Determining The Climatologically Suitable Areas
For Wheat Production Using MODIS-NDVI In
Mashhad, Iran
Author(s)
S. H. Sanaeinejad, S. M. Hasheminiya & S. Khojasteh
Abstract
One of the most important factors in sustainable irrigation is the adaptability of
crops to climate. Vegetative vigor or "greenness" of wheat could be considered
as an appropriate index to measure water availability and deficiency stress and
also plant health, plant density and quality. The index is called Normalized
Difference Vegetation Index (NDVI). In this study MODIS-NDVI values were
compared with climatological parameters to assess the relations between
vegetative vigor and climatological parameters. The NDVI values for three
selected wheat farms in Mashhad area were calculated using MODIS images for
2003 and 2004 growing seasons. The data of four climatological parameters
including air temperature, precipitation, relative humidity and sunshine hours
were also collected from the nearest weather stations. Then a multi-regression
statistical analysis was performed to find the relation between wheat NDVI and
climatological parameters in the study area. Pertaining statistical methods
including Mixed, and Stepwise (Forward and Backward) were used in the
analysis. Scattering matrix was used to determine the data scattering of the
models and NDVI values for comparison. The results showed that backward
method was more appropriate than the other two methods for predicting NDVI
values of the study area. After finalizing this model the results were statistically
tested using 20% of the samples for the test purpose and the remaining 80% for
running the model. The results showed that there was no significant difference
between Backward, Testing Backward and Training Backward models. The
results from the latter method showed that the NDVI of the pixels could be
estimated for 79% of the cases. It can be stated that the rest of NDVI values
could be affected by other environmental parameters such as soil type and
characteristics, topographical conditions, agronomical practices, plant diseases
and other unknown factors. Finally, some maps were developed showing the
potential wheat farming in the area according to the model results.
Keywords: NDVI, wheat, GIS, multi-regression model, MODIS.
Keywords
NDVI, wheat, GIS, multi-regression model, MODIS.
Related Book
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