Using spatial rainfall and products from the MODIS sensor to improve an existing maize yield estimation system
Date
2008-08-07T13:54:35Z
Authors
Frost, Celeste
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Abstract
Abstract
After deregulation of the agricultural markets in South Africa in 1997, the estimated maize
crop could no longer be verified against the actual crop, due to the lack of control data from
the Maize Control Board. This drove the need to explore remotely sensed data as a
supplement to the current crop estimation methodology to improve crop estimations.
Input data for the development of a Geographic Information System (GIS)-based model
consisted of objective yield point data, Moderate Resolution Imaging Spectroradiometer
(MODIS) Normalised Difference Vegetation Index (NDVI) images and rainfall grids.
Rainfall grids were interpolated from weather station data. NDVI values were obtained from
the MODIS sensor aboard the Terra platform. Objective yield point field survey data for the
2001/2002 growing season were utilised since dry-land or irrigated conditions were recorded
for that season.
MODIS NDVI values corresponded well with the growing stages and age of the maize plants
after being adjusted to reflect the crop’s age rather than the Julian date. Rainfall values were
extracted from rainfall grids and also aligned with the age of the maize plants. This is a
suggested alternative to the traditional method of using the mean NDVI for several districts
in a region over a Julian growing period of 11 months according to Julian dates.
South African maize production areas extend over seven (7) provinces with eight
(8) different temperature and rainfall zones (du Plessis, 2004).
Planting-date zones based on the uniform age of the maize plants were developed from
objective yield Global Positioning System (GPS) points for the 2001/2002 growing season
and compared with the 2004/2005 growing season (Frost and Kneen, 2006). Planting dates
were interpolated from these planting zones for objective yield GPS points which were
missing planting dates in the survey database. MODIS imagery is affordable (free) and four
(4) images cover the whole of South Africa daily, while one (1) image covers the study area
daily. Several recommendations, such as establishing yield equations for a normal, dry, and
wet season were made. It is also suggested that dry-land and irrigated areas continue to be
evaluated separately in future.
Description
Keywords
MODIS sensor, maize yield estimation, GIS, remote sensing