Testing a high-resolution satellite interpretation technique for crop area monitoring in developing countries

International Journal of Remote Sensing
By: , and 

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Abstract

District-level crop area (CA) is a highly uncertain term in food production equations, which are used to allocate food aid and implement appropriate food security initiatives. Remote sensing studies typically overestimate CA and production, as subsistence plots are exaggerated at coarser resolution, which leads to overoptimistic food reports. In this study, medium-resolution (MR) Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images were manually classified for Niger and corrected using CA estimates derived from high-resolution (HR) sample image, topographic and socioeconomic data. A logistic model with smoothing splines was used to compute the block-average (0.1°) probability of an area being cropped. Livelihood zones and elevation explained 75% of the deviance in CA, while MR did not add explanatory power. The model overestimates CA when compared to the national inventory, possibly because of temporal changes in intercropping and the exclusion of some staple crops in the national inventory.

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Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Testing a high-resolution satellite interpretation technique for crop area monitoring in developing countries
Series title International Journal of Remote Sensing
DOI 10.1080/01431161.2010.532168
Volume 32
Issue 23
Year Published 2011
Language English
Publisher Taylor & Francis
Contributing office(s) Earth Resources Observation and Science (EROS) Center
Description 16 p.
First page 7997
Last page 8012
Country Niger
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