Crop area estimation using high and medium resolution satellite imagery in areas with complex topography

Journal of Geophysical Research D: Atmospheres
By: , and 

Links

Abstract

Reliable estimates of cropped area (CA) in developing countries with chronic food shortages are essential for emergency relief and the design of appropriate market-based food security programs. Satellite interpretation of CA is an effective alternative to extensive and costly field surveys, which fail to represent the spatial heterogeneity at the country-level. Bias-corrected, texture based classifications show little deviation from actual crop inventories, when estimates derived from aerial photographs or field measurements are used to remove systematic errors in medium resolution estimates. In this paper, we demonstrate a hybrid high-medium resolution technique for Central Ethiopia that combines spatially limited unbiased estimates from IKONOS images, with spatially extensive Landsat ETM+ interpretations, land-cover, and SRTM-based topography. Logistic regression is used to derive the probability of a location being crop. These individual points are then aggregated to produce regional estimates of CA. District-level analysis of Landsat based estimates showed CA totals which supported the estimates of the Bureau of Agriculture and Rural Development. Continued work will evaluate the technique in other parts of Africa, while segmentation algorithms will be evaluated, in order to automate classification of medium resolution imagery for routine CA estimation in the future.

Publication type Article
Publication Subtype Journal Article
Title Crop area estimation using high and medium resolution satellite imagery in areas with complex topography
Series title Journal of Geophysical Research D: Atmospheres
DOI 10.1029/2007JD009175
Volume 113
Issue 14
Year Published 2008
Language English
Publisher AGU Publications
Contributing office(s) Earth Resources Observation and Science (EROS) Center
Description D14112: 8 p.
Online Only (Y/N) N
Additional Online Files (Y/N) N
Google Analytic Metrics Metrics page
Additional publication details