such studies have related the growth parameters, nutrient status, physiological responses, and water resources to the yield of agricultural crops or native vegetation. The NDVI (Normalized Difference Vegetation Index) is associated with parameters of growth and yield with readings at several moments of the crop cycle. The objective of this work was to correlate the yield and variability of the NDVI in cotton fields by analyzing Landsat satellite images acquired over nine growing seasons. The study involved the analysis of 101 cotton production fields located in West-Central Brazil. One Landsat image was used during each crop cycle, and the average yield was computed based on total fiber harvested at each field. The fiber yield ranged from 393 to 2,030 kg ha-1, and its correlation with NDVI was 0.37. The coefficient of variation (CV) had a negative correlation with yield, approximating -58.1 kg ha-1 for every one percent increment of the CV. The CV explained the yield variability over the cotton fields more accurately than the average absolute NDVI value.

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Published

2018-12-06

How to Cite

BAIO, F.H.R., NEVES, D.C., CAMPOS, C.N. da S. and TEODORO, P.E., 2018. Relationship between cotton productivity and variability of NDVI obtained by landsat images . Bioscience Journal [online], vol. 34, no. 6, pp. 197–205. [Accessed28 November 2022]. DOI 10.14393/BJ-v34n6a2018-39583. Available from: https://seer.ufu.br/index.php/biosciencejournal/article/view/39583.

Issue

Section

Agricultural Sciences