Predicting stem borer density in maize using RapidEye data and generalized linear models-Reference-Cited by-同舟云学术

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Predicting stem borer density in maize using RapidEye data and generalized linear models

Published:2017-05 Issue: Volume:57 Page:61-74
ISSN:0303-2434
Container-title:International Journal of Applied Earth Observation and Geoinformation
language:en
Short-container-title:International Journal of Applied Earth Observation and Geoinformation

Author:

Abdel-Rahman Elfatih M.,Landmann Tobias,Kyalo Richard,Ong’amo George,Mwalusepo Sizah,Sulieman Saad,Ru Bruno Le

Funder

United Kingdom Department for International Development

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Earth-Surface Processes,Global and Planetary Change

Reference86 articles.

1. Potential of spectroscopic data sets for sugarcane thrips (Fulmekiola serrata Kobus) damage detection;Abdel-Rahman;Int. J. Remote Sens.,2010

2. Estimation of thrips (Fulmekiola serrata Kobus) density in sugarcane using leaf-level hyperspectral data;Abdel-Rahman;S. Afr. J. Plant Soil,2013

3. Categorical Data Analysis;Agresti,2002

4. A review of remote sensing methods for biomass feedstock production;Ahamed;J. Biomass Bioenergy,2011

5. Fast and accurate detection and classification of plant diseases;Al-Hiary;Int. J. Comput. Appl.,2011

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