Abstract

Remote sensing has been investigated the generation of spatial variability maps in agriculture as a possible alternative. The objective of this work was to evaluate multispectral aerial digital videographic images, regarding their potential in the grain crops yield estimate and in the delineation of management zones. Yield maps were also used. They refer to the two study areas, cultivated with wheat, in the winter of 2001, and with soybean, in the summer of 2002. The images were geometrically rectified and radiometrically normalized. Simple linear regression was also performed between images and yield maps, pixel-to-pixel, with very different results for the two areas. The same happened when the degree of agreement between crops yield and image data was analyzed through the Kappa Index. Aerial multispectral videography has a good potential in the delineation of management zones in areas with large spatial variability.

Highlights

  • Remote sensing has been investigated the generation of spatial variability maps in agriculture as a possible alternative

  • They refer to the two study areas, cultivated with wheat, in the winter of 2001, and with soybean, in the summer of 2002

  • Aerial multispectral videography has a good potential in the delineation of management zones in areas with large spatial variability

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Summary

Material e métodos

O trabalho foi realizado em Castro, Estado do Paraná, na região dos Campos Gerais, em áreas de cooperados da Fundação ABC. De maio a setembro de 2001 a área 1 foi cultivada com trigo da variedade CD-105 e a área 2 com a variedade CV OR-1, ambas com 0,17 m entre linhas. No verão seguinte (novembro de 2001 a fevereiro de 2002) as duas áreas foram cultivadas com soja da variedade FT-Abyara, cultivada com 0,40 m entre linhas. Foram obtidas imagens das duas áreas, nas duas épocas, com uma câmera de vídeo digital multiespectral (Duncantech MS3100), com alta resolução espacial (um metro) em três faixas coregistradas que utilizam um prisma com três sensores de imagem CCDs (“charge-coupled device”), que cobrem as regiões espectrais do azul (450 - 520 nm), verde (520 – 600 nm), vermelho (630 - 690 nm) e infravermelho próximo (760 1100 nm). O ajuste do ganho e o controle de tempo de exposição são independentes para cada canal

Processamento dos mapas de produtividade
Obtenção e tratamento das imagens
Determinação dos índices de vegetação
Análise dos resultados
Imagens aéreas para as culturas da soja e do trigo
Regressão entre variáveis
Vermelho Infravermelho próximo NDVI
Análise das variáveis classificadas em duas categorias
Grau de concordância entre as variáveis classificadas em duas categorias
Infravermelho próximo NDVI
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