Using spatial rainfall and products from the MODIS sensor to improve an existing maize yield estimation system

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dc.contributor.author Frost, Celeste
dc.date.accessioned 2008-08-07T13:54:35Z
dc.date.available 2008-08-07T13:54:35Z
dc.date.issued 2008-08-07T13:54:35Z
dc.identifier.uri http://hdl.handle.net/10539/5288
dc.description.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. en
dc.format.extent 11790602 bytes
dc.format.mimetype application/pdf
dc.language.iso en en
dc.subject MODIS sensor en
dc.subject maize yield estimation en
dc.subject GIS en
dc.subject remote sensing en
dc.title Using spatial rainfall and products from the MODIS sensor to improve an existing maize yield estimation system en
dc.type Thesis en


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